exo_bench: set temperature=0.0 for argmax sampling (drops decode overhead)

## Motivation

The RDMA setup instructions were missing a step: after booting to
Recovery mode, users need to open Terminal from the Utilities menu
before they can run the `rdma_ctl` command. Without this step, users
following the instructions wouldn't know how to access a terminal in
Recovery mode. This step was already in the README just not in the UI
notifications.

## Changes

Added a missing instruction step — "Open Terminal from the Utilities
menu" — to three instances of the RDMA setup flow in
`dashboard/src/routes/+page.svelte`.

## Why It Works

N/A copy change only. 

## Test Plan

### Manual Testing
Hardware: MacBook Pro M4 Max 48GB

### Automated Testing
No automated tests affected; this is a UI copy change only.

Co-authored-by: Sam Bradbury <sam@consultbradbury.com>

.github/workflows/build-app.yml

@@ -32,7 +32,6 @@ jobs:
       SPARKLE_ED25519_PRIVATE: ${{ secrets.SPARKLE_ED25519_PRIVATE }}
       SPARKLE_S3_BUCKET: ${{ secrets.SPARKLE_S3_BUCKET }}
       SPARKLE_S3_PREFIX: ${{ secrets.SPARKLE_S3_PREFIX }}
-      EXO_BUG_REPORT_PRESIGNED_URL_ENDPOINT: ${{ secrets.EXO_BUG_REPORT_PRESIGNED_URL_ENDPOINT }}
       AWS_REGION: ${{ secrets.AWS_REGION }}
       EXO_BUILD_NUMBER: ${{ github.run_number }}
       EXO_LIBP2P_NAMESPACE: ${{ github.ref_name }}
@@ -347,7 +346,6 @@ jobs:
             EXO_BUILD_COMMIT="$GITHUB_SHA" \
             SPARKLE_FEED_URL="$SPARKLE_FEED_URL" \
             SPARKLE_ED25519_PUBLIC="$SPARKLE_ED25519_PUBLIC" \
-            EXO_BUG_REPORT_PRESIGNED_URL_ENDPOINT="$EXO_BUG_REPORT_PRESIGNED_URL_ENDPOINT" \
             CODE_SIGNING_IDENTITY="$SIGNING_IDENTITY" \
             CODE_SIGN_INJECT_BASE_ENTITLEMENTS=YES
           mkdir -p ../../output

.mlx_typings/mlx/core/__init__.pyi

@@ -1767,12 +1767,12 @@ def clip(
         array: The clipped array.
     """
 
-def compile(
-    fun: Callable,
+def compile[F: Callable[..., object]](
+    fun: F,
     inputs: object | None = ...,
     outputs: object | None = ...,
     shapeless: bool = ...,
-) -> Callable:
+) -> F:
     """
     Returns a compiled function which produces the same output as ``fun``.
 
@@ -2915,8 +2915,8 @@ def gather_mm(
     a: array,
     b: array,
     /,
-    lhs_indices: array,
-    rhs_indices: array,
+    lhs_indices: array | None = ...,
+    rhs_indices: array | None = ...,
     *,
     sorted_indices: bool = ...,
     stream: Stream | Device | None = ...,
@@ -4707,6 +4707,7 @@ def softmax(
     /,
     axis: int | Sequence[int] | None = ...,
     *,
+    precise: bool = ...,
     stream: Stream | Device | None = ...,
 ) -> array:
     """

.mlx_typings/mlx/nn/layers/base.pyi

@@ -57,6 +57,10 @@ class Module(dict):
     def __init__(self) -> None:
         """Should be called by the subclasses of ``Module``."""
 
+    def __getitem__(self, key: str) -> mx.array | Module: ...
+    def get(
+        self, key: str, default: mx.array | Module | None = ...
+    ) -> mx.array | Module | None: ...
     @property
     def training(self):  # -> bool:
         """Boolean indicating if the model is in training mode."""

.mlx_typings/mlx_lm/generate.pyi

@@ -383,11 +383,12 @@ class GenerationBatch:
     state_machines: List[SequenceStateMachine]
     max_tokens: List[int]
     _current_tokens: Optional[mx.array]
-    _current_logprobs: List[mx.array]
-    _next_tokens: mx.array
-    _next_logprobs: List[mx.array]
-    _token_context: List[mx.array]
+    _current_logprobs: mx.array | List[mx.array]
+    _next_tokens: Optional[mx.array]
+    _next_logprobs: mx.array | List[mx.array]
+    _token_context: List[Any]
     _num_tokens: List[int]
+    _matcher_states: List[Any]
 
     def __init__(
         self,

.mlx_typings/mlx_lm/models/base.pyi

@@ -3,7 +3,7 @@ This type stub file was generated by pyright.
 """
 
 from dataclasses import dataclass
-from typing import Optional
+from typing import Any, Optional
 
 import mlx.core as mx
 
@@ -37,10 +37,10 @@ def quantized_scaled_dot_product_attention(
     bits: int = ...,
 ) -> mx.array: ...
 def scaled_dot_product_attention(
-    queries,
-    keys,
-    values,
-    cache,
+    queries: mx.array,
+    keys: mx.array,
+    values: mx.array,
+    cache: Optional[Any],
     scale: float,
     mask: Optional[mx.array],
     sinks: Optional[mx.array] = ...,

.mlx_typings/mlx_lm/models/deepseek_v4.pyi

@@ -0,0 +1,280 @@
+"""Type stubs for mlx_lm.models.deepseek_v4"""
+
+from dataclasses import dataclass
+from typing import Any, Dict, List, Optional
+
+import mlx.core as mx
+import mlx.nn as nn
+
+from .base import BaseModelArgs
+from .cache import ArraysCache, RotatingKVCache
+from .switch_layers import SwitchGLU
+
+@dataclass
+class ModelArgs(BaseModelArgs):
+    model_type: str
+    vocab_size: int
+    hidden_size: int
+    intermediate_size: int
+    moe_intermediate_size: int
+    num_hidden_layers: int
+    num_attention_heads: int
+    num_key_value_heads: int
+    n_shared_experts: Optional[int]
+    n_routed_experts: int
+    num_experts_per_tok: int
+    head_dim: int
+    qk_rope_head_dim: int
+    q_lora_rank: int
+    o_lora_rank: int
+    o_groups: int
+    sliding_window: int
+    hc_mult: int
+    hc_sinkhorn_iters: int
+    hc_eps: float
+    compress_ratios: Optional[List[int]]
+    compress_rope_theta: float
+    rope_theta: float
+    rope_scaling: Optional[Dict[str, Any]]
+    rms_norm_eps: float
+    swiglu_limit: float
+    attention_bias: bool
+    max_position_embeddings: int
+
+class DeepseekV4RoPE(nn.Module):
+    dims: int
+    freqs: mx.array
+
+    def __init__(
+        self,
+        dims: int,
+        base: float,
+        scaling_config: Optional[Dict[str, Any]] = None,
+    ) -> None: ...
+    def __call__(
+        self,
+        x: mx.array,
+        offset: int = 0,
+        inverse: bool = False,
+    ) -> mx.array: ...
+
+class HyperConnection(nn.Module):
+    dim: int
+    hc_mult: int
+    norm_eps: float
+
+    def __init__(
+        self,
+        dim: int,
+        hc_mult: int,
+        norm_eps: float,
+        sinkhorn_iters: int,
+        hc_eps: float,
+    ) -> None: ...
+
+class HyperHead(nn.Module):
+    dim: int
+    hc_mult: int
+
+    def __init__(
+        self,
+        dim: int,
+        hc_mult: int,
+        norm_eps: float,
+        hc_eps: float,
+    ) -> None: ...
+    def __call__(self, x: mx.array) -> mx.array: ...
+
+class Compressor(nn.Module):
+    dim: int
+    head_dim: int
+    rope_head_dim: int
+    compress_ratio: int
+    overlap: bool
+    wkv_gate: nn.Linear
+    ape: mx.array
+    norm: nn.RMSNorm
+    rope: DeepseekV4RoPE
+
+    def __init__(
+        self,
+        dim: int,
+        compress_ratio: int,
+        head_dim: int,
+        rope_head_dim: int,
+        rms_norm_eps: float,
+        rope: DeepseekV4RoPE,
+    ) -> None: ...
+    def __call__(
+        self,
+        x: mx.array,
+        cache: "DeepseekV4Cache",
+        offset: Any,
+        key: str = ...,
+    ) -> mx.array: ...
+
+class Indexer(nn.Module):
+    def __init__(
+        self,
+        args: ModelArgs,
+        compress_ratio: int,
+        rope: DeepseekV4RoPE,
+    ) -> None: ...
+
+class _CompressorBranch:
+    buffer_kv: Optional[mx.array]
+    buffer_gate: Optional[mx.array]
+    prev_kv: Optional[mx.array]
+    prev_gate: Optional[mx.array]
+    pool: Optional[mx.array]
+    buffer_lengths: Optional[List[int]]
+    pool_lengths: Optional[List[int]]
+    buffer_count: int
+    _new_pool_lengths: Optional[List[int]]
+
+    def __init__(self) -> None: ...
+
+class DeepseekV4Cache:
+    local: RotatingKVCache
+    offset: int
+    keys: Optional[mx.array]
+    values: Optional[mx.array]
+    state: Any
+    meta_state: Any
+    nbytes: int
+    _branches: Dict[str, _CompressorBranch]
+    _pending_lengths: Optional[List[int]]
+
+    def __init__(self, sliding_window: int) -> None: ...
+    def update_and_fetch(
+        self, keys: mx.array, values: mx.array
+    ) -> tuple[mx.array, mx.array]: ...
+    def is_trimmable(self) -> bool: ...
+    def trim(self, n: int) -> int: ...
+    def empty(self) -> bool: ...
+    def size(self) -> int: ...
+    def prepare(
+        self,
+        *,
+        left_padding: Optional[List[int]] = None,
+        lengths: Optional[List[int]] = None,
+        right_padding: Optional[List[int]] = None,
+    ) -> None: ...
+    def finalize(self) -> None: ...
+    def filter(self, batch_indices: mx.array) -> None: ...
+    def extend(self, other: "DeepseekV4Cache") -> None: ...
+    def extract(self, idx: int) -> "DeepseekV4Cache": ...
+    @classmethod
+    def merge(cls, caches: List["DeepseekV4Cache"]) -> "DeepseekV4Cache": ...
+
+class V4Attention(nn.Module):
+    args: ModelArgs
+    layer_id: int
+    dim: int
+    n_heads: int
+    head_dim: int
+    rope_head_dim: int
+    nope_head_dim: int
+    n_groups: int
+    q_lora_rank: int
+    o_lora_rank: int
+    window: int
+    eps: float
+    scale: float
+    compress_ratio: int
+    wqkv_a: nn.Linear
+    q_norm: nn.RMSNorm
+    wq_b: nn.Linear
+    kv_norm: nn.RMSNorm
+    attn_sink: mx.array
+    wo_a: nn.Linear
+    wo_b: nn.Linear
+    rope: DeepseekV4RoPE
+    compressor: Compressor
+    indexer: Indexer
+
+    def __init__(self, args: ModelArgs, layer_id: int) -> None: ...
+    def __call__(
+        self,
+        x: mx.array,
+        mask: Optional[mx.array] = None,
+        cache: Optional[Any] = None,
+    ) -> mx.array: ...
+
+class DeepseekV4MLP(nn.Module):
+    gate_proj: nn.Linear
+    up_proj: nn.Linear
+    down_proj: nn.Linear
+
+    def __init__(
+        self,
+        hidden_size: int,
+        intermediate_size: int,
+        swiglu_limit: float = 0.0,
+    ) -> None: ...
+    def __call__(self, x: mx.array) -> mx.array: ...
+
+class MoEGate(nn.Module):
+    weight: mx.array
+
+    def __init__(self, args: ModelArgs, layer_id: int) -> None: ...
+    def __call__(
+        self, x: mx.array, input_ids: mx.array
+    ) -> tuple[mx.array, mx.array]: ...
+
+class DeepseekV4MoE(nn.Module):
+    num_experts_per_tok: int
+    switch_mlp: SwitchGLU
+    gate: MoEGate
+    shared_experts: DeepseekV4MLP
+
+    def __init__(self, args: ModelArgs, layer_id: int) -> None: ...
+    def __call__(self, x: mx.array, input_ids: mx.array) -> mx.array: ...
+
+class DeepseekV4Block(nn.Module):
+    attn_norm: nn.RMSNorm
+    attn: V4Attention
+    hc_attn: HyperConnection
+    ffn_norm: nn.RMSNorm
+    ffn: DeepseekV4MoE
+    hc_ffn: HyperConnection
+
+    def __init__(self, args: ModelArgs, layer_id: int) -> None: ...
+    def __call__(
+        self,
+        h: mx.array,
+        cache: Optional[Any],
+        input_ids: mx.array,
+    ) -> mx.array: ...
+
+class DeepseekV4Model(nn.Module):
+    args: ModelArgs
+    vocab_size: int
+    embed_tokens: nn.Embedding
+    layers: list[DeepseekV4Block]
+    norm: nn.RMSNorm
+    hc_head: HyperHead
+
+    def __init__(self, args: ModelArgs) -> None: ...
+    def __call__(
+        self,
+        inputs: mx.array,
+        cache: Optional[List[Any]] = None,
+    ) -> mx.array: ...
+
+class Model(nn.Module):
+    args: ModelArgs
+    model_type: str
+    model: DeepseekV4Model
+    lm_head: nn.Linear
+
+    def __init__(self, args: ModelArgs) -> None: ...
+    def __call__(
+        self,
+        inputs: mx.array,
+        cache: Optional[List[Any]] = None,
+    ) -> mx.array: ...
+    def sanitize(self, weights: dict[str, Any]) -> dict[str, Any]: ...
+    def make_cache(self) -> list[RotatingKVCache | DeepseekV4Cache]: ...
+    @property
+    def layers(self) -> list[DeepseekV4Block]: ...

.mlx_typings/mlx_lm/models/gpt_oss.pyi

@@ -0,0 +1,103 @@
+"""Type stubs for mlx_lm.models.gpt_oss"""
+
+from dataclasses import dataclass
+from typing import Any, List, Optional
+
+import mlx.core as mx
+import mlx.nn as nn
+
+from .base import BaseModelArgs
+from .cache import KVCache
+from .switch_layers import SwitchGLU
+
+@dataclass
+class ModelArgs(BaseModelArgs):
+    model_type: str
+    hidden_size: int
+    intermediate_size: int
+    num_hidden_layers: int
+    num_attention_heads: int
+    num_key_value_heads: int
+    num_local_experts: int
+    num_experts_per_tok: int
+    vocab_size: int
+    rms_norm_eps: float
+    sliding_window: int
+    layer_types: Optional[List[str]]
+
+def mlx_topk(a: mx.array, k: int, axis: int = -1) -> tuple[mx.array, mx.array]: ...
+
+class AttentionBlock(nn.Module):
+    head_dim: int
+    num_attention_heads: int
+    num_key_value_heads: int
+    num_key_value_groups: int
+    sinks: mx.array
+    q_proj: nn.Linear
+    k_proj: nn.Linear
+    v_proj: nn.Linear
+    o_proj: nn.Linear
+    sm_scale: float
+    rope: nn.Module
+
+    def __init__(self, config: ModelArgs) -> None: ...
+    def __call__(
+        self,
+        x: mx.array,
+        mask: Optional[mx.array] = None,
+        cache: Optional[Any] = None,
+    ) -> mx.array: ...
+
+class TransformerBlock(nn.Module):
+    self_attn: AttentionBlock
+    mlp: MLPBlock
+
+    def __init__(self, config: ModelArgs) -> None: ...
+    def __call__(
+        self,
+        x: mx.array,
+        mask: Optional[mx.array] = None,
+        cache: Optional[Any] = None,
+    ) -> mx.array: ...
+
+class MLPBlock(nn.Module):
+    hidden_size: int
+    num_local_experts: int
+    num_experts_per_tok: int
+    experts: SwitchGLU
+    router: nn.Linear
+    sharding_group: Optional[mx.distributed.Group]
+
+    def __init__(self, config: ModelArgs) -> None: ...
+    def __call__(self, x: mx.array) -> mx.array: ...
+
+class GptOssMoeModel(nn.Module):
+    embed_tokens: nn.Embedding
+    norm: nn.RMSNorm
+    layer_types: List[str]
+    layers: list[TransformerBlock]
+    window_size: int
+    swa_idx: int
+    ga_idx: int
+
+    def __init__(self, args: ModelArgs) -> None: ...
+    def __call__(
+        self,
+        inputs: mx.array,
+        cache: Optional[Any] = None,
+    ) -> mx.array: ...
+
+class Model(nn.Module):
+    model_type: str
+    model: GptOssMoeModel
+    lm_head: nn.Linear
+
+    def __init__(self, args: ModelArgs) -> None: ...
+    def __call__(
+        self,
+        inputs: mx.array,
+        cache: Optional[Any] = None,
+    ) -> mx.array: ...
+    @property
+    def layers(self) -> list[nn.Module]: ...
+    def make_cache(self) -> list[KVCache]: ...

.mlx_typings/mlx_lm/models/minimax.pyi

@@ -0,0 +1,94 @@
+"""Type stubs for mlx_lm.models.minimax"""
+
+from dataclasses import dataclass
+from typing import Any, Optional
+
+import mlx.core as mx
+import mlx.nn as nn
+
+from .base import BaseModelArgs
+from .switch_layers import SwitchGLU
+
+@dataclass
+class ModelArgs(BaseModelArgs):
+    model_type: str
+    hidden_size: int
+    intermediate_size: int
+    num_hidden_layers: int
+    num_attention_heads: int
+    num_key_value_heads: int
+    num_local_experts: int
+    num_experts_per_tok: int
+    max_position_embeddings: int
+
+class MiniMaxAttention(nn.Module):
+    num_heads: int
+    num_attention_heads: int
+    num_key_value_heads: int
+    head_dim: int
+    scale: float
+    q_proj: nn.Linear
+    k_proj: nn.Linear
+    v_proj: nn.Linear
+    o_proj: nn.Linear
+    q_norm: nn.Module
+    k_norm: nn.Module
+    rope: nn.Module
+
+    def __init__(self, args: ModelArgs) -> None: ...
+    def __call__(
+        self,
+        x: mx.array,
+        mask: Optional[mx.array] = None,
+        cache: Optional[Any] = None,
+    ) -> mx.array: ...
+
+class MiniMaxSparseMoeBlock(nn.Module):
+    num_experts_per_tok: int
+    gate: nn.Linear
+    switch_mlp: SwitchGLU
+    e_score_correction_bias: mx.array
+    sharding_group: Optional[mx.distributed.Group]
+
+    def __init__(self, args: ModelArgs) -> None: ...
+    def __call__(self, x: mx.array) -> mx.array: ...
+
+class MiniMaxDecoderLayer(nn.Module):
+    self_attn: MiniMaxAttention
+    block_sparse_moe: MiniMaxSparseMoeBlock
+    input_layernorm: nn.RMSNorm
+    post_attention_layernorm: nn.RMSNorm
+
+    def __init__(self, args: ModelArgs) -> None: ...
+    def __call__(
+        self,
+        x: mx.array,
+        mask: Optional[mx.array] = None,
+        cache: Optional[Any] = None,
+    ) -> mx.array: ...
+
+class MiniMaxModel(nn.Module):
+    embed_tokens: nn.Embedding
+    layers: list[MiniMaxDecoderLayer]
+    norm: nn.RMSNorm
+
+    def __init__(self, args: ModelArgs) -> None: ...
+    def __call__(
+        self,
+        inputs: mx.array,
+        cache: Optional[Any] = None,
+    ) -> mx.array: ...
+
+class Model(nn.Module):
+    model_type: str
+    model: MiniMaxModel
+    lm_head: nn.Linear
+
+    def __init__(self, args: ModelArgs) -> None: ...
+    def __call__(
+        self,
+        inputs: mx.array,
+        cache: Optional[Any] = None,
+    ) -> mx.array: ...
+    @property
+    def layers(self) -> list[MiniMaxDecoderLayer]: ...

.mlx_typings/mlx_lm/models/nemotron_h.pyi

@@ -92,6 +92,15 @@ class NemotronHAttention(nn.Module):
         cache: Optional[KVCache] = None,
     ) -> mx.array: ...
 
+class MoEGate(nn.Module):
+    config: ModelArgs
+    top_k: int
+    norm_topk_prob: bool
+    weight: mx.array
+
+    def __init__(self, config: ModelArgs) -> None: ...
+    def __call__(self, x: mx.array) -> tuple[mx.array, mx.array]: ...
+
 class NemotronHMLP(nn.Module):
     up_proj: nn.Linear
     down_proj: nn.Linear
@@ -102,9 +111,14 @@ class NemotronHMLP(nn.Module):
     def __call__(self, x: mx.array) -> mx.array: ...
 
 class NemotronHMoE(nn.Module):
+    config: ModelArgs
     num_experts_per_tok: int
+    moe_latent_size: Optional[int]
     switch_mlp: SwitchMLP
+    gate: MoEGate
     shared_experts: NemotronHMLP
+    fc1_latent_proj: nn.Linear
+    fc2_latent_proj: nn.Linear
 
     def __init__(self, config: ModelArgs) -> None: ...
     def __call__(self, x: mx.array) -> mx.array: ...

.mlx_typings/mlx_lm/models/qwen3_next.pyi

@@ -71,6 +71,7 @@ class Qwen3NextAttention(nn.Module):
 class Qwen3NextSparseMoeBlock(nn.Module):
     norm_topk_prob: bool
     num_experts: int
+    num_experts_per_tok: int
     top_k: int
     gate: nn.Linear
     switch_mlp: SwitchGLU

app/EXO/EXO/ContentView.swift

@@ -16,22 +16,13 @@ struct ContentView: View {
     @EnvironmentObject private var updater: SparkleUpdater
     @EnvironmentObject private var thunderboltBridgeService: ThunderboltBridgeService
     @EnvironmentObject private var settingsWindowController: SettingsWindowController
+    @EnvironmentObject private var bugReportWindowController: BugReportWindowController
     @State private var focusedNode: NodeViewModel?
     @State private var deletingInstanceIDs: Set<String> = []
     @State private var showAllNodes = false
     @State private var showAllInstances = false
     @State private var baseURLCopied = false
     @State private var showAdvanced = false
-    @State private var showDebugInfo = false
-    private enum BugReportPhase: Equatable {
-        case idle
-        case prompting
-        case sending(String)
-        case success(String)
-        case failure(String)
-    }
-    @State private var bugReportPhase: BugReportPhase = .idle
-    @State private var bugReportUserDescription: String = ""
     @State private var uninstallInProgress = false
     @State private var pendingNamespace: String = ""
     @State private var pendingHFToken: String = ""
@@ -294,6 +285,13 @@ struct ContentView: View {
             ) {
                 updater.checkForUpdates()
             }
+            HoverButton(
+                title: "Share Bug Report…",
+                tint: .primary,
+                trailingSystemImage: "ladybug"
+            ) {
+                bugReportWindowController.open()
+            }
             .padding(.bottom, 8)
             HoverButton(title: "Quit", tint: .secondary) {
                 controller.stop()
@@ -477,40 +475,6 @@ struct ContentView: View {
         }
     }
 
-    private var debugSection: some View {
-        VStack(alignment: .leading, spacing: 4) {
-            HoverButton(
-                title: "Debug Info",
-                tint: .primary,
-                trailingSystemImage: showDebugInfo ? "chevron.up" : "chevron.down",
-                small: true
-            ) {
-                showDebugInfo.toggle()
-            }
-            if showDebugInfo {
-                VStack(alignment: .leading, spacing: 4) {
-                    Text("Version: \(buildTag)")
-                        .font(.caption2)
-                        .foregroundColor(.secondary)
-                    Text("Commit: \(buildCommit)")
-                        .font(.caption2)
-                        .foregroundColor(.secondary)
-                    Text(thunderboltStatusText)
-                        .font(.caption2)
-                        .foregroundColor(thunderboltStatusColor)
-                    clusterThunderboltBridgeView
-                    interfaceIpList
-                    rdmaStatusView
-                    sendBugReportButton
-                        .padding(.top, 6)
-                }
-                .padding(.leading, 8)
-                .transition(.opacity)
-            }
-        }
-        .animation(.easeInOut(duration: 0.25), value: showDebugInfo)
-    }
-
     private var rdmaStatusView: some View {
         let rdmaStatuses = stateService.latestSnapshot?.nodeRdmaCtl ?? [:]
         let localNodeId = stateService.localNodeId
@@ -559,118 +523,6 @@ struct ContentView: View {
         }
     }
 
-    private var sendBugReportButton: some View {
-        VStack(alignment: .leading, spacing: 6) {
-            switch bugReportPhase {
-            case .idle:
-                Button {
-                    bugReportPhase = .prompting
-                    bugReportUserDescription = ""
-                } label: {
-                    HStack {
-                        Text("Send Bug Report")
-                            .font(.caption)
-                            .fontWeight(.semibold)
-                        Spacer()
-                    }
-                    .padding(.vertical, 6)
-                    .padding(.horizontal, 8)
-                    .background(
-                        RoundedRectangle(cornerRadius: 6)
-                            .fill(Color.accentColor.opacity(0.12))
-                    )
-                }
-                .buttonStyle(.plain)
-
-            case .prompting:
-                VStack(alignment: .leading, spacing: 6) {
-                    Text("What's the issue? (optional)")
-                        .font(.caption2)
-                        .foregroundColor(.secondary)
-                    TextEditor(text: $bugReportUserDescription)
-                        .font(.caption2)
-                        .frame(height: 60)
-                        .overlay(
-                            RoundedRectangle(cornerRadius: 4)
-                                .stroke(Color.secondary.opacity(0.3), lineWidth: 1)
-                        )
-                    HStack(spacing: 8) {
-                        Button("Send") {
-                            Task {
-                                await sendBugReport()
-                            }
-                        }
-                        .font(.caption2)
-                        .buttonStyle(.borderedProminent)
-                        .controlSize(.small)
-                        Button("Cancel") {
-                            bugReportPhase = .idle
-                        }
-                        .font(.caption2)
-                        .buttonStyle(.bordered)
-                        .controlSize(.small)
-                    }
-                }
-                .padding(8)
-                .background(
-                    RoundedRectangle(cornerRadius: 6)
-                        .fill(Color.accentColor.opacity(0.06))
-                )
-
-            case .sending(let message):
-                HStack(spacing: 6) {
-                    ProgressView()
-                        .scaleEffect(0.6)
-                    Text(message)
-                        .font(.caption2)
-                        .foregroundColor(.secondary)
-                }
-
-            case .success(let message):
-                VStack(alignment: .leading, spacing: 6) {
-                    Text(message)
-                        .font(.caption2)
-                        .foregroundColor(.secondary)
-                        .fixedSize(horizontal: false, vertical: true)
-                    Button {
-                        openGitHubIssue()
-                    } label: {
-                        HStack(spacing: 4) {
-                            Image(systemName: "arrow.up.right.square")
-                                .imageScale(.small)
-                            Text("Create GitHub Issue")
-                                .font(.caption2)
-                        }
-                    }
-                    .buttonStyle(.bordered)
-                    .controlSize(.small)
-                    Button("Done") {
-                        bugReportPhase = .idle
-                        bugReportUserDescription = ""
-                    }
-                    .font(.caption2)
-                    .buttonStyle(.plain)
-                    .foregroundColor(.secondary)
-                }
-
-            case .failure(let message):
-                VStack(alignment: .leading, spacing: 4) {
-                    Text(message)
-                        .font(.caption2)
-                        .foregroundColor(.red)
-                        .fixedSize(horizontal: false, vertical: true)
-                    Button("Dismiss") {
-                        bugReportPhase = .idle
-                    }
-                    .font(.caption2)
-                    .buttonStyle(.plain)
-                    .foregroundColor(.secondary)
-                }
-            }
-        }
-        .animation(.easeInOut(duration: 0.2), value: bugReportPhase)
-    }
-
     private var processToggleBinding: Binding<Bool> {
         Binding(
             get: {
@@ -711,61 +563,6 @@ struct ContentView: View {
         )
     }
 
-    private func sendBugReport() async {
-        bugReportPhase = .sending("Collecting logs...")
-        let service = BugReportService()
-        let description = bugReportUserDescription.trimmingCharacters(in: .whitespacesAndNewlines)
-        do {
-            let outcome = try await service.sendReport(
-                isManual: true,
-                userDescription: description.isEmpty ? nil : description
-            )
-            if outcome.success {
-                bugReportPhase = .success(outcome.message)
-            } else {
-                bugReportPhase = .failure(outcome.message)
-            }
-        } catch {
-            bugReportPhase = .failure(error.localizedDescription)
-        }
-    }
-
-    private func openGitHubIssue() {
-        let description = bugReportUserDescription.trimmingCharacters(in: .whitespacesAndNewlines)
-
-        var bodyParts: [String] = []
-        bodyParts.append("## Describe the bug")
-        bodyParts.append("")
-        if !description.isEmpty {
-            bodyParts.append(description)
-        } else {
-            bodyParts.append("A clear and concise description of what the bug is.")
-        }
-        bodyParts.append("")
-        bodyParts.append("## Environment")
-        bodyParts.append("")
-        bodyParts.append("- macOS Version: \(ProcessInfo.processInfo.operatingSystemVersionString)")
-        bodyParts.append("- EXO Version: \(buildTag) (\(buildCommit))")
-        bodyParts.append("")
-        bodyParts.append("## Additional context")
-        bodyParts.append("")
-        bodyParts.append("A bug report with diagnostic logs was submitted via the app.")
-
-        let body = bodyParts.joined(separator: "\n")
-
-        var components = URLComponents(string: "https://github.com/exo-explore/exo/issues/new")!
-        components.queryItems = [
-            URLQueryItem(name: "template", value: "bug_report.md"),
-            URLQueryItem(name: "title", value: "[BUG] "),
-            URLQueryItem(name: "body", value: body),
-            URLQueryItem(name: "labels", value: "bug"),
-        ]
-
-        if let url = components.url {
-            NSWorkspace.shared.open(url)
-        }
-    }
-
     private func showUninstallConfirmationAlert() {
         let alert = NSAlert()
         alert.messageText = "Uninstall EXO"
@@ -848,13 +645,6 @@ struct ContentView: View {
         }
     }
 
-    private var buildTag: String {
-        Bundle.main.infoDictionary?["EXOBuildTag"] as? String ?? "unknown"
-    }
-
-    private var buildCommit: String {
-        Bundle.main.infoDictionary?["EXOBuildCommit"] as? String ?? "unknown"
-    }
 }
 
 private struct HoverButton: View {

app/EXO/EXO/EXOApp.swift

@@ -22,6 +22,7 @@ struct EXOApp: App {
     @StateObject private var updater: SparkleUpdater
     @StateObject private var thunderboltBridgeService: ThunderboltBridgeService
     @StateObject private var settingsWindowController: SettingsWindowController
+    @StateObject private var bugReportWindowController: BugReportWindowController
     private let terminationObserver: TerminationObserver
     private let firstLaunchPopout = FirstLaunchPopout()
     private let ciContext = CIContext(options: nil)
@@ -46,6 +47,7 @@ struct EXOApp: App {
         let thunderboltBridge = ThunderboltBridgeService(clusterStateService: service)
         _thunderboltBridgeService = StateObject(wrappedValue: thunderboltBridge)
         _settingsWindowController = StateObject(wrappedValue: SettingsWindowController())
+        _bugReportWindowController = StateObject(wrappedValue: BugReportWindowController())
         enableLaunchAtLoginIfNeeded()
         // Install LaunchDaemon to disable Thunderbolt Bridge on startup (prevents network loops)
         NetworkSetupHelper.promptAndInstallIfNeeded()
@@ -66,6 +68,7 @@ struct EXOApp: App {
                 .environmentObject(updater)
                 .environmentObject(thunderboltBridgeService)
                 .environmentObject(settingsWindowController)
+                .environmentObject(bugReportWindowController)
         } label: {
             menuBarIcon
                 .onReceive(controller.$isFirstLaunchReady) { ready in

app/EXO/EXO/Info.plist

@@ -9,7 +9,7 @@
 	<key>EXOBuildCommit</key>
 	<string>$(EXO_BUILD_COMMIT)</string>
 	<key>EXOBugReportPresignedUrlEndpoint</key>
-	<string>$(EXO_BUG_REPORT_PRESIGNED_URL_ENDPOINT)</string>
+	<string>https://reports.exolabs.net/presigned-urls</string>
 	<key>NSLocalNetworkUsageDescription</key>
 	<string>EXO needs local network access to discover and connect to other devices in your cluster for distributed AI inference.</string>
 	<key>NSBonjourServices</key>

app/EXO/EXO/Services/ClusterStateService.swift

@@ -17,7 +17,7 @@ final class ClusterStateService: ObservableObject {
 
     init(
         baseURL: URL = URL(string: "http://127.0.0.1:52415")!,
-        session: URLSession = .shared
+        session: URLSession = ClusterStateService.makeNonCachingSession()
     ) {
         self.baseURL = baseURL
         self.endpoint = baseURL.appendingPathComponent("state")
@@ -27,6 +27,23 @@ final class ClusterStateService: ObservableObject {
         self.decoder = decoder
     }
 
+    /// `URLSession.shared` carries an on-disk `URLCache` that persists every
+    /// response body under `~/Library/Caches/exolabs.EXO/`. We poll `/state`
+    /// at 2 Hz from `startPolling`, so leaving the shared cache attached
+    /// dirties ~500–620 KB/sec of file-backed memory and trips macOS's
+    /// per-process `disk writes` resource limit (microstackshot reports
+    /// observed on M3 Ultra producing GBs of cached responses per hour).
+    /// Cluster-state polling responses are time-sensitive and small; they
+    /// gain nothing from being cached on disk. Use an ephemeral session
+    /// with `urlCache = nil` so neither response bodies nor metadata
+    /// touch disk.
+    private static func makeNonCachingSession() -> URLSession {
+        let config = URLSessionConfiguration.ephemeral
+        config.urlCache = nil
+        config.requestCachePolicy = .reloadIgnoringLocalCacheData
+        return URLSession(configuration: config)
+    }
+
     func startPolling(interval: TimeInterval = 0.5) {
         stopPolling()
         Task {

app/EXO/EXO/Views/BugReportWindowController.swift

@@ -0,0 +1,242 @@
+import AppKit
+import SwiftUI
+
+/// Manages a standalone window for the bug-report flow.
+/// Ensures only one instance exists and brings it to front on repeated opens.
+@MainActor
+final class BugReportWindowController: ObservableObject {
+    private var window: NSWindow?
+
+    func open() {
+        if let existing = window, existing.isVisible {
+            existing.makeKeyAndOrderFront(nil)
+            NSApp.activate()
+            return
+        }
+
+        let view = BugReportView(onDismiss: { [weak self] in
+            self?.window?.close()
+        })
+
+        let hostingController = NSHostingController(rootView: view)
+        hostingController.sizingOptions = [.preferredContentSize, .minSize]
+
+        let newWindow = NSWindow(contentViewController: hostingController)
+        newWindow.styleMask = [.titled, .closable, .resizable]
+        newWindow.title = "Send a Bug Report"
+        newWindow.center()
+        newWindow.setFrameAutosaveName("ExoBugReportWindow")
+        newWindow.isReleasedWhenClosed = false
+        newWindow.makeKeyAndOrderFront(nil)
+        NSApp.activate()
+
+        window = newWindow
+    }
+}
+
+private struct BugReportView: View {
+    fileprivate enum Phase: Equatable {
+        case prompting
+        case sending(String)
+        case success(String)
+        case failure(String)
+    }
+
+    let onDismiss: () -> Void
+
+    @State private var phase: Phase = .prompting
+    @State private var userDescription: String = ""
+    @FocusState private var descriptionFocused: Bool
+
+    var body: some View {
+        VStack(alignment: .leading, spacing: 12) {
+            switch phase {
+            case .prompting:
+                promptingView
+            case .sending(let message):
+                sendingView(message: message)
+            case .success(let message):
+                successView(message: message)
+            case .failure(let message):
+                failureView(message: message)
+            }
+        }
+        .padding(16)
+        .frame(minWidth: 380)
+        .animation(.easeInOut(duration: 0.2), value: phase)
+        .onAppear { descriptionFocused = true }
+    }
+
+    private var promptingView: some View {
+        VStack(alignment: .leading, spacing: 8) {
+            Text("Description (optional)")
+                .font(.subheadline)
+                .foregroundColor(.secondary)
+            ZStack(alignment: .topLeading) {
+                if userDescription.isEmpty {
+                    Text("What were you doing when it broke?")
+                        .font(.body)
+                        .foregroundColor(Color(nsColor: .placeholderTextColor))
+                        .padding(.horizontal, 10)
+                        .padding(.vertical, 8)
+                        .allowsHitTesting(false)
+                }
+                TextEditor(text: $userDescription)
+                    .font(.body)
+                    .scrollContentBackground(.hidden)
+                    .padding(4)
+                    .frame(height: 72)
+                    .focused($descriptionFocused)
+            }
+            .background(
+                RoundedRectangle(cornerRadius: 6)
+                    .fill(Color(nsColor: .textBackgroundColor))
+            )
+            .overlay(
+                RoundedRectangle(cornerRadius: 6)
+                    .strokeBorder(Color(nsColor: .separatorColor), lineWidth: 1)
+            )
+
+            Text("Diagnostic logs will be uploaded with your report.")
+                .font(.caption)
+                .foregroundColor(.secondary)
+
+            HStack {
+                Spacer()
+                Button("Cancel") { onDismiss() }
+                    .keyboardShortcut(.cancelAction)
+                Button("Send") {
+                    Task { await send() }
+                }
+                .keyboardShortcut(.defaultAction)
+            }
+            .padding(.top, 4)
+        }
+    }
+
+    private func sendingView(message: String) -> some View {
+        VStack(alignment: .leading, spacing: 12) {
+            HStack(spacing: 10) {
+                ProgressView().controlSize(.small)
+                Text(message)
+                    .foregroundColor(.secondary)
+            }
+            HStack {
+                Spacer()
+                Button("Cancel") { onDismiss() }
+                    .keyboardShortcut(.cancelAction)
+                    .disabled(true)
+                Button("Send") {}
+                    .disabled(true)
+            }
+        }
+    }
+
+    private func successView(message: String) -> some View {
+        VStack(alignment: .leading, spacing: 12) {
+            HStack(alignment: .top, spacing: 10) {
+                Image(systemName: "checkmark.circle.fill")
+                    .foregroundColor(.green)
+                    .font(.title2)
+                Text(message)
+                    .fixedSize(horizontal: false, vertical: true)
+            }
+            HStack {
+                Button {
+                    openGitHubIssue()
+                } label: {
+                    HStack(spacing: 4) {
+                        Image(systemName: "arrow.up.right.square")
+                        Text("Open GitHub Issue")
+                    }
+                }
+                Spacer()
+                Button("Done") { onDismiss() }
+                    .keyboardShortcut(.defaultAction)
+            }
+        }
+    }
+
+    private func failureView(message: String) -> some View {
+        VStack(alignment: .leading, spacing: 12) {
+            HStack(alignment: .top, spacing: 10) {
+                Image(systemName: "exclamationmark.triangle.fill")
+                    .foregroundColor(.orange)
+                    .font(.title2)
+                Text(message)
+                    .fixedSize(horizontal: false, vertical: true)
+            }
+            HStack {
+                Spacer()
+                Button("Try Again") {
+                    phase = .prompting
+                }
+                Button("Close") { onDismiss() }
+                    .keyboardShortcut(.defaultAction)
+            }
+        }
+    }
+
+    private func send() async {
+        phase = .sending("Collecting logs and uploading…")
+        let service = BugReportService()
+        let description = userDescription.trimmingCharacters(in: .whitespacesAndNewlines)
+        do {
+            let outcome = try await service.sendReport(
+                isManual: true,
+                userDescription: description.isEmpty ? nil : description
+            )
+            if outcome.success {
+                phase = .success(outcome.message)
+            } else {
+                phase = .failure(outcome.message)
+            }
+        } catch {
+            phase = .failure(error.localizedDescription)
+        }
+    }
+
+    private func openGitHubIssue() {
+        let description = userDescription.trimmingCharacters(in: .whitespacesAndNewlines)
+
+        var bodyParts: [String] = []
+        bodyParts.append("## Describe the bug")
+        bodyParts.append("")
+        if !description.isEmpty {
+            bodyParts.append(description)
+        } else {
+            bodyParts.append("A clear and concise description of what the bug is.")
+        }
+        bodyParts.append("")
+        bodyParts.append("## Environment")
+        bodyParts.append("")
+        bodyParts.append("- macOS Version: \(ProcessInfo.processInfo.operatingSystemVersionString)")
+        bodyParts.append("- EXO Version: \(buildTag) (\(buildCommit))")
+        bodyParts.append("")
+        bodyParts.append("## Additional context")
+        bodyParts.append("")
+        bodyParts.append("A bug report with diagnostic logs was submitted via the app.")
+
+        let body = bodyParts.joined(separator: "\n")
+
+        var components = URLComponents(string: "https://github.com/exo-explore/exo/issues/new")!
+        components.queryItems = [
+            URLQueryItem(name: "template", value: "bug_report.md"),
+            URLQueryItem(name: "title", value: "[BUG] "),
+            URLQueryItem(name: "body", value: body),
+            URLQueryItem(name: "labels", value: "bug"),
+        ]
+
+        if let url = components.url {
+            NSWorkspace.shared.open(url)
+        }
+    }
+
+    private var buildTag: String {
+        Bundle.main.infoDictionary?["EXOBuildTag"] as? String ?? "unknown"
+    }
+
+    private var buildCommit: String {
+        Bundle.main.infoDictionary?["EXOBuildCommit"] as? String ?? "unknown"
+    }
+}

app/EXO/EXO/Views/SettingsView.swift

@@ -21,8 +21,6 @@ struct SettingsView: View {
     @State private var pendingReadOnlyModelsDirs: String = ""
     @State private var pendingCustomEnvironmentVariables: [CustomEnvironmentVariable] = []
     @State private var needsRestart = false
-    @State private var bugReportInFlight = false
-    @State private var bugReportMessage: String?
     @State private var uninstallInProgress = false
 
     var body: some View {
@@ -202,8 +200,6 @@ struct SettingsView: View {
                 VStack(alignment: .leading, spacing: 2) {
                     rdmaStatusView
                 }
-
-                sendBugReportButton
             }
 
             Section("Danger Zone") {
@@ -504,63 +500,30 @@ struct SettingsView: View {
         }
     }
 
-    private var sendBugReportButton: some View {
-        VStack(alignment: .leading, spacing: 4) {
-            Button {
-                Task {
-                    await sendBugReport()
-                }
-            } label: {
-                HStack {
-                    if bugReportInFlight {
-                        ProgressView()
-                            .scaleEffect(0.6)
-                    }
-                    Text("Send Bug Report")
-                        .font(.caption)
-                        .fontWeight(.semibold)
-                    Spacer()
-                }
-            }
-            .disabled(bugReportInFlight)
-
-            if let message = bugReportMessage {
-                Text(message)
-                    .font(.caption2)
-                    .foregroundColor(.secondary)
-                    .fixedSize(horizontal: false, vertical: true)
-            }
-        }
-    }
-
     // MARK: - Actions
 
-    private func sendBugReport() async {
-        bugReportInFlight = true
-        bugReportMessage = "Collecting logs..."
-        let service = BugReportService()
-        do {
-            let outcome = try await service.sendReport(isManual: true)
-            bugReportMessage = outcome.message
-        } catch {
-            bugReportMessage = error.localizedDescription
-        }
-        bugReportInFlight = false
-    }
-
     private func showUninstallConfirmationAlert() {
         let alert = NSAlert()
         alert.messageText = "Uninstall EXO"
         alert.informativeText = """
-            This will remove EXO and all its system components:
+            This will remove EXO and all its components:
 
             • Network configuration daemon
             • Launch at login registration
             • EXO network location
+            • EXO data directory (~/.exo)
 
             The app will be moved to Trash.
             """
         alert.alertStyle = .warning
+
+        let checkbox = NSButton(
+            checkboxWithTitle: "Keep downloaded models (~/.exo/models)",
+            target: nil, action: nil)
+        checkbox.state = .off
+        checkbox.sizeToFit()
+        alert.accessoryView = checkbox
+
         alert.addButton(withTitle: "Uninstall")
         alert.addButton(withTitle: "Cancel")
 
@@ -570,11 +533,11 @@ struct SettingsView: View {
 
         let response = alert.runModal()
         if response == .alertFirstButtonReturn {
-            performUninstall()
+            performUninstall(keepModels: checkbox.state == .on)
         }
     }
 
-    private func performUninstall() {
+    private func performUninstall(keepModels: Bool) {
         uninstallInProgress = true
 
         controller.cancelPendingLaunch()
@@ -584,6 +547,7 @@ struct SettingsView: View {
         DispatchQueue.global(qos: .utility).async {
             do {
                 try NetworkSetupHelper.uninstall()
+                try Self.removeExoDirectory(keepModels: keepModels)
 
                 DispatchQueue.main.async {
                     LaunchAtLoginHelper.disable()
@@ -607,6 +571,23 @@ struct SettingsView: View {
         }
     }
 
+    private static func removeExoDirectory(keepModels: Bool) throws {
+        let fm = FileManager.default
+        let exoDir = ExoProcessController.exoDirectoryURL
+        guard fm.fileExists(atPath: exoDir.path) else { return }
+
+        if !keepModels {
+            try fm.removeItem(at: exoDir)
+            return
+        }
+
+        let contents = try fm.contentsOfDirectory(
+            at: exoDir, includingPropertiesForKeys: nil, options: [])
+        for entry in contents where entry.lastPathComponent != "models" {
+            try? fm.removeItem(at: entry)
+        }
+    }
+
     private func moveAppToTrash() {
         guard let appURL = Bundle.main.bundleURL as URL? else { return }
         do {

app/EXO/uninstall-exo.sh

@@ -3,25 +3,55 @@
 # EXO Uninstaller Script
 #
 # This script removes all EXO system components that persist after deleting the app.
-# Run with: sudo ./uninstall-exo.sh
+# Run with: sudo ./uninstall-exo.sh [--keep-models]
+#
+# Options:
+#   --keep-models   Preserve ~/.exo/models when removing the EXO data directory.
 #
 # Components removed:
 # - LaunchDaemon: /Library/LaunchDaemons/io.exo.networksetup.plist
 # - Network script: /Library/Application Support/EXO/
 # - Log files: /var/log/io.exo.networksetup.*
 # - Network location: "exo"
+# - EXO data directory: ~/.exo (or all of ~/.exo except models/ when --keep-models is set)
 # - Launch at login registration
 #
 
 set -euo pipefail
 
+KEEP_MODELS=0
+for arg in "$@"; do
+  case "$arg" in
+  --keep-models)
+    KEEP_MODELS=1
+    ;;
+  -h | --help)
+    echo "Usage: sudo ./uninstall-exo.sh [--keep-models]"
+    echo "  --keep-models   Preserve ~/.exo/models when removing the EXO data directory."
+    exit 0
+    ;;
+  *)
+    echo "Unknown argument: $arg" >&2
+    echo "Usage: sudo ./uninstall-exo.sh [--keep-models]" >&2
+    exit 2
+    ;;
+  esac
+done
+
 LABEL="io.exo.networksetup"
-SCRIPT_DEST="/Library/Application Support/EXO/disable_bridge_enable_dhcp.sh"
+# Current script path. Older installs used a different filename; keep the
+# legacy path here so a fresh uninstall still cleans up upgraded machines.
+CURRENT_SCRIPT_DEST="/Library/Application Support/EXO/disable_bridge.sh"
+LEGACY_SCRIPT_DEST="/Library/Application Support/EXO/disable_bridge_enable_dhcp.sh"
 PLIST_DEST="/Library/LaunchDaemons/io.exo.networksetup.plist"
 LOG_OUT="/var/log/${LABEL}.log"
 LOG_ERR="/var/log/${LABEL}.err.log"
 APP_BUNDLE_ID="io.exo.EXO"
 
+# Resolve the invoking user's home, even when run via sudo.
+USER_HOME="$(eval echo "~${SUDO_USER:-$USER}")"
+EXO_DIR="$USER_HOME/.exo"
+
 # Colors for output
 RED='\033[0;31m'
 GREEN='\033[0;32m'
@@ -69,11 +99,17 @@ else
   echo_warn "LaunchDaemon plist not found (already removed?)"
 fi
 
-# Remove the script and parent directory
-if [[ -f $SCRIPT_DEST ]]; then
-  rm -f "$SCRIPT_DEST"
-  echo_info "Removed network setup script"
-else
+# Remove the script (current and legacy filenames) — backwards-compatible:
+# tolerate either, both, or neither being present.
+removed_any_script=0
+for script in "$CURRENT_SCRIPT_DEST" "$LEGACY_SCRIPT_DEST"; do
+  if [[ -f $script ]]; then
+    rm -f "$script"
+    echo_info "Removed network setup script: $script"
+    removed_any_script=1
+  fi
+done
+if [[ $removed_any_script -eq 0 ]]; then
   echo_warn "Network setup script not found (already removed?)"
 fi
 
@@ -115,6 +151,22 @@ if networksetup -listnetworkservices 2>/dev/null | grep -q "Thunderbolt Bridge";
   echo_info "Re-enabled Thunderbolt Bridge"
 fi
 
+# Remove EXO data directory (~/.exo)
+EXO_DIR_REMOVED=""
+if [[ -d $EXO_DIR ]]; then
+  if [[ $KEEP_MODELS == "1" && -d "$EXO_DIR/models" ]]; then
+    find "$EXO_DIR" -mindepth 1 -maxdepth 1 ! -name models -exec rm -rf {} +
+    EXO_DIR_REMOVED="kept_models"
+    echo_info "Removed ~/.exo (preserved models/)"
+  else
+    rm -rf "$EXO_DIR"
+    EXO_DIR_REMOVED="full"
+    echo_info "Removed ~/.exo"
+  fi
+else
+  echo_warn "~/.exo not found (already removed?)"
+fi
+
 # Note about launch at login registration
 # SMAppService-based login items cannot be removed from a shell script.
 # They can only be unregistered from within the app itself or manually via System Settings.
@@ -144,6 +196,10 @@ echo "  • Network setup LaunchDaemon"
 echo "  • Network configuration script"
 echo "  • Log files"
 echo "  • 'exo' network location"
+case "$EXO_DIR_REMOVED" in
+full) echo "  • EXO data directory (~/.exo)" ;;
+kept_models) echo "  • EXO data directory (~/.exo, models preserved)" ;;
+esac
 echo ""
 echo "Your network has been restored to use the 'Automatic' location."
 echo "Thunderbolt Bridge has been re-enabled (if present)."

bench/eval_configs/models.toml

@@ -7,7 +7,7 @@
 #   name, patterns, reasoning
 #
 # Optional per-model overrides (CLI flags take priority over these):
-#   temperature, top_p, max_tokens, reasoning_effort
+#   temperature, top_p, max_tokens, reasoning_effort, enable_thinking
 #
 # Fallback defaults (when no per-model config):
 #   reasoning:     temperature=1.0, max_tokens=131072, reasoning_effort="high"
@@ -18,10 +18,9 @@
 
 # ─── Qwen3.5 (Feb 2026) ─────────────────────────────────────────────
 # Source: HuggingFace model cards (Qwen/Qwen3.5-*)
-# 35B-A3B thinking general: temp=1.0, top_p=0.95, top_k=20
-# 397B thinking: temp=0.6, top_p=0.95, top_k=20
-# Non-thinking: temp=0.7, top_p=0.8, top_k=20
-# max_tokens: 32768 general, 81920 for complex math/code
+# Model card recommends: temp=0.6, top_p=0.95, top_k=20
+# We omit top_k to match vllm eval (which doesn't set it).
+# max_tokens=121072 to match vllm eval (131072 context - 10000 safety margin).
 
 [[model]]
 name = "Qwen3.5 2B"
@@ -29,7 +28,8 @@ patterns = ["Qwen3.5-2B"]
 reasoning = true
 temperature = 0.6
 top_p = 0.95
-max_tokens = 81920
+enable_thinking = true
+max_tokens = 121072
 
 [[model]]
 name = "Qwen3.5 9B"
@@ -37,7 +37,8 @@ patterns = ["Qwen3.5-9B"]
 reasoning = true
 temperature = 0.6
 top_p = 0.95
-max_tokens = 81920
+enable_thinking = true
+max_tokens = 121072
 
 [[model]]
 name = "Qwen3.5 27B"
@@ -45,15 +46,17 @@ patterns = ["Qwen3.5-27B"]
 reasoning = true
 temperature = 0.6
 top_p = 0.95
-max_tokens = 81920
+enable_thinking = true
+max_tokens = 121072
 
 [[model]]
 name = "Qwen3.5 35B A3B"
 patterns = ["Qwen3.5-35B-A3B"]
 reasoning = true
-temperature = 1.0
+temperature = 0.6
 top_p = 0.95
-max_tokens = 81920
+enable_thinking = true
+max_tokens = 121072
 
 [[model]]
 name = "Qwen3.5 122B A10B"
@@ -61,7 +64,8 @@ patterns = ["Qwen3.5-122B-A10B"]
 reasoning = true
 temperature = 0.6
 top_p = 0.95
-max_tokens = 81920
+enable_thinking = true
+max_tokens = 121072
 
 [[model]]
 name = "Qwen3.5 397B A17B"
@@ -69,12 +73,14 @@ patterns = ["Qwen3.5-397B-A17B"]
 reasoning = true
 temperature = 0.6
 top_p = 0.95
-max_tokens = 81920
+enable_thinking = true
+max_tokens = 121072
 
 # ─── Qwen3 (Apr 2025) ───────────────────────────────────────────────
 # Source: HuggingFace model cards (Qwen/Qwen3-*)
-# Thinking: temp=0.6, top_p=0.95, top_k=20
-# Non-thinking: temp=0.7, top_p=0.8, top_k=20
+# Model card recommends: temp=0.6, top_p=0.95, top_k=20
+# We omit top_k to match vllm eval (which doesn't set it).
+# Non-thinking: temp=0.7, top_p=0.8
 # max_tokens: 32768 general, 38912 for complex math/code
 
 [[model]]
@@ -83,6 +89,7 @@ patterns = ["Qwen3-0.6B"]
 reasoning = true
 temperature = 0.6
 top_p = 0.95
+enable_thinking = true
 max_tokens = 38912
 
 [[model]]
@@ -91,6 +98,7 @@ patterns = ["Qwen3-30B-A3B"]
 reasoning = true
 temperature = 0.6
 top_p = 0.95
+enable_thinking = true
 max_tokens = 38912
 
 [[model]]
@@ -99,6 +107,7 @@ patterns = ["Qwen3-235B-A22B"]
 reasoning = true
 temperature = 0.6
 top_p = 0.95
+enable_thinking = true
 max_tokens = 38912
 
 [[model]]
@@ -107,6 +116,7 @@ patterns = ["Qwen3-Next-80B-A3B-Thinking"]
 reasoning = true
 temperature = 0.6
 top_p = 0.95
+enable_thinking = true
 max_tokens = 38912
 
 [[model]]
@@ -129,9 +139,9 @@ max_tokens = 16384
 name = "Qwen3 Coder Next"
 patterns = ["Qwen3-Coder-Next"]
 reasoning = false
-temperature = 0.7
-top_p = 0.8
-max_tokens = 16384
+temperature = 1.0
+top_p = 0.95
+max_tokens = 121072
 
 # ─── GPT-OSS (OpenAI) ───────────────────────────────────────────────
 # Source: OpenAI GitHub README + HuggingFace discussion #21
@@ -165,10 +175,38 @@ patterns = ["DeepSeek-V3.1"]
 reasoning = true
 temperature = 0.0
 
+[[model]]
+name = "DeepSeek V3.2"
+patterns = ["DeepSeek-V3.2"]
+reasoning = true
+temperature = 1.0
+top_p = 0.95
+enable_thinking = true
+
+# ─── NVIDIA Nemotron ───────────────────────────────────────────────────
+# Source: HuggingFace model cards
+# All variants: temp=1.0, top_p=0.95, enable_thinking=true
+
+[[model]]
+name = "Nemotron Cascade 2 30B A3B"
+patterns = ["Nemotron-Cascade-2-30B-A3B"]
+reasoning = true
+temperature = 1.0
+top_p = 0.95
+enable_thinking = true
+
+[[model]]
+name = "Nemotron 3 Super 120B A12B"
+patterns = ["Nemotron-3-Super-120B-A12B", "NVIDIA-Nemotron-3-Super-120B-A12B"]
+reasoning = true
+temperature = 1.0
+top_p = 0.95
+enable_thinking = true
+
 # ─── GLM (ZhipuAI / THUDM) ──────────────────────────────────────────
 # Source: HuggingFace model cards + generation_config.json + docs.z.ai
 # GLM 4.5+: temp=1.0, top_p=0.95
-# Reasoning tasks: 131072 max_tokens; coding/SWE tasks: temp=0.7
+# max_tokens=121072 to match vllm eval (131072 context - 10000 safety margin)
 
 [[model]]
 name = "GLM-5"
@@ -176,7 +214,8 @@ patterns = ["GLM-5"]
 reasoning = true
 temperature = 1.0
 top_p = 0.95
-max_tokens = 131072
+enable_thinking = true
+max_tokens = 121072
 
 [[model]]
 name = "GLM 4.5 Air"
@@ -191,7 +230,8 @@ patterns = ["GLM-4.7-"]
 reasoning = true
 temperature = 1.0
 top_p = 0.95
-max_tokens = 131072
+enable_thinking = true
+max_tokens = 121072
 # Note: matches both GLM-4.7 and GLM-4.7-Flash
 
 # ─── Kimi (Moonshot AI) ─────────────────────────────────────────────
@@ -213,7 +253,8 @@ patterns = ["Kimi-K2.5"]
 reasoning = true
 temperature = 1.0
 top_p = 0.95
-max_tokens = 131072
+enable_thinking = true
+max_tokens = 121072
 
 [[model]]
 name = "Kimi K2 Instruct"
@@ -223,7 +264,17 @@ temperature = 0.6
 
 # ─── MiniMax ─────────────────────────────────────────────────────────
 # Source: HuggingFace model cards + generation_config.json
-# All models: temp=1.0, top_p=0.95, top_k=40
+# All models: temp=1.0, top_p=0.95
+# max_tokens=90000 to match vllm eval (100000 context - 10000 safety margin)
+
+[[model]]
+name = "MiniMax M2.7"
+patterns = ["MiniMax-M2.7"]
+reasoning = true
+temperature = 1.0
+top_p = 0.95
+enable_thinking = true
+max_tokens = 90000
 
 [[model]]
 name = "MiniMax M2.5"
@@ -231,6 +282,8 @@ patterns = ["MiniMax-M2.5"]
 reasoning = true
 temperature = 1.0
 top_p = 0.95
+enable_thinking = true
+max_tokens = 90000
 
 [[model]]
 name = "MiniMax M2.1"
@@ -251,6 +304,8 @@ patterns = ["Step-3.5-Flash"]
 reasoning = true
 temperature = 1.0
 top_p = 0.95
+enable_thinking = true
+max_tokens = 121072
 
 # ─── Llama (Meta) ───────────────────────────────────────────────────
 # Source: generation_config.json + meta-llama/llama-models generation.py

bench/eval_tool_calls.py

@@ -3,11 +3,13 @@ from __future__ import annotations
 
 import argparse
 import contextlib
+import io
 import json
 import os
 import sys
 import time
 import tomllib
+from concurrent.futures import ThreadPoolExecutor, as_completed
 from dataclasses import dataclass, field
 from pathlib import Path
 from typing import Any, Literal
@@ -209,7 +211,7 @@ def _openai_build_request(
         "model": model,
         "messages": messages,
         "tools": tools,
-        "max_tokens": 16384,
+        "max_tokens": 4096,
         "temperature": 0.0,
     }
     return "/v1/chat/completions", body
@@ -276,7 +278,7 @@ def _openai_build_followup(
         "model": model,
         "messages": followup_messages,
         "tools": tools,
-        "max_tokens": 16384,
+        "max_tokens": 4096,
         "temperature": 0.0,
     }
     return "/v1/chat/completions", body
@@ -379,7 +381,7 @@ def _claude_build_request(
         "model": model,
         "messages": claude_messages,
         "tools": claude_tools,
-        "max_tokens": 16384,
+        "max_tokens": 4096,
         "temperature": 0.0,
     }
     if system_content is not None:
@@ -489,7 +491,7 @@ def _claude_build_followup(
         "model": model,
         "messages": claude_messages,
         "tools": claude_tools,
-        "max_tokens": 16384,
+        "max_tokens": 4096,
         "temperature": 0.0,
     }
     if system_content is not None:
@@ -913,6 +915,12 @@ Examples:
         default=1,
         help="Repeat each scenario N times (default: 1)",
     )
+    parser.add_argument(
+        "--concurrency",
+        type=int,
+        default=1,
+        help="Run up to N scenarios in parallel against the same instance (default: 1)",
+    )
     parser.add_argument(
         "--scenarios",
         nargs="*",
@@ -935,6 +943,13 @@ Examples:
     )
     args = parser.parse_args()
 
+    if args.concurrency < 1:
+        print(
+            f"--concurrency must be >= 1 (got {args.concurrency})",
+            file=sys.stderr,
+        )
+        sys.exit(2)
+
     all_scenarios = load_scenarios(SCENARIOS_PATH)
     if args.scenarios:
         scenarios = [s for s in all_scenarios if s.name in args.scenarios]
@@ -1010,42 +1025,72 @@ Examples:
     cluster_snapshot = capture_cluster_snapshot(exo)
     all_results: list[ScenarioResult] = []
 
+    tasks: list[tuple[int, Scenario, ApiName]] = [
+        (run_idx, scenario, api_name)
+        for run_idx in range(args.repeat)
+        for scenario in scenarios
+        for api_name in api_names
+    ]
+
+    def _run_one(
+        http_client: httpx.Client,
+        task: tuple[int, Scenario, ApiName],
+    ) -> tuple[tuple[int, Scenario, ApiName], list[ScenarioResult], str]:
+        run_idx, scenario, api_name = task
+        buf = io.StringIO()
+        run_tag = f"[run {run_idx + 1}/{args.repeat}]" if args.repeat > 1 else ""
+        print(
+            f"\n  {run_tag}[{api_name:>9}] {scenario.name}: {scenario.description}",
+            file=buf,
+        )
+        scenario_results = run_scenario(
+            http_client,
+            args.host,
+            args.port,
+            full_model_id,
+            scenario,
+            api_name,
+            args.timeout,
+            args.verbose,
+        )
+        for r in scenario_results:
+            status = "PASS" if r.passed else "FAIL"
+            print(
+                f"    [{r.phase:>10}] {status}  ({r.latency_ms:.0f}ms)",
+                file=buf,
+            )
+            for check_name, check_ok in r.checks.items():
+                mark = "+" if check_ok else "-"
+                print(f"      {mark} {check_name}", file=buf)
+            if r.error:
+                print(f"      ! {r.error}", file=buf)
+        return task, scenario_results, buf.getvalue()
+
     try:
         with httpx.Client() as http_client:
-            for run_idx in range(args.repeat):
-                if args.repeat > 1:
-                    print(f"\n--- Run {run_idx + 1}/{args.repeat} ---", file=log)
-
-                for scenario in scenarios:
-                    for api_name in api_names:
-                        print(
-                            f"\n  [{api_name:>9}] {scenario.name}: {scenario.description}",
-                            file=log,
-                        )
-
-                        scenario_results = run_scenario(
-                            http_client,
-                            args.host,
-                            args.port,
-                            full_model_id,
-                            scenario,
-                            api_name,
-                            args.timeout,
-                            args.verbose,
-                        )
+            if args.concurrency == 1:
+                current_run = -1
+                for task in tasks:
+                    run_idx = task[0]
+                    if args.repeat > 1 and run_idx != current_run:
+                        print(f"\n--- Run {run_idx + 1}/{args.repeat} ---", file=log)
+                        current_run = run_idx
+                    _, scenario_results, buffered = _run_one(http_client, task)
+                    all_results.extend(scenario_results)
+                    log.write(buffered)
+                    log.flush()
+            else:
+                print(
+                    f"Running {len(tasks)} tasks with concurrency={args.concurrency}",
+                    file=log,
+                )
+                with ThreadPoolExecutor(max_workers=args.concurrency) as pool:
+                    futures = [pool.submit(_run_one, http_client, t) for t in tasks]
+                    for fut in as_completed(futures):
+                        _, scenario_results, buffered = fut.result()
                         all_results.extend(scenario_results)
-
-                        for r in scenario_results:
-                            status = "PASS" if r.passed else "FAIL"
-                            print(
-                                f"    [{r.phase:>10}] {status}  ({r.latency_ms:.0f}ms)",
-                                file=log,
-                            )
-                            for check_name, check_ok in r.checks.items():
-                                mark = "+" if check_ok else "-"
-                                print(f"      {mark} {check_name}", file=log)
-                            if r.error:
-                                print(f"      ! {r.error}", file=log)
+                        log.write(buffered)
+                        log.flush()
     finally:
         try:
             exo.request_json("DELETE", f"/instance/{instance_id}")

bench/exo_bench.py

@@ -35,6 +35,7 @@ from harness import (
     ExoHttpError,
     add_common_instance_args,
     capture_cluster_snapshot,
+    find_existing_instance,
     instance_id_from_instance,
     node_ids_from_instance,
     nodes_used_in_instance,
@@ -79,7 +80,7 @@ def load_tokenizer_for_bench(model_id: str) -> Any:
         model_path = Path(
             snapshot_download(
                 model_id,
-                allow_patterns=["*.json", "*.py", "*.tiktoken", "*.model"],
+                allow_patterns=["*.json", "*.py", "*.tiktoken", "*.model", "*.jinja"],
             )
         )
 
@@ -122,8 +123,48 @@ def load_tokenizer_for_bench(model_id: str) -> Any:
 
         return hf_tokenizer
 
-    # Default: use AutoTokenizer
-    return AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
+    # TODO: Change back to using only transformers
+    try:
+        return AutoTokenizer.from_pretrained(model_id, trust_remote_code=True)
+    except (AttributeError, ValueError):
+        from huggingface_hub import snapshot_download
+        from transformers import PretrainedConfig
+
+        model_path = Path(
+            snapshot_download(
+                model_id,
+                allow_patterns=[
+                    "*.json",
+                    "*.py",
+                    "tokenizer.model",
+                    "*.tiktoken",
+                    "tiktoken.model",
+                    "*.txt",
+                    "*.jsonl",
+                    "*.jinja",
+                ],
+            )
+        )
+        stub_kwargs: dict[str, Any] = {}
+        config_file = model_path / "config.json"
+        if config_file.exists():
+            with open(config_file) as f:
+                raw = json.load(f)
+            for key in (
+                "model_type",
+                "max_position_embeddings",
+                "vocab_size",
+                "bos_token_id",
+                "eos_token_id",
+                "pad_token_id",
+            ):
+                if key in raw:
+                    stub_kwargs[key] = raw[key]
+        return AutoTokenizer.from_pretrained(
+            str(model_path),
+            config=PretrainedConfig(**stub_kwargs),
+            trust_remote_code=True,
+        )
 
 
 def format_peak_memory(b: float) -> str:
@@ -237,28 +278,76 @@ def run_one_completion(
     prompt_sizer: PromptSizer,
     *,
     use_prefix_cache: bool = False,
+    stream: bool = False,
 ) -> tuple[dict[str, Any], int]:
     content, pp_tokens = prompt_sizer.build(pp_hint)
     payload: dict[str, Any] = {
         "model": model_id,
         "messages": [{"role": "user", "content": content}],
-        "stream": False,
         "max_tokens": tg,
         "logprobs": False,
         "use_prefix_cache": use_prefix_cache,
+        # Argmax sampling for deterministic, faster decode (matches
+        # mlx_lm.benchmark default). Avoids per-token softmax + categorical
+        # sample over the full vocab.
+        "temperature": 0.0,
     }
 
-    t0 = time.perf_counter()
-    out = client.post_bench_chat_completions(payload)
-    elapsed = time.perf_counter() - t0
+    if not stream:
+        payload["stream"] = False
+        t0 = time.perf_counter()
+        out = client.post_bench_chat_completions(payload)
+        elapsed = time.perf_counter() - t0
 
-    stats = out.get("generation_stats")
+        stats = out.get("generation_stats")
+        choices = out.get("choices") or [{}]
+        message = choices[0].get("message", {}) if choices else {}
+        content = message.get("content") or ""
+        preview = content[:200] if content else ""
+    else:
+        tokens = 0
+        first_token_time = None
+        t0 = time.perf_counter()
+        text_parts: list[str] = []
+        stats = None
 
-    # Extract preview, handling None content (common for thinking models)
-    choices = out.get("choices") or [{}]
-    message = choices[0].get("message", {}) if choices else {}
-    content = message.get("content") or ""
-    preview = content[:200] if content else ""
+        for raw_line in client.stream_bench_chat_completions(payload):
+            line = raw_line.strip()
+            if line.startswith(": generation_stats "):
+                with contextlib.suppress(json.JSONDecodeError):
+                    stats = json.loads(line[len(": generation_stats ") :])
+                continue
+            if not line.startswith("data: "):
+                continue
+            data = line[6:]
+            if data == "[DONE]":
+                break
+            try:
+                chunk = json.loads(data)
+                delta = chunk.get("choices", [{}])[0].get("delta", {})
+                if delta.get("content"):
+                    if first_token_time is None:
+                        first_token_time = time.perf_counter()
+                    tokens += 1
+                    text_parts.append(delta["content"])
+            except json.JSONDecodeError:
+                pass
+
+        elapsed = time.perf_counter() - t0
+        preview = "".join(text_parts)[:200]
+
+        if not stats:
+            ttft = (first_token_time - t0) if first_token_time else elapsed
+            gen_time = elapsed - ttft if tokens > 1 else elapsed
+            gen_tps = (tokens - 1) / gen_time if tokens > 1 and gen_time > 0 else 0.0
+            prompt_tps = pp_tokens / ttft if ttft > 0 else 0.0
+            stats = {
+                "prompt_tokens": pp_tokens,
+                "generation_tokens": tokens,
+                "prompt_tps": round(prompt_tps, 2),
+                "generation_tps": round(gen_tps, 2),
+                "peak_memory_usage": {"inBytes": 0},
+            }
 
     return {
         "elapsed_s": elapsed,
@@ -278,9 +367,19 @@ class PromptSizer:
     def _make_counter(tokenizer: Any) -> Callable[[str], int]:
         def count_fn(user_content: str) -> int:
             messages = [{"role": "user", "content": user_content}]
-            ids = tokenizer.apply_chat_template(
-                messages, tokenize=True, add_generation_prompt=True
-            )
+            try:
+                ids = tokenizer.apply_chat_template(
+                    messages, tokenize=True, add_generation_prompt=True
+                )
+            except ValueError:
+                # Models without a Jinja chat template (e.g. DeepSeek V4 which
+                # ships its own Python encoder). Use the exo-side V4 encoder.
+                from exo.worker.engines.mlx.deepseek_v4_encoding import (
+                    encode_messages as encode_v4,
+                )
+
+                prompt = encode_v4(messages, thinking_mode="thinking")
+                ids = tokenizer.encode(prompt, add_special_tokens=False)
             # Fix for transformers 5.x
             if hasattr(ids, "input_ids"):
                 ids = ids.input_ids
@@ -375,6 +474,11 @@ def main() -> int:
         action="store_true",
         help="Force all pp×tg combinations (cartesian product) even when lists have equal length.",
     )
+    ap.add_argument(
+        "--stream",
+        action="store_true",
+        help="Use /bench/chat/completions with streaming SSE response (bench=True still applies: no EOS detection, no KV cache).",
+    )
     ap.add_argument(
         "--no-system-metrics",
         action="store_true",
@@ -440,81 +544,124 @@ def main() -> int:
         logger.error("[exo-bench] tokenizer usable but prompt sizing failed")
         raise
 
-    selected = settle_and_fetch_placements(
-        client, full_model_id, args, settle_timeout=args.settle_timeout
-    )
+    # Optionally reuse a running instance for this model
+    reused_instance_id: str | None = None
+    if args.reuse_instance:
+        existing = find_existing_instance(client, full_model_id)
+        if existing:
+            reused_instance_id = existing
+            logger.info(f"Reusing existing instance {reused_instance_id}")
+        else:
+            logger.warning(
+                "--reuse-instance: no existing instance found, creating a new one"
+            )
 
-    if not selected:
-        logger.error("No valid placements matched your filters.")
-        return 1
-
-    selected.sort(
-        key=lambda p: (
-            str(p.get("instance_meta", "")),
-            str(p.get("sharding", "")),
-            -nodes_used_in_instance(p["instance"]),
-        ),
-        reverse=True,
-    )
-
-    logger.debug(f"exo-bench model: short_id={short_id} full_id={full_model_id}")
-    logger.info(f"placements: {len(selected)}")
-    for p in selected:
-        logger.info(
-            f"  - {p['sharding']} / {p['instance_meta']} / nodes={nodes_used_in_instance(p['instance'])}"
+    if reused_instance_id is not None:
+        # Use the existing instance directly — skip placement iteration
+        selected = []
+        download_duration_s = None
+    else:
+        selected = settle_and_fetch_placements(
+            client, full_model_id, args, settle_timeout=args.settle_timeout
         )
 
-    if args.dry_run:
-        return 0
+        if not selected:
+            logger.error("No valid placements matched your filters.")
+            return 1
 
-    settle_deadline = (
-        time.monotonic() + args.settle_timeout if args.settle_timeout > 0 else None
-    )
+        selected.sort(
+            key=lambda p: (
+                str(p.get("instance_meta", "")),
+                str(p.get("sharding", "")),
+                nodes_used_in_instance(p["instance"]),
+            ),
+            reverse=True,
+        )
 
-    logger.info("Planning phase: checking downloads...")
-    download_duration_s = run_planning_phase(
-        client,
-        full_model_id,
-        selected[0],
-        args.danger_delete_downloads,
-        args.timeout,
-        settle_deadline,
-    )
-    if download_duration_s is not None:
-        logger.info(f"Download: {download_duration_s:.1f}s (freshly downloaded)")
-    else:
-        logger.info("Download: model already cached")
+        logger.debug(f"exo-bench model: short_id={short_id} full_id={full_model_id}")
+        logger.info(f"placements: {len(selected)}")
+        for p in selected:
+            logger.info(
+                f"  - {p['sharding']} / {p['instance_meta']} / nodes={nodes_used_in_instance(p['instance'])}"
+            )
+
+        if args.dry_run:
+            return 0
+
+        settle_deadline = (
+            time.monotonic() + args.settle_timeout if args.settle_timeout > 0 else None
+        )
+
+        logger.info("Planning phase: checking downloads...")
+        download_duration_s = run_planning_phase(
+            client,
+            full_model_id,
+            selected[0],
+            args.danger_delete_downloads,
+            args.timeout,
+            settle_deadline,
+        )
+        if download_duration_s is not None:
+            logger.info(f"Download: {download_duration_s:.1f}s (freshly downloaded)")
+        else:
+            logger.info("Download: model already cached")
 
     cluster_snapshot = capture_cluster_snapshot(client)
     all_rows: list[dict[str, Any]] = []
     all_system_metrics: dict[str, dict[str, dict[str, float]]] = {}
 
+    # If reusing an existing instance, run a single benchmark pass against it
+    if reused_instance_id is not None:
+        selected = [None]
+
     for preview in selected:
-        instance = preview["instance"]
-        instance_id = instance_id_from_instance(instance)
+        created_instance = False
+        if preview is not None:
+            instance = preview["instance"]
+            instance_id = instance_id_from_instance(instance)
 
-        sharding = str(preview["sharding"])
-        instance_meta = str(preview["instance_meta"])
-        n_nodes = nodes_used_in_instance(instance)
+            sharding = str(preview["sharding"])
+            instance_meta = str(preview["instance_meta"])
+            n_nodes = nodes_used_in_instance(instance)
 
-        logger.info("=" * 80)
-        logger.info(
-            f"PLACEMENT: {sharding} / {instance_meta} / nodes={n_nodes} / instance_id={instance_id}"
-        )
+            logger.info("=" * 80)
+            logger.info(
+                f"PLACEMENT: {sharding} / {instance_meta} / nodes={n_nodes} / instance_id={instance_id}"
+            )
 
-        client.request_json("POST", "/instance", body={"instance": instance})
-        try:
-            wait_for_instance_ready(client, instance_id)
-        except (RuntimeError, TimeoutError) as e:
-            logger.error(f"Failed to initialize placement: {e}")
-            with contextlib.suppress(ExoHttpError):
-                client.request_json("DELETE", f"/instance/{instance_id}")
-            continue
+            # Delete any existing instances to free resources before placing
+            try:
+                state = client.request_json("GET", "/state")
+                for old_id in list(state.get("instances", {}).keys()):
+                    logger.info(f"Deleting stale instance {old_id}")
+                    with contextlib.suppress(ExoHttpError):
+                        client.request_json("DELETE", f"/instance/{old_id}")
+                if state.get("instances"):
+                    time.sleep(2)
+            except Exception as e:
+                logger.warning(f"Failed to clean up stale instances: {e}")
 
-        time.sleep(1)
+            client.request_json("POST", "/instance", body={"instance": instance})
+            try:
+                wait_for_instance_ready(client, instance_id)
+            except (RuntimeError, TimeoutError) as e:
+                logger.error(f"Failed to initialize placement: {e}")
+                with contextlib.suppress(ExoHttpError):
+                    client.request_json("DELETE", f"/instance/{instance_id}")
+                continue
+
+            time.sleep(1)
+            created_instance = True
+        else:
+            instance_id = reused_instance_id
+            sharding = "reused"
+            instance_meta = "reused"
+            n_nodes = 0
+            logger.info("=" * 80)
+            logger.info(f"Using existing instance {instance_id}")
 
         sampler: SystemMetricsSampler | None = None
-        if not args.no_system_metrics:
+        if not args.no_system_metrics and preview is not None:
             nids = node_ids_from_instance(instance)
             sampler = SystemMetricsSampler(
                 ExoClient(args.host, args.port, timeout_s=30),
@@ -523,16 +670,20 @@ def main() -> int:
             )
             sampler.start()
 
+        def _do_one(c: ExoClient, pp: int, tg: int) -> tuple[dict[str, Any], int]:
+            return run_one_completion(
+                c,
+                full_model_id,
+                pp,
+                tg,
+                prompt_sizer,
+                use_prefix_cache=args.use_prefix_cache,
+                stream=args.stream,
+            )
+
         try:
             for i in range(args.warmup):
-                run_one_completion(
-                    client,
-                    full_model_id,
-                    pp_list[0],
-                    tg_list[0],
-                    prompt_sizer,
-                    use_prefix_cache=args.use_prefix_cache,
-                )
+                _do_one(client, pp_list[0], tg_list[0])
                 logger.debug(f"  warmup {i + 1}/{args.warmup} done")
 
             # If pp and tg lists have same length, run in tandem (zip)
@@ -554,14 +705,7 @@ def main() -> int:
                             # Sequential: single request
                             try:
                                 inf_t0 = time.monotonic()
-                                row, actual_pp_tokens = run_one_completion(
-                                    client,
-                                    full_model_id,
-                                    pp,
-                                    tg,
-                                    prompt_sizer,
-                                    use_prefix_cache=args.use_prefix_cache,
-                                )
+                                row, actual_pp_tokens = _do_one(client, pp, tg)
                                 inference_windows.append((inf_t0, time.monotonic()))
                             except Exception as e:
                                 logger.error(e)
@@ -587,6 +731,15 @@ def main() -> int:
                             )
                             runs.append(row)
                             all_rows.append(row)
+                            # Per-repeat trial log so individual numbers are visible
+                            # alongside the final averaged summary. Useful for
+                            # spotting outliers and trial-to-trial variance.
+                            _s = row.get("stats") or {}
+                            logger.info(
+                                f"  repeat {r + 1}/{args.repeat}: "
+                                f"prompt_tps={_s.get('prompt_tps', 0):.2f} "
+                                f"gen_tps={_s.get('generation_tps', 0):.2f}"
+                            )
                         else:
                             # Concurrent: fire N requests in parallel
                             # Pre-build prompt once, barrier ensures simultaneous dispatch
@@ -598,6 +751,8 @@ def main() -> int:
                                 "max_tokens": tg,
                                 "logprobs": False,
                                 "use_prefix_cache": args.use_prefix_cache,
+                                # Argmax sampling — matches mlx_lm.benchmark default
+                                "temperature": 0.0,
                             }
                             barrier = threading.Barrier(concurrency)
                             batch_start = threading.Event()
@@ -710,10 +865,12 @@ def main() -> int:
                         gen_tps = per_req_tps * concurrency
                         ptok = mean(x["stats"]["prompt_tokens"] for x in runs)
                         gtok = mean(x["stats"]["generation_tokens"] for x in runs)
-                        peak = mean(
-                            x["stats"]["peak_memory_usage"]["inBytes"] for x in runs
-                        )
 
+                        def _peak_bytes(s: dict[str, Any]) -> float:
+                            pm = s["peak_memory_usage"]
+                            return pm.get("inBytes") or pm.get("in_bytes", 0)
+
+                        peak = mean(_peak_bytes(x["stats"]) for x in runs)
                         summary = (
                             f"prompt_tps={prompt_tps:.2f} gen_tps={gen_tps:.2f}    "
                             f"prompt_tokens={ptok} gen_tokens={gtok}    "
@@ -738,15 +895,16 @@ def main() -> int:
                 if placement_metrics:
                     all_system_metrics.update(placement_metrics)
 
-            try:
-                client.request_json("DELETE", f"/instance/{instance_id}")
-            except ExoHttpError as e:
-                if e.status != 404:
-                    raise
-            wait_for_instance_gone(client, instance_id)
-            logger.debug(f"Deleted instance {instance_id}")
+            if created_instance and instance_id is not None:
+                try:
+                    client.request_json("DELETE", f"/instance/{instance_id}")
+                except ExoHttpError as e:
+                    if e.status != 404:
+                        raise
+                wait_for_instance_gone(client, instance_id)
+                logger.debug(f"Deleted instance {instance_id}")
 
-            time.sleep(5)
+                time.sleep(5)
 
     output: dict[str, Any] = {"runs": all_rows}
     if cluster_snapshot:

bench/exo_eval.py

@@ -47,6 +47,7 @@ from harness import (
     ExoHttpError,
     add_common_instance_args,
     capture_cluster_snapshot,
+    find_existing_instance,
     instance_id_from_instance,
     nodes_used_in_instance,
     resolve_model_short_id,
@@ -62,6 +63,15 @@ from loguru import logger
 # ---------------------------------------------------------------------------
 
 MAX_RETRIES = 30
+INSTANCE_HEALTH_CHECK_AFTER = (
+    3  # Check instance health after this many consecutive failures
+)
+
+
+class InstanceFailedError(RuntimeError):
+    """Raised when the exo instance is detected as failed/gone."""
+
+
 DEFAULT_MAX_TOKENS = 16_384
 REASONING_MAX_TOKENS = 131_072
 TEMPERATURE_NON_REASONING = 0.0
@@ -271,7 +281,7 @@ def run_humaneval_test(
 
 @dataclass
 class QuestionResult:
-    question_id: int
+    question_id: int | str
     prompt: str
     response: str
     extracted_answer: str | None
@@ -281,7 +291,11 @@ class QuestionResult:
     prompt_tokens: int = 0
     completion_tokens: int = 0
     reasoning_tokens: int = 0
+    reasoning_content: str = ""
+    finish_reason: str = ""
     elapsed_s: float = 0.0
+    power_watts: float = 0.0
+    energy_joules: float = 0.0
 
 
 @dataclass
@@ -517,6 +531,10 @@ class ApiResult:
     prompt_tokens: int
     completion_tokens: int
     reasoning_tokens: int
+    reasoning_content: str = ""
+    finish_reason: str = ""
+    power_watts: float = 0.0
+    energy_joules: float = 0.0
 
 
 async def _call_api(
@@ -530,6 +548,9 @@ async def _call_api(
     system_message: str | None = None,
     reasoning_effort: str | None = None,
     top_p: float | None = None,
+    top_k: int | None = None,
+    min_p: float | None = None,
+    enable_thinking: bool | None = None,
 ) -> ApiResult:
     messages = []
     if system_message:
@@ -546,6 +567,12 @@ async def _call_api(
         body["reasoning_effort"] = reasoning_effort
     if top_p is not None:
         body["top_p"] = top_p
+    if top_k is not None:
+        body["top_k"] = top_k
+    if min_p is not None:
+        body["min_p"] = min_p
+    if enable_thinking is not None:
+        body["enable_thinking"] = enable_thinking
 
     resp = await client.post(
         f"{base_url}/v1/chat/completions",
@@ -554,19 +581,40 @@ async def _call_api(
     )
     resp.raise_for_status()
     data = resp.json()
-    content = data["choices"][0]["message"]["content"]
-    if not content or not content.strip():
+    choice = data["choices"][0]
+    message = choice["message"]
+    content = message.get("content") or ""
+    reasoning_content = message.get("reasoning_content") or ""
+    finish_reason = choice.get("finish_reason") or ""
+
+    # For thinking models, empty content is expected when finish_reason is "length"
+    if not content.strip() and finish_reason != "length" and not reasoning_content:
         raise ValueError("Empty response from model")
     usage = data.get("usage", {})
     details = usage.get("completion_tokens_details", {})
+    power = data.get("power_usage") or {}
     return ApiResult(
         content=content,
         prompt_tokens=usage.get("prompt_tokens", 0),
         completion_tokens=usage.get("completion_tokens", 0),
         reasoning_tokens=details.get("reasoning_tokens", 0) if details else 0,
+        reasoning_content=reasoning_content,
+        finish_reason=finish_reason,
+        power_watts=power.get("total_avg_sys_power_watts", 0.0),
+        energy_joules=power.get("total_energy_joules", 0.0),
     )
 
 
+async def _check_instance_health(base_url: str) -> bool:
+    """Return True if the exo instance is still reachable."""
+    try:
+        async with httpx.AsyncClient() as c:
+            resp = await c.get(f"{base_url}/models", timeout=5.0)
+            return resp.status_code == 200
+    except Exception:
+        return False
+
+
 async def call_with_retries(
     client: httpx.AsyncClient,
     base_url: str,
@@ -578,8 +626,14 @@ async def call_with_retries(
     system_message: str | None = None,
     reasoning_effort: str | None = None,
     top_p: float | None = None,
+    top_k: int | None = None,
+    min_p: float | None = None,
+    enable_thinking: bool | None = None,
+    instance_failed: asyncio.Event | None = None,
 ) -> ApiResult | None:
     for attempt in range(MAX_RETRIES):
+        if instance_failed and instance_failed.is_set():
+            raise InstanceFailedError("Instance already marked as failed")
         try:
             return await _call_api(
                 client,
@@ -592,8 +646,30 @@ async def call_with_retries(
                 system_message,
                 reasoning_effort,
                 top_p,
+                top_k,
+                min_p,
+                enable_thinking,
             )
         except Exception as e:
+            is_conn_error = isinstance(
+                e,
+                (
+                    httpx.ConnectError,
+                    httpx.RemoteProtocolError,
+                    ConnectionRefusedError,
+                    OSError,
+                ),
+            )
+            if (
+                is_conn_error
+                and attempt >= INSTANCE_HEALTH_CHECK_AFTER
+                and not await _check_instance_health(base_url)
+            ):
+                if instance_failed:
+                    instance_failed.set()
+                raise InstanceFailedError(
+                    f"Instance is down after {attempt + 1} failures: {e}"
+                ) from e
             if attempt < MAX_RETRIES - 1:
                 wait = min(2**attempt, 60)
                 logger.warning(
@@ -618,10 +694,16 @@ async def evaluate_benchmark(
     max_tokens: int,
     concurrency: int = 1,
     limit: int | None = None,
+    offset: int = 0,
     timeout: float | None = None,
     reasoning_effort: str | None = None,
     top_p: float | None = None,
+    top_k: int | None = None,
+    min_p: float | None = None,
+    enable_thinking: bool | None = None,
     difficulty: str | None = None,
+    checkpoint_path: Path | None = None,
+    release_version: str | None = None,
 ) -> list[QuestionResult]:
     """Run a benchmark. Returns per-question results."""
     import datasets
@@ -652,7 +734,21 @@ async def evaluate_benchmark(
         ds = ds.filter(lambda x: x["difficulty"] == difficulty)
         logger.info(f"Filtered to {len(ds)} {difficulty} problems")
 
+    if release_version and "release_version" in ds.column_names:
+        ds = ds.filter(lambda x: x["release_version"] == release_version)
+        logger.info(
+            f"Filtered to {len(ds)} problems with release_version={release_version}"
+        )
+
+    # Sort by question_id to match LCB runner ordering (scenario_router.py:60).
+    # This ensures [offset:offset+limit] slices select the same problems as vllm.
+    if "question_id" in ds.column_names:
+        ds = ds.sort("question_id")
+
     total = len(ds)
+    if offset > 0:
+        ds = ds.select(range(min(offset, total), total))
+        total = len(ds)
     if limit and limit < total:
         ds = ds.select(range(limit))
         total = limit
@@ -660,6 +756,13 @@ async def evaluate_benchmark(
     logger.info(
         f"Evaluating {benchmark_name}: {total} questions, concurrency={concurrency}, "
         f"temperature={temperature}, max_tokens={max_tokens}"
+        + (f", top_k={top_k}" if top_k is not None else "")
+        + (f", min_p={min_p}" if min_p is not None else "")
+        + (
+            f", enable_thinking={enable_thinking}"
+            if enable_thinking is not None
+            else ""
+        )
     )
 
     if config.kind == "code":
@@ -667,16 +770,64 @@ async def evaluate_benchmark(
             "Code benchmarks execute model-generated code. Use a sandboxed environment."
         )
 
+    # Load checkpoint for resume
+    checkpoint_data: dict[str | int, dict[str, Any]] = {}
+    if checkpoint_path and checkpoint_path.exists():
+        with open(checkpoint_path) as f:
+            for line in f:
+                entry = json.loads(line)
+                checkpoint_data[entry["question_id"]] = entry
+        logger.info(f"Loaded {len(checkpoint_data)} checkpointed results")
+
     semaphore = asyncio.Semaphore(concurrency)
+    instance_failed = asyncio.Event()
     results: list[QuestionResult | None] = [None] * total
     completed = 0
     lock = asyncio.Lock()
 
+    def _get_question_id(idx: int, doc: dict) -> str | int:
+        """Get a stable question ID for checkpointing."""
+        if benchmark_name == "livecodebench":
+            return doc.get("question_id", idx)
+        elif benchmark_name == "humaneval":
+            return doc.get("task_id", idx)
+        return idx
+
     async def process_question(
         idx: int, doc: dict, http_client: httpx.AsyncClient
     ) -> None:
         nonlocal completed
         system_msg = None
+        question_id = _get_question_id(idx, doc)
+
+        # Bail out early if instance is already dead
+        if instance_failed.is_set():
+            return
+
+        # Check checkpoint
+        if question_id in checkpoint_data:
+            cached = checkpoint_data[question_id]
+            results[idx] = QuestionResult(
+                question_id=question_id,
+                prompt=cached.get("prompt", ""),
+                response=cached.get("response", ""),
+                extracted_answer=cached.get("extracted_answer"),
+                gold_answer=cached.get("gold_answer", ""),
+                correct=cached.get("correct", False),
+                error=cached.get("error"),
+                prompt_tokens=cached.get("prompt_tokens", 0),
+                completion_tokens=cached.get("completion_tokens", 0),
+                reasoning_tokens=cached.get("reasoning_tokens", 0),
+                reasoning_content=cached.get("reasoning_content", ""),
+                finish_reason=cached.get("finish_reason", ""),
+                elapsed_s=cached.get("elapsed_s", 0.0),
+                power_watts=cached.get("power_watts", 0.0),
+                energy_joules=cached.get("energy_joules", 0.0),
+            )
+            async with lock:
+                completed += 1
+            logger.info(f"  [{completed}/{total}] {question_id} (cached)")
+            return
 
         if benchmark_name == "gpqa_diamond":
             prompt, gold = format_gpqa_question(doc, idx)
@@ -697,24 +848,50 @@ async def evaluate_benchmark(
             raise ValueError(f"Unknown benchmark: {benchmark_name}")
 
         async with semaphore:
+            if instance_failed.is_set():
+                return
             t0 = time.monotonic()
-            api_result = await call_with_retries(
-                http_client,
-                base_url,
-                model,
-                prompt,
-                temperature,
-                max_tokens,
-                timeout,
-                system_message=system_msg,
-                reasoning_effort=reasoning_effort,
-                top_p=top_p,
-            )
+            try:
+                # Race the API call against the instance_failed event
+                api_task = asyncio.create_task(
+                    call_with_retries(
+                        http_client,
+                        base_url,
+                        model,
+                        prompt,
+                        temperature,
+                        max_tokens,
+                        timeout,
+                        system_message=system_msg,
+                        reasoning_effort=reasoning_effort,
+                        top_p=top_p,
+                        top_k=top_k,
+                        min_p=min_p,
+                        enable_thinking=enable_thinking,
+                        instance_failed=instance_failed,
+                    )
+                )
+                failed_waiter = asyncio.create_task(instance_failed.wait())
+                done, pending = await asyncio.wait(
+                    [api_task, failed_waiter],
+                    return_when=asyncio.FIRST_COMPLETED,
+                )
+                for p in pending:
+                    p.cancel()
+                    with contextlib.suppress(asyncio.CancelledError):
+                        await p
+                if instance_failed.is_set() and api_task not in done:
+                    logger.error(f"Instance failed, aborting {question_id}")
+                    return
+                api_result = api_task.result()
+            except InstanceFailedError:
+                logger.error(f"Instance failed, skipping {question_id}")
+                return
             elapsed = time.monotonic() - t0
 
         if api_result is None:
             result = QuestionResult(
-                question_id=idx,
+                question_id=question_id,
                 prompt=prompt,
                 response="",
                 extracted_answer=None,
@@ -729,13 +906,17 @@ async def evaluate_benchmark(
                 "prompt_tokens": api_result.prompt_tokens,
                 "completion_tokens": api_result.completion_tokens,
                 "reasoning_tokens": api_result.reasoning_tokens,
+                "reasoning_content": api_result.reasoning_content,
+                "finish_reason": api_result.finish_reason,
                 "elapsed_s": elapsed,
+                "power_watts": api_result.power_watts,
+                "energy_joules": api_result.energy_joules,
             }
 
             if config.kind == "mc":
                 extracted = extract_mc_answer(response, valid_letters)
                 result = QuestionResult(
-                    question_id=idx,
+                    question_id=question_id,
                     prompt=prompt,
                     response=response,
                     extracted_answer=extracted,
@@ -749,7 +930,7 @@ async def evaluate_benchmark(
                     check_aime_answer(extracted, int(gold)) if extracted else False
                 )
                 result = QuestionResult(
-                    question_id=idx,
+                    question_id=question_id,
                     prompt=prompt,
                     response=response,
                     extracted_answer=extracted,
@@ -763,7 +944,7 @@ async def evaluate_benchmark(
                 code = extract_code_block(response, preserve_indent=keep_indent)
                 if code is None:
                     result = QuestionResult(
-                        question_id=idx,
+                        question_id=question_id,
                         prompt=prompt,
                         response=response,
                         extracted_answer=None,
@@ -778,7 +959,7 @@ async def evaluate_benchmark(
                         code,
                     )
                     result = QuestionResult(
-                        question_id=idx,
+                        question_id=question_id,
                         prompt=prompt,
                         response=response,
                         extracted_answer="pass" if passed else "fail",
@@ -793,7 +974,7 @@ async def evaluate_benchmark(
                         exec_meta["sample"],
                     )
                     result = QuestionResult(
-                        question_id=idx,
+                        question_id=question_id,
                         prompt=prompt,
                         response=response,
                         extracted_answer="pass" if passed else "fail",
@@ -804,7 +985,7 @@ async def evaluate_benchmark(
                     )
                 else:
                     result = QuestionResult(
-                        question_id=idx,
+                        question_id=question_id,
                         prompt=prompt,
                         response=response,
                         extracted_answer=None,
@@ -815,7 +996,7 @@ async def evaluate_benchmark(
                     )
             else:
                 result = QuestionResult(
-                    question_id=idx,
+                    question_id=question_id,
                     prompt=prompt,
                     response=response,
                     extracted_answer=None,
@@ -827,24 +1008,82 @@ async def evaluate_benchmark(
 
         results[idx] = result
 
+        # Write checkpoint (skip infra failures so they get retried on resume,
+        # but keep wrong answers — they are legitimate results)
+        if checkpoint_path is not None and result.response:
+            _write_checkpoint(checkpoint_path, result)
+
         async with lock:
             completed += 1
             n = completed
-        if n % max(1, total // 20) == 0 or n == total:
-            correct_so_far = sum(1 for r in results if r is not None and r.correct)
-            answered = sum(1 for r in results if r is not None)
-            logger.info(
-                f"  [{n}/{total}] {correct_so_far}/{answered} correct "
-                f"({correct_so_far / max(answered, 1):.1%})"
-            )
+
+        # Log progress
+        thinking_info = ""
+        if result.reasoning_content:
+            thinking_info = f", {len(result.reasoning_content)} chars thinking"
+        logger.info(
+            f"  [{n}/{total}] {question_id}: {len(result.response)} chars{thinking_info}, "
+            f"tokens: {result.prompt_tokens}+{result.completion_tokens} "
+            f"[{result.finish_reason}]"
+            + (f" {result.extracted_answer}" if result.extracted_answer else "")
+        )
+
+    async def _health_monitor() -> None:
+        """Periodically check if the instance is still alive."""
+        # Wait a bit before first check to let things start
+        await asyncio.sleep(10)
+        while not instance_failed.is_set():
+            if not await _check_instance_health(base_url):
+                # Double-check to avoid false positives
+                await asyncio.sleep(2)
+                if not await _check_instance_health(base_url):
+                    logger.error("Health monitor: instance is down!")
+                    instance_failed.set()
+                    return
+            await asyncio.sleep(5)
 
     async with httpx.AsyncClient() as http_client:
+        monitor = asyncio.create_task(_health_monitor())
         tasks = [process_question(i, doc, http_client) for i, doc in enumerate(ds)]
         await asyncio.gather(*tasks)
+        monitor.cancel()
+        with contextlib.suppress(asyncio.CancelledError):
+            await monitor
+
+    if instance_failed.is_set():
+        completed_count = sum(1 for r in results if r is not None)
+        logger.error(
+            f"Instance failed! Completed {completed_count}/{total} problems. "
+            f"Checkpoint saved — restart to resume remaining problems."
+        )
+        raise InstanceFailedError("Instance failed during evaluation")
 
     return [r for r in results if r is not None]
 
 
+def _write_checkpoint(path: Path, result: QuestionResult) -> None:
+    """Append a single result to the JSONL checkpoint file."""
+    entry = {
+        "question_id": result.question_id,
+        "prompt": result.prompt,
+        "response": result.response,
+        "extracted_answer": result.extracted_answer,
+        "gold_answer": result.gold_answer,
+        "correct": result.correct,
+        "error": result.error,
+        "prompt_tokens": result.prompt_tokens,
+        "completion_tokens": result.completion_tokens,
+        "reasoning_tokens": result.reasoning_tokens,
+        "reasoning_content": result.reasoning_content,
+        "finish_reason": result.finish_reason,
+        "elapsed_s": round(result.elapsed_s, 2),
+        "power_watts": round(result.power_watts, 2),
+        "energy_joules": round(result.energy_joules, 2),
+    }
+    with open(path, "a") as f:
+        f.write(json.dumps(entry) + "\n")
+
+
 # ---------------------------------------------------------------------------
 # Results display
 # ---------------------------------------------------------------------------
@@ -867,6 +1106,8 @@ def print_results(
     total_elapsed = sum(r.elapsed_s for r in results)
     wall_clock = max(r.elapsed_s for r in results) if results else 0.0
     avg_gen_tps = total_completion_tokens / total_elapsed if total_elapsed > 0 else 0.0
+    total_energy = sum(r.energy_joules for r in results)
+    avg_power = sum(r.power_watts for r in results) / max(total, 1)
 
     label = f"[c={concurrency}] " if concurrency is not None else ""
     print(f"\n{label}{benchmark_name}: {correct}/{total} ({accuracy:.1%})")
@@ -878,6 +1119,10 @@ def print_results(
         f"  |  total time: {total_elapsed:.1f}s  wall clock: {wall_clock:.1f}s"
     )
     print(tok_line)
+    if total_energy > 0:
+        print(
+            f"  power: avg {avg_power:.1f}W  |  total energy: {total_energy:.1f}J ({total_energy / 3600:.2f}Wh)"
+        )
     if errors:
         print(f"  API errors: {errors}")
     if no_extract:
@@ -896,6 +1141,8 @@ def print_results(
         "total_elapsed_s": total_elapsed,
         "wall_clock_s": wall_clock,
         "avg_gen_tps": avg_gen_tps,
+        "avg_power_watts": avg_power,
+        "total_energy_joules": total_energy,
     }
 
 
@@ -1053,7 +1300,11 @@ def save_results(
                 "prompt_tokens": r.prompt_tokens,
                 "completion_tokens": r.completion_tokens,
                 "reasoning_tokens": r.reasoning_tokens,
+                "reasoning_content": r.reasoning_content,
+                "finish_reason": r.finish_reason,
                 "elapsed_s": round(r.elapsed_s, 2),
+                "power_watts": round(r.power_watts, 2),
+                "energy_joules": round(r.energy_joules, 2),
             }
             for r in results
         ],
@@ -1069,6 +1320,15 @@ def save_results(
 # ---------------------------------------------------------------------------
 
 
+def _checkpoint_path(
+    results_dir: str, benchmark: str, model: str, concurrency: int
+) -> Path:
+    """Return the JSONL checkpoint path for a benchmark run."""
+    out_dir = Path(results_dir) / model.replace("/", "_") / benchmark
+    out_dir.mkdir(parents=True, exist_ok=True)
+    return out_dir / f"c{concurrency}.checkpoint.jsonl"
+
+
 def parse_int_list(values: list[str]) -> list[int]:
     items: list[int] = []
     for v in values:
@@ -1096,6 +1356,12 @@ def main() -> int:
         default=None,
         help="Max questions per benchmark (for fast iteration).",
     )
+    ap.add_argument(
+        "--offset",
+        type=int,
+        default=0,
+        help="Skip first N questions (0-based).",
+    )
 
     reasoning_group = ap.add_mutually_exclusive_group()
     reasoning_group.add_argument(
@@ -1115,6 +1381,8 @@ def main() -> int:
         "--temperature", type=float, default=None, help="Override temperature."
     )
     ap.add_argument("--top-p", type=float, default=None, help="Override top_p.")
+    ap.add_argument("--top-k", type=int, default=None, help="Override top_k.")
+    ap.add_argument("--min-p", type=float, default=None, help="Override min_p.")
     ap.add_argument(
         "--max-tokens", type=int, default=None, help="Override max output tokens."
     )
@@ -1148,15 +1416,31 @@ def main() -> int:
         choices=["easy", "medium", "hard"],
         help="Filter by difficulty (livecodebench only). E.g. --difficulty hard",
     )
+    ap.add_argument(
+        "--release-version",
+        default=None,
+        help="LCB dataset release version (livecodebench only). E.g. release_v5",
+    )
     ap.add_argument(
         "--results-dir",
         default="eval_results",
         help="Directory for result JSON files (default: eval_results).",
     )
     ap.add_argument(
-        "--skip-instance-setup",
+        "--enable-thinking",
+        type=lambda v: v.lower() in ("true", "1", "yes"),
+        default=None,
+        help="Enable thinking mode for models that support it.",
+    )
+    ap.add_argument(
+        "--force",
         action="store_true",
-        help="Skip exo instance management (assumes model is already running).",
+        help="Discard any existing checkpoint and run from scratch.",
+    )
+    ap.add_argument(
+        "--keep-instance",
+        action="store_true",
+        help="Skip deleting the instance after eval (for chaining runs).",
     )
 
     args, _ = ap.parse_known_args()
@@ -1177,13 +1461,26 @@ def main() -> int:
     # Instance management
     client = ExoClient(args.host, args.port, timeout_s=args.timeout)
     instance_id: str | None = None
+    created_instance = False
 
-    if not args.skip_instance_setup:
-        short_id, full_model_id = resolve_model_short_id(
-            client,
-            args.model,
-            force_download=args.force_download,
-        )
+    _short_id, full_model_id = resolve_model_short_id(
+        client,
+        args.model,
+        force_download=args.force_download,
+    )
+
+    # Optionally reuse a running instance for this model
+    if args.reuse_instance:
+        existing = find_existing_instance(client, full_model_id)
+        if existing:
+            instance_id = existing
+            logger.info(f"Reusing existing instance {instance_id}")
+        else:
+            logger.warning(
+                "--reuse-instance: no existing instance found, creating a new one"
+            )
+
+    if instance_id is None:
         selected = settle_and_fetch_placements(
             client,
             full_model_id,
@@ -1198,7 +1495,7 @@ def main() -> int:
             key=lambda p: (
                 str(p.get("instance_meta", "")),
                 str(p.get("sharding", "")),
-                -nodes_used_in_instance(p["instance"]),
+                nodes_used_in_instance(p["instance"]),
             ),
             reverse=True,
         )
@@ -1225,6 +1522,18 @@ def main() -> int:
         if download_duration is not None:
             logger.info(f"Download: {download_duration:.1f}s")
 
+        # Delete any existing instances to free resources before placing
+        try:
+            state = client.request_json("GET", "/state")
+            for old_id in list(state.get("instances", {}).keys()):
+                logger.info(f"Deleting stale instance {old_id}")
+                with contextlib.suppress(ExoHttpError):
+                    client.request_json("DELETE", f"/instance/{old_id}")
+            if state.get("instances"):
+                time.sleep(2)
+        except Exception as e:
+            logger.warning(f"Failed to clean up stale instances: {e}")
+
         client.request_json("POST", "/instance", body={"instance": instance})
         try:
             wait_for_instance_ready(client, instance_id)
@@ -1234,10 +1543,9 @@ def main() -> int:
                 client.request_json("DELETE", f"/instance/{instance_id}")
             return 1
         time.sleep(1)
-        cluster_snapshot = capture_cluster_snapshot(client)
-    else:
-        full_model_id = args.model
-        cluster_snapshot = None
+        created_instance = True
+
+    cluster_snapshot = capture_cluster_snapshot(client)
 
     # Auto-detect reasoning from model config
     model_config = load_model_config(full_model_id)
@@ -1291,16 +1599,57 @@ def main() -> int:
         reasoning_effort = str(cfg["reasoning_effort"])
     else:
         reasoning_effort = "high" if is_reasoning else None
+
+    if args.top_k is not None:
+        top_k: int | None = args.top_k
+    elif "top_k" in cfg:
+        top_k = int(cfg["top_k"])
+    else:
+        top_k = None
+
+    if args.min_p is not None:
+        min_p: float | None = args.min_p
+    elif "min_p" in cfg:
+        min_p = float(cfg["min_p"])
+    else:
+        min_p = None
+
+    if args.enable_thinking is not None:
+        enable_thinking: bool | None = args.enable_thinking
+    elif "enable_thinking" in cfg:
+        enable_thinking = bool(cfg["enable_thinking"])
+    else:
+        enable_thinking = None
+
     base_url = f"http://{args.host}:{args.port}"
 
     logger.info(f"Model: {full_model_id}")
     logger.info(
         f"Settings: temperature={temperature}, max_tokens={max_tokens}, "
         + (f"top_p={top_p}, " if top_p is not None else "")
+        + (f"top_k={top_k}, " if top_k is not None else "")
+        + (f"min_p={min_p}, " if min_p is not None else "")
         + f"reasoning={'yes' if is_reasoning else 'no'}"
         + (f", reasoning_effort={reasoning_effort}" if reasoning_effort else "")
+        + (
+            f", enable_thinking={enable_thinking}"
+            if enable_thinking is not None
+            else ""
+        )
     )
 
+    # Common kwargs for evaluate_benchmark
+    eval_kwargs: dict[str, Any] = {
+        "reasoning_effort": reasoning_effort,
+        "top_p": top_p,
+        "top_k": top_k,
+        "min_p": min_p,
+        "enable_thinking": enable_thinking,
+        "difficulty": args.difficulty,
+        "offset": args.offset,
+        "release_version": args.release_version,
+    }
+
     try:
         if args.compare_concurrency:
             concurrency_levels = parse_int_list(args.compare_concurrency)
@@ -1309,6 +1658,11 @@ def main() -> int:
                 for c in concurrency_levels:
                     logger.info(f"\n{'=' * 50}")
                     logger.info(f"Running {task_name} at concurrency={c}")
+                    checkpoint_path = _checkpoint_path(
+                        args.results_dir, task_name, full_model_id, c
+                    )
+                    if args.force and checkpoint_path.exists():
+                        checkpoint_path.unlink()
                     results = asyncio.run(
                         evaluate_benchmark(
                             task_name,
@@ -1319,9 +1673,8 @@ def main() -> int:
                             concurrency=c,
                             limit=args.limit,
                             timeout=args.request_timeout,
-                            reasoning_effort=reasoning_effort,
-                            top_p=top_p,
-                            difficulty=args.difficulty,
+                            checkpoint_path=checkpoint_path,
+                            **eval_kwargs,
                         )
                     )
                     if results:
@@ -1336,10 +1689,18 @@ def main() -> int:
                             cluster=cluster_snapshot,
                         )
                         results_by_c[c] = results
+                    # Clean up checkpoint on success
+                    if checkpoint_path.exists():
+                        checkpoint_path.unlink()
                 if len(results_by_c) >= 2:
                     print_comparison(task_name, results_by_c)
         else:
             for task_name in task_names:
+                checkpoint_path = _checkpoint_path(
+                    args.results_dir, task_name, full_model_id, args.num_concurrent
+                )
+                if args.force and checkpoint_path.exists():
+                    checkpoint_path.unlink()
                 results = asyncio.run(
                     evaluate_benchmark(
                         task_name,
@@ -1350,9 +1711,8 @@ def main() -> int:
                         concurrency=args.num_concurrent,
                         limit=args.limit,
                         timeout=args.request_timeout,
-                        reasoning_effort=reasoning_effort,
-                        top_p=top_p,
-                        difficulty=args.difficulty,
+                        checkpoint_path=checkpoint_path,
+                        **eval_kwargs,
                     )
                 )
                 if results:
@@ -1366,14 +1726,25 @@ def main() -> int:
                         scores,
                         cluster=cluster_snapshot,
                     )
+                # Clean up checkpoint on success
+                if checkpoint_path.exists():
+                    checkpoint_path.unlink()
     finally:
-        if instance_id is not None:
-            try:
-                client.request_json("DELETE", f"/instance/{instance_id}")
-            except ExoHttpError as e:
-                if e.status != 404:
-                    raise
-            wait_for_instance_gone(client, instance_id)
+        if created_instance and instance_id is not None:
+            if args.keep_instance:
+                logger.info(f"Keeping instance {instance_id} (--keep-instance)")
+            else:
+                try:
+                    client.request_json("DELETE", f"/instance/{instance_id}")
+                except ExoHttpError as e:
+                    if e.status != 404:
+                        raise
+                try:
+                    wait_for_instance_gone(client, instance_id)
+                except TimeoutError:
+                    logger.warning(
+                        f"Timed out waiting for instance {instance_id} to be deleted"
+                    )
 
     return 0
 

bench/harness.py

@@ -6,6 +6,7 @@ import http.client
 import json
 import os
 import time
+from collections.abc import Iterator
 from typing import Any
 from urllib.parse import urlencode
 
@@ -69,6 +70,30 @@ class ExoClient:
     def post_bench_chat_completions(self, payload: dict[str, Any]) -> dict[str, Any]:
         return self.request_json("POST", "/bench/chat/completions", body=payload)
 
+    def stream_bench_chat_completions(self, payload: dict[str, Any]) -> Iterator[str]:
+        """POST /bench/chat/completions with stream=True, yielding raw SSE lines."""
+        payload = {**payload, "stream": True}
+        data = json.dumps(payload).encode("utf-8")
+        conn = http.client.HTTPConnection(self.host, self.port, timeout=self.timeout_s)
+        try:
+            conn.request(
+                "POST",
+                "/bench/chat/completions",
+                body=data,
+                headers={
+                    "Content-Type": "application/json",
+                    "Accept": "text/event-stream",
+                },
+            )
+            resp = conn.getresponse()
+            if resp.status >= 400:
+                raw = resp.read().decode("utf-8", errors="replace")
+                raise ExoHttpError(resp.status, resp.reason, raw[:300])
+            for line in resp:
+                yield line.decode("utf-8", errors="replace")
+        finally:
+            conn.close()
+
     def get_state_path(self, path: str) -> Any:
         try:
             return self.request_json("GET", f"/state/{path}")
@@ -268,11 +293,15 @@ def sharding_filter(sharding: str, wanted: str) -> bool:
 
 
 def fetch_and_filter_placements(
-    client: ExoClient, full_model_id: str, args: argparse.Namespace
+    client: ExoClient,
+    full_model_id: str,
+    args: argparse.Namespace,
+    node_id: str | None = None,
 ) -> list[dict[str, Any]]:
-    previews_resp = client.request_json(
-        "GET", "/instance/previews", params={"model_id": full_model_id}
-    )
+    params: dict[str, str] = {"model_id": full_model_id}
+    if node_id is not None:
+        params["node_ids"] = node_id
+    previews_resp = client.request_json("GET", "/instance/previews", params=params)
     previews = previews_resp.get("previews") or []
 
     selected: list[dict[str, Any]] = []
@@ -332,8 +361,9 @@ def settle_and_fetch_placements(
     full_model_id: str,
     args: argparse.Namespace,
     settle_timeout: float = 0,
+    node_id: str | None = None,
 ) -> list[dict[str, Any]]:
-    selected = fetch_and_filter_placements(client, full_model_id, args)
+    selected = fetch_and_filter_placements(client, full_model_id, args, node_id=node_id)
 
     if not selected and settle_timeout > 0:
         backoff = _SETTLE_INITIAL_BACKOFF_S
@@ -346,7 +376,9 @@ def settle_and_fetch_placements(
             )
             time.sleep(min(backoff, remaining))
             backoff = min(backoff * _SETTLE_BACKOFF_MULTIPLIER, _SETTLE_MAX_BACKOFF_S)
-            selected = fetch_and_filter_placements(client, full_model_id, args)
+            selected = fetch_and_filter_placements(
+                client, full_model_id, args, node_id=node_id
+            )
 
     return selected
 
@@ -462,9 +494,8 @@ def run_planning_phase(
         )
         logger.info(f"Started download on {node_id}")
 
-    # Wait for downloads
-    start = time.time()
-    while time.time() - start < timeout:
+    # Wait for downloads (no timeout — poll until complete or failed)
+    while True:
         all_done = True
         for node_id in node_ids:
             node_downloads = client.get_node_downloads(node_id) or []
@@ -514,9 +545,24 @@ def run_planning_phase(
             if download_t0 is not None:
                 return time.perf_counter() - download_t0
             return None
-        time.sleep(1)
+        time.sleep(10)
 
-    raise TimeoutError("Downloads did not complete in time")
+
+def find_existing_instance(client: ExoClient, model_id: str) -> str | None:
+    """Find an existing running instance for the given model."""
+    try:
+        state = client.request_json("GET", "/state")
+    except Exception:
+        return None
+    for inst_id, inst in state.get("instances", {}).items():
+        # Instance structure is nested: {"MlxJacclInstance": {"shardAssignments": {"modelId": ...}}}
+        for _inst_type, inner in inst.items():
+            if not isinstance(inner, dict):
+                continue
+            sa = inner.get("shardAssignments", {})
+            if sa.get("modelId") == model_id:
+                return inst_id
+    return None
 
 
 def add_common_instance_args(ap: argparse.ArgumentParser) -> None:
@@ -564,7 +610,7 @@ def add_common_instance_args(ap: argparse.ArgumentParser) -> None:
     ap.add_argument(
         "--settle-timeout",
         type=float,
-        default=0,
+        default=60.0,
         help="Max seconds to wait for the cluster to produce valid placements (0 = try once).",
     )
     ap.add_argument(
@@ -572,3 +618,8 @@ def add_common_instance_args(ap: argparse.ArgumentParser) -> None:
         action="store_true",
         help="Delete existing models from smallest to largest to make room for benchmark model.",
     )
+    ap.add_argument(
+        "--reuse-instance",
+        action="store_true",
+        help="Reuse an existing running instance for this model instead of creating a new one.",
+    )

bench/prefill-decode.toml

@@ -0,0 +1,36 @@
+# Prefill/Decode disaggregation benchmark config.
+#
+# Top-level keys are bench-wide. [prefill] and [decode] sections set per-side
+# placement filters and (optionally) per-side model.
+#
+# Example:
+#   uv run python bench/prefill_decode_bench.py --config bench/prefill-decode.toml
+
+host = "james"
+port = 52415
+timeout = 7200.0
+settle_timeout = 60.0
+
+# Workload
+pp = [4096]
+tg = [512]
+repeat = 1
+warmup = 0
+
+json_out = "bench/prefill_decode_results.json"
+
+[prefill]
+model = "mlx-community/gpt-oss-20b-MXFP4-Q8"
+node = "mike"
+instance_meta = "ring"
+sharding = "pipeline"
+min_nodes = 1
+max_nodes = 1
+
+[decode]
+model = "mlx-community/gpt-oss-20b-MXFP4-Q8"
+node = "james"
+instance_meta = "ring"
+sharding = "pipeline"
+min_nodes = 1
+max_nodes = 1

bench/prefill_decode_bench.py

@@ -0,0 +1,785 @@
+# type: ignore
+#!/usr/bin/env python3
+"""Disaggregated prefill-decode benchmark for exo (MLX → MLX).
+
+Spins up two MLX instances on the cluster, marks one as Prefill source and
+the other as Decode target via /v1/instance-links, then sends chat
+completions to the API. The master routes the request to the decode
+instance and stamps `prefill_endpoint` pointing at the prefill instance —
+the worker decides per-request whether to ship prefill remotely
+(uncached_count > REMOTE_PREFILL_MIN_TOKENS).
+
+Usage:
+    uv run python bench/prefill_decode_bench.py --model <id> --pp 2048,8192 --tg 128
+    uv run python bench/prefill_decode_bench.py --model <id> --pp 4096 --tg 128 --repeat 3
+    uv run python bench/prefill_decode_bench.py --model <id> --pp 2048 --tg 128 --dry-run
+"""
+
+from __future__ import annotations
+
+import argparse
+import contextlib
+import copy
+import itertools
+import json
+import sys
+import time
+import tomllib
+from pathlib import Path
+from statistics import mean
+from typing import Any
+
+from exo_bench import (
+    PromptSizer,
+    format_peak_memory,
+    load_tokenizer_for_bench,
+    parse_int_list,
+)
+from harness import (
+    ExoClient,
+    ExoHttpError,
+    add_common_instance_args,
+    instance_id_from_instance,
+    node_ids_from_instance,
+    nodes_used_in_instance,
+    resolve_model_short_id,
+    run_planning_phase,
+    settle_and_fetch_placements,
+    unwrap_instance,
+    wait_for_instance_gone,
+    wait_for_instance_ready,
+)
+from loguru import logger
+
+
+def _node_id_to_friendly(client: ExoClient) -> dict[str, str]:
+    identities = client.get_node_identities() or {}
+    out: dict[str, str] = {}
+    for node_id, identity in identities.items():
+        if isinstance(identity, dict):
+            name = identity.get("friendlyName") or identity.get("friendly_name")
+            if isinstance(name, str):
+                out[str(node_id)] = name
+    return out
+
+
+def _placement_node_friendly_names(
+    placement: dict[str, Any], id_to_friendly: dict[str, str]
+) -> list[str]:
+    instance = placement["instance"]
+    return [id_to_friendly.get(nid, nid) for nid in node_ids_from_instance(instance)]
+
+
+def _filter_by_node(
+    placements: list[dict[str, Any]],
+    friendly_name: str,
+    id_to_friendly: dict[str, str],
+) -> list[dict[str, Any]]:
+    target = friendly_name.lower()
+    matched: list[dict[str, Any]] = []
+    for p in placements:
+        names = [n.lower() for n in _placement_node_friendly_names(p, id_to_friendly)]
+        if any(target == n or target in n for n in names):
+            matched.append(p)
+    return matched
+
+
+def _node_id_by_friendly(id_to_friendly: dict[str, str], target: str) -> str | None:
+    target_lc = target.lower()
+    for nid, name in id_to_friendly.items():
+        if target_lc == name.lower() or target_lc in name.lower():
+            return nid
+    return None
+
+
+def _load_toml(path: str) -> dict[str, Any]:
+    with Path(path).open("rb") as f:
+        return tomllib.load(f)
+
+
+_TOP_LEVEL_TOML_KEYS = {
+    "host",
+    "port",
+    "timeout",
+    "settle_timeout",
+    "model",
+    "pp",
+    "tg",
+    "repeat",
+    "warmup",
+    "json_out",
+    "instance_meta",
+    "sharding",
+    "min_nodes",
+    "max_nodes",
+    "force_download",
+    "danger_delete_downloads",
+    "all_combinations",
+}
+
+
+def _inject_toml_into_argv() -> None:
+    """If --config X is in sys.argv, pre-load it and inject required CLI args
+    (--model, --pp, --tg) so argparse's required=True checks pass."""
+    argv = sys.argv
+    if "--config" not in argv:
+        return
+    idx = argv.index("--config")
+    if idx + 1 >= len(argv):
+        return
+    cfg_path = argv[idx + 1]
+    cfg = _load_toml(cfg_path)
+    decode = cfg.get("decode", {})
+
+    def _has(flag: str) -> bool:
+        return any(a == flag or a.startswith(flag + "=") for a in argv)
+
+    # --model: prefer top-level, then [decode].model
+    if not _has("--model"):
+        model = cfg.get("model") or decode.get("model")
+        if model:
+            argv += ["--model", str(model)]
+    if not _has("--pp"):
+        pp = cfg.get("pp")
+        if pp:
+            argv += (
+                ["--pp", *(str(x) for x in pp)]
+                if isinstance(pp, list)
+                else [
+                    "--pp",
+                    str(pp),
+                ]
+            )
+    if not _has("--tg"):
+        tg = cfg.get("tg")
+        if tg:
+            argv += (
+                ["--tg", *(str(x) for x in tg)]
+                if isinstance(tg, list)
+                else [
+                    "--tg",
+                    str(tg),
+                ]
+            )
+
+
+def _merge_toml_into_args(args: argparse.Namespace, cfg: dict[str, Any]) -> None:
+    """Apply top-level toml keys onto args namespace where args has a default."""
+    for key, value in cfg.items():
+        if key in {"prefill", "decode"}:
+            continue
+        if key not in _TOP_LEVEL_TOML_KEYS:
+            continue
+        attr = key
+        current = getattr(args, attr, None)
+        if current in (None, [], False):
+            setattr(args, attr, value)
+
+
+def _side_args(
+    base: argparse.Namespace, overrides: dict[str, Any]
+) -> argparse.Namespace:
+    out = copy.copy(base)
+    for k in (
+        "instance_meta",
+        "sharding",
+        "min_nodes",
+        "max_nodes",
+        "skip_pipeline_jaccl",
+        "skip_tensor_ring",
+    ):
+        if k in overrides:
+            setattr(out, k, overrides[k])
+    return out
+
+
+def _pick_two_distinct_placements(
+    placements: list[dict[str, Any]],
+) -> tuple[dict[str, Any], dict[str, Any]] | None:
+    if len(placements) < 2:
+        return None
+    seen_nodes: set[tuple[str, ...]] = set()
+    chosen: list[dict[str, Any]] = []
+    for p in placements:
+        nodes = tuple(sorted(str(n) for n in p.get("nodes", [])))
+        if nodes in seen_nodes:
+            continue
+        seen_nodes.add(nodes)
+        chosen.append(p)
+        if len(chosen) == 2:
+            return chosen[0], chosen[1]
+    return None
+
+
+def _create_instance_link(
+    client: ExoClient,
+    prefill_instance_id: str,
+    decode_instance_id: str,
+) -> str:
+    out = client.request_json(
+        "POST",
+        "/v1/instance-links",
+        body={
+            "prefill_instances": [prefill_instance_id],
+            "decode_instances": [decode_instance_id],
+        },
+    )
+    return str(out.get("commandId", ""))
+
+
+def _list_instance_links(client: ExoClient) -> list[dict[str, Any]]:
+    out = client.request_json("GET", "/v1/instance-links")
+    return out if isinstance(out, list) else []
+
+
+def _delete_instance_link(client: ExoClient, link_id: str) -> None:
+    client.request_json("DELETE", f"/v1/instance-links/{link_id}")
+
+
+def run_one(
+    client: ExoClient,
+    model_id: str,
+    pp_hint: int,
+    tg: int,
+    prompt_sizer: PromptSizer,
+) -> tuple[dict[str, Any], int]:
+    content, pp_tokens = prompt_sizer.build(pp_hint)
+    payload: dict[str, Any] = {
+        "model": model_id,
+        "messages": [{"role": "user", "content": content}],
+        "stream": False,
+        "max_tokens": tg,
+    }
+
+    t0 = time.perf_counter()
+    out = client.post_bench_chat_completions(payload)
+    elapsed = time.perf_counter() - t0
+
+    stats = out.get("generation_stats")
+    choices = out.get("choices") or [{}]
+    message = choices[0].get("message", {}) if choices else {}
+    text = message.get("content") or ""
+    preview = text[:200] if text else ""
+
+    return {
+        "elapsed_s": elapsed,
+        "output_text_preview": preview,
+        "stats": stats,
+    }, pp_tokens
+
+
+def _run_phase(
+    *,
+    client: ExoClient,
+    label: str,
+    pp_tg_pairs: list[tuple[int, int]],
+    model_id: str,
+    prompt_sizer: PromptSizer,
+    warmup: int,
+    repeat: int,
+    common_meta: dict[str, Any],
+) -> list[dict[str, Any]]:
+    logger.info(f"=== phase: {label} (model={model_id}) ===")
+    rows: list[dict[str, Any]] = []
+    for i in range(warmup):
+        run_one(client, model_id, pp_tg_pairs[0][0], pp_tg_pairs[0][1], prompt_sizer)
+        logger.debug(f"  warmup {i + 1}/{warmup} done")
+
+    for pp, tg in pp_tg_pairs:
+        logger.info(f"--- {label}: pp={pp} tg={tg} ---")
+        runs: list[dict[str, Any]] = []
+        for r in range(repeat):
+            time.sleep(2)
+            try:
+                row, actual_pp_tokens = run_one(client, model_id, pp, tg, prompt_sizer)
+            except Exception as e:
+                logger.error(e)
+                continue
+            row.update(common_meta)
+            row.update(
+                {
+                    "phase": label,
+                    "phase_model_id": model_id,
+                    "pp_tokens": actual_pp_tokens,
+                    "tg": tg,
+                    "repeat_index": r,
+                }
+            )
+            runs.append(row)
+            rows.append(row)
+
+        if runs:
+            prompt_tps = mean(x["stats"]["prompt_tps"] for x in runs)
+            gen_tps = mean(x["stats"]["generation_tps"] for x in runs)
+            ptok = mean(x["stats"]["prompt_tokens"] for x in runs)
+            gtok = mean(x["stats"]["generation_tokens"] for x in runs)
+            peak = mean(x["stats"]["peak_memory_usage"]["inBytes"] for x in runs)
+            avg_elapsed = mean(x["elapsed_s"] for x in runs)
+            logger.info(
+                f"[{label}] prompt_tps={prompt_tps:.2f} gen_tps={gen_tps:.2f}    "
+                f"prompt_tokens={ptok} gen_tokens={gtok}    "
+                f"peak_memory={format_peak_memory(peak)}    "
+                f"avg_elapsed={avg_elapsed:.2f}s"
+            )
+        time.sleep(2)
+    return rows
+
+
+def _summarise(rows: list[dict[str, Any]]) -> dict[tuple[int, int], dict[str, float]]:
+    grouped: dict[tuple[int, int], list[dict[str, Any]]] = {}
+    for r in rows:
+        key = (int(r["pp_tokens"]), int(r["tg"]))
+        grouped.setdefault(key, []).append(r)
+    out: dict[tuple[int, int], dict[str, float]] = {}
+    for key, runs in grouped.items():
+        out[key] = {
+            "prompt_tps": mean(x["stats"]["prompt_tps"] for x in runs),
+            "gen_tps": mean(x["stats"]["generation_tps"] for x in runs),
+            "elapsed_s": mean(x["elapsed_s"] for x in runs),
+        }
+    return out
+
+
+def _print_diff(
+    disagg_rows: list[dict[str, Any]],
+    decode_alone_rows: list[dict[str, Any]],
+    prefill_alone_rows: list[dict[str, Any]],
+) -> None:
+    disagg = _summarise(disagg_rows)
+    decode_alone = _summarise(decode_alone_rows)
+    prefill_alone = _summarise(prefill_alone_rows)
+    keys = set(disagg.keys()) | set(decode_alone.keys()) | set(prefill_alone.keys())
+
+    width = 64
+    for key in sorted(keys):
+        pp, tg = key
+        logger.info("─" * width)
+        logger.info(f"  pp={pp}  tg={tg}")
+        logger.info("─" * width)
+        logger.info(
+            f"  {'phase':<16} {'elapsed':>10}  {'prompt_tps':>11}  {'gen_tps':>9}"
+        )
+        for label, summary in (
+            ("disaggregated", disagg.get(key)),
+            ("decode_alone", decode_alone.get(key)),
+            ("prefill_alone", prefill_alone.get(key)),
+        ):
+            if summary is None:
+                logger.info(f"  {label:<16} {'—':>10}  {'—':>11}  {'—':>9}")
+                continue
+            logger.info(
+                f"  {label:<16} "
+                f"{summary['elapsed_s']:>9.2f}s  "
+                f"{summary['prompt_tps']:>11.1f}  "
+                f"{summary['gen_tps']:>9.2f}"
+            )
+
+        d = disagg.get(key)
+        da = decode_alone.get(key)
+        pa = prefill_alone.get(key)
+        if d and da and d["elapsed_s"] > 0:
+            logger.info(
+                f"  speedup vs decode_alone:  {da['elapsed_s'] / d['elapsed_s']:.2f}x"
+            )
+        if d and pa and d["elapsed_s"] > 0:
+            logger.info(
+                f"  speedup vs prefill_alone: {pa['elapsed_s'] / d['elapsed_s']:.2f}x"
+            )
+    logger.info("─" * width)
+
+
+def main() -> int:
+    _inject_toml_into_argv()
+    ap = argparse.ArgumentParser(
+        prog="prefill-decode-bench",
+        description="Benchmark MLX-MLX disaggregated prefill/decode via instance links.",
+    )
+    add_common_instance_args(ap)
+    ap.add_argument(
+        "--pp",
+        nargs="+",
+        required=True,
+        help="Prompt-size hints (ints, must be >1000). Accepts commas.",
+    )
+    ap.add_argument(
+        "--tg",
+        nargs="+",
+        required=True,
+        help="Generation lengths (ints). Accepts commas.",
+    )
+    ap.add_argument(
+        "--repeat", type=int, default=1, help="Repetitions per (pp,tg) pair."
+    )
+    ap.add_argument(
+        "--warmup",
+        type=int,
+        default=0,
+        help="Warmup runs (uses first pp/tg).",
+    )
+    ap.add_argument(
+        "--json-out",
+        default="bench/prefill_decode_results.json",
+        help="Write raw per-run results JSON to this path.",
+    )
+    ap.add_argument("--stdout", action="store_true", help="Write results to stdout")
+    ap.add_argument(
+        "--dry-run", action="store_true", help="List selected placements and exit."
+    )
+    ap.add_argument(
+        "--all-combinations",
+        action="store_true",
+        help="Force all pp×tg combinations even when lists have equal length.",
+    )
+    ap.add_argument(
+        "--prefill-model",
+        default=None,
+        help="Model id for the prefill instance. Defaults to --model.",
+    )
+    ap.add_argument(
+        "--prefill-node",
+        default=None,
+        help="friendly_name of the node hosting the prefill instance.",
+    )
+    ap.add_argument(
+        "--decode-node",
+        default=None,
+        help="friendly_name of the node hosting the decode instance.",
+    )
+    ap.add_argument(
+        "--config",
+        default=None,
+        help="TOML config file. CLI flags override toml values.",
+    )
+    ap.add_argument(
+        "--compare-baseline",
+        action="store_true",
+        help="Also run each (pp,tg) pair without the prefill/decode link "
+        "(decode instance does its own prefill) and report the diff.",
+    )
+    args = ap.parse_args()
+    cfg = _load_toml(args.config) if args.config else {}
+    _merge_toml_into_args(args, cfg)
+    prefill_overrides = cfg.get("prefill", {}) if cfg else {}
+    decode_overrides = cfg.get("decode", {}) if cfg else {}
+    if args.prefill_model is None and "model" in prefill_overrides:
+        args.prefill_model = prefill_overrides["model"]
+    if args.prefill_node is None and "node" in prefill_overrides:
+        args.prefill_node = prefill_overrides["node"]
+    if args.decode_node is None and "node" in decode_overrides:
+        args.decode_node = decode_overrides["node"]
+    if "model" in decode_overrides and not args.model:
+        args.model = decode_overrides["model"]
+
+    pp_list = parse_int_list(args.pp)
+    tg_list = parse_int_list(args.tg)
+    if not pp_list or not tg_list:
+        logger.error("pp and tg lists must be non-empty")
+        return 2
+    for pp in pp_list:
+        if pp <= 1000:
+            logger.error(
+                f"pp={pp} must be >1000 (remote prefill triggers when uncached >1000)"
+            )
+            return 2
+    if args.repeat <= 0:
+        logger.error("--repeat must be >= 1")
+        return 2
+
+    use_combinations = args.all_combinations or len(pp_list) != len(tg_list)
+    if use_combinations:
+        logger.info(
+            f"pp/tg mode: combinations (product) — {len(pp_list) * len(tg_list)} pairs"
+        )
+    else:
+        logger.info(f"pp/tg mode: tandem (zip) — {len(pp_list)} pairs")
+
+    client = ExoClient(args.host, args.port, timeout_s=args.timeout)
+
+    decode_short_id, decode_full_id = resolve_model_short_id(
+        client, args.model, force_download=args.force_download
+    )
+    if args.prefill_model:
+        prefill_short_id, prefill_full_id = resolve_model_short_id(
+            client, args.prefill_model, force_download=args.force_download
+        )
+    else:
+        prefill_short_id, prefill_full_id = decode_short_id, decode_full_id
+
+    tokenizer = load_tokenizer_for_bench(decode_full_id)
+    if tokenizer is None:
+        raise RuntimeError("[prefill-decode-bench] decode tokenizer load failed")
+    try:
+        decode_prompt_sizer = PromptSizer(tokenizer)
+    except Exception:
+        logger.error("[prefill-decode-bench] decode prompt sizing failed")
+        raise
+
+    if prefill_full_id == decode_full_id:
+        prefill_prompt_sizer = decode_prompt_sizer
+    else:
+        prefill_tokenizer = load_tokenizer_for_bench(prefill_full_id)
+        if prefill_tokenizer is None:
+            raise RuntimeError("[prefill-decode-bench] prefill tokenizer load failed")
+        prefill_prompt_sizer = PromptSizer(prefill_tokenizer)
+
+    id_to_friendly = _node_id_to_friendly(client)
+
+    prefill_args = _side_args(args, prefill_overrides)
+    decode_args = _side_args(args, decode_overrides)
+
+    if prefill_full_id == decode_full_id and prefill_overrides == decode_overrides:
+        placements = settle_and_fetch_placements(
+            client, decode_full_id, args, settle_timeout=args.settle_timeout
+        )
+        prefill_candidates = (
+            _filter_by_node(placements, args.prefill_node, id_to_friendly)
+            if args.prefill_node
+            else placements
+        )
+        decode_candidates = (
+            _filter_by_node(placements, args.decode_node, id_to_friendly)
+            if args.decode_node
+            else placements
+        )
+        if args.prefill_node and not prefill_candidates:
+            logger.error(f"No placement on prefill node {args.prefill_node!r}.")
+            return 1
+        if args.decode_node and not decode_candidates:
+            logger.error(f"No placement on decode node {args.decode_node!r}.")
+            return 1
+        if args.prefill_node and args.decode_node:
+            prefill_p = prefill_candidates[0]
+            decode_p = decode_candidates[0]
+        else:
+            pair = _pick_two_distinct_placements(placements)
+            if pair is None:
+                logger.error(
+                    "Need at least two distinct-node MLX placements for the same model."
+                )
+                return 1
+            prefill_p, decode_p = pair
+            if args.prefill_node:
+                prefill_p = prefill_candidates[0]
+            if args.decode_node:
+                decode_p = decode_candidates[0]
+    else:
+        prefill_node_id = (
+            _node_id_by_friendly(id_to_friendly, args.prefill_node)
+            if args.prefill_node
+            else None
+        )
+        decode_node_id = (
+            _node_id_by_friendly(id_to_friendly, args.decode_node)
+            if args.decode_node
+            else None
+        )
+        if args.prefill_node and prefill_node_id is None:
+            logger.error(f"Unknown node {args.prefill_node!r}.")
+            return 1
+        if args.decode_node and decode_node_id is None:
+            logger.error(f"Unknown node {args.decode_node!r}.")
+            return 1
+        prefill_placements = settle_and_fetch_placements(
+            client,
+            prefill_full_id,
+            prefill_args,
+            settle_timeout=args.settle_timeout,
+            node_id=prefill_node_id,
+        )
+        decode_placements = settle_and_fetch_placements(
+            client,
+            decode_full_id,
+            decode_args,
+            settle_timeout=args.settle_timeout,
+            node_id=decode_node_id,
+        )
+        if not prefill_placements:
+            logger.error(
+                f"No placement found for prefill model {prefill_full_id}"
+                f"{f' on node {args.prefill_node!r}' if args.prefill_node else ''}."
+            )
+            return 1
+        if not decode_placements:
+            logger.error(
+                f"No placement found for decode model {decode_full_id}"
+                f"{f' on node {args.decode_node!r}' if args.decode_node else ''}."
+            )
+            return 1
+        prefill_p = prefill_placements[0]
+        decode_p = decode_placements[0]
+
+    prefill_node_names = _placement_node_friendly_names(prefill_p, id_to_friendly)
+    decode_node_names = _placement_node_friendly_names(decode_p, id_to_friendly)
+    _ = unwrap_instance
+
+    prefill_instance = prefill_p["instance"]
+    decode_instance = decode_p["instance"]
+    prefill_id = instance_id_from_instance(prefill_instance)
+    decode_id = instance_id_from_instance(decode_instance)
+    prefill_meta = str(prefill_p.get("instance_meta", ""))
+    decode_meta = str(decode_p.get("instance_meta", ""))
+    prefill_nodes = nodes_used_in_instance(prefill_instance)
+    decode_nodes = nodes_used_in_instance(decode_instance)
+
+    logger.info("=" * 80)
+    logger.info(
+        f"PREFILL: {prefill_meta} / nodes={prefill_nodes} ({','.join(prefill_node_names)}) "
+        f"/ {prefill_short_id} ({prefill_full_id}) / instance_id={prefill_id}"
+    )
+    logger.info(
+        f"DECODE:  {decode_meta} / nodes={decode_nodes} ({','.join(decode_node_names)}) "
+        f"/ {decode_short_id} ({decode_full_id}) / instance_id={decode_id}"
+    )
+
+    if args.dry_run:
+        return 0
+
+    settle_deadline = (
+        time.monotonic() + args.settle_timeout if args.settle_timeout > 0 else None
+    )
+
+    logger.info("Planning phase: prefill...")
+    run_planning_phase(
+        client,
+        prefill_full_id,
+        prefill_p,
+        args.danger_delete_downloads,
+        args.timeout,
+        settle_deadline,
+    )
+    logger.info("Planning phase: decode...")
+    run_planning_phase(
+        client,
+        decode_full_id,
+        decode_p,
+        args.danger_delete_downloads,
+        args.timeout,
+        settle_deadline,
+    )
+
+    if use_combinations:
+        pp_tg_pairs = list(itertools.product(pp_list, tg_list))
+    else:
+        pp_tg_pairs = list(zip(pp_list, tg_list, strict=True))
+
+    common_meta = {
+        "decode_model_short_id": decode_short_id,
+        "decode_model_id": decode_full_id,
+        "prefill_model_short_id": prefill_short_id,
+        "prefill_model_id": prefill_full_id,
+        "prefill_instance_id": prefill_id,
+        "prefill_instance_meta": prefill_meta,
+        "prefill_nodes": prefill_nodes,
+        "decode_instance_id": decode_id,
+        "decode_instance_meta": decode_meta,
+        "decode_nodes": decode_nodes,
+    }
+
+    all_rows: list[dict[str, Any]] = []
+    disagg_rows: list[dict[str, Any]] = []
+    decode_alone_rows: list[dict[str, Any]] = []
+    prefill_alone_rows: list[dict[str, Any]] = []
+    link_id = ""
+    prefill_alive = False
+    decode_alive = False
+    try:
+        logger.info("Creating prefill instance...")
+        client.request_json("POST", "/instance", body={"instance": prefill_instance})
+        wait_for_instance_ready(client, prefill_id)
+        prefill_alive = True
+        logger.info("Prefill instance ready")
+
+        if args.compare_baseline:
+            time.sleep(2)
+            prefill_alone_rows = _run_phase(
+                client=client,
+                label="prefill_alone",
+                pp_tg_pairs=pp_tg_pairs,
+                model_id=prefill_full_id,
+                prompt_sizer=prefill_prompt_sizer,
+                warmup=args.warmup,
+                repeat=args.repeat,
+                common_meta=common_meta,
+            )
+            all_rows.extend(prefill_alone_rows)
+
+        logger.info("Creating decode instance...")
+        client.request_json("POST", "/instance", body={"instance": decode_instance})
+        wait_for_instance_ready(client, decode_id)
+        decode_alive = True
+        logger.info("Decode instance ready")
+
+        logger.info("Linking instances (prefill → decode)...")
+        _create_instance_link(client, prefill_id, decode_id)
+        time.sleep(1)
+        links = _list_instance_links(client)
+        if not links:
+            logger.error("Link did not appear in state.")
+            return 1
+        link_id = str(links[-1].get("linkId") or links[-1].get("link_id") or "")
+        logger.info(f"Link created: {link_id}")
+        time.sleep(2)
+
+        disagg_rows = _run_phase(
+            client=client,
+            label="disaggregated",
+            pp_tg_pairs=pp_tg_pairs,
+            model_id=decode_full_id,
+            prompt_sizer=decode_prompt_sizer,
+            warmup=args.warmup,
+            repeat=args.repeat,
+            common_meta=common_meta,
+        )
+        all_rows.extend(disagg_rows)
+
+        if args.compare_baseline:
+            logger.info("Removing link and prefill instance to isolate decode_alone.")
+            with contextlib.suppress(ExoHttpError):
+                if link_id:
+                    _delete_instance_link(client, link_id)
+                    link_id = ""
+            with contextlib.suppress(ExoHttpError):
+                client.request_json("DELETE", f"/instance/{prefill_id}")
+            wait_for_instance_gone(client, prefill_id)
+            prefill_alive = False
+            time.sleep(2)
+
+            decode_alone_rows = _run_phase(
+                client=client,
+                label="decode_alone",
+                pp_tg_pairs=pp_tg_pairs,
+                model_id=decode_full_id,
+                prompt_sizer=decode_prompt_sizer,
+                warmup=args.warmup,
+                repeat=args.repeat,
+                common_meta=common_meta,
+            )
+            all_rows.extend(decode_alone_rows)
+
+            _print_diff(disagg_rows, decode_alone_rows, prefill_alone_rows)
+    finally:
+        with contextlib.suppress(ExoHttpError):
+            if link_id:
+                _delete_instance_link(client, link_id)
+        if decode_alive:
+            with contextlib.suppress(ExoHttpError):
+                client.request_json("DELETE", f"/instance/{decode_id}")
+            wait_for_instance_gone(client, decode_id)
+        if prefill_alive:
+            with contextlib.suppress(ExoHttpError):
+                client.request_json("DELETE", f"/instance/{prefill_id}")
+            wait_for_instance_gone(client, prefill_id)
+        logger.debug("Deleted both instances")
+
+    if args.stdout:
+        json.dump(all_rows, sys.stdout, indent=2, ensure_ascii=False)
+    elif args.json_out:
+        with open(args.json_out, "w", encoding="utf-8") as f:
+            json.dump(all_rows, f, indent=2, ensure_ascii=False)
+        logger.debug(f"\nWrote results JSON: {args.json_out}")
+
+    return 0
+
+
+if __name__ == "__main__":
+    sys.exit(main())

dashboard/src/lib/components/HeaderNav.svelte

@@ -1,5 +1,8 @@
 <script lang="ts">
   import { browser } from "$app/environment";
+  import { featureFlags } from "$lib/stores/app.svelte";
+
+  const showAdvanced = $derived(featureFlags()["disaggregation"] === true);
 
   interface Props {
     showHome?: boolean;
@@ -297,5 +300,28 @@
       </svg>
       <span class="hidden sm:inline">Integrations</span>
     </a>
+    {#if showAdvanced}
+      <a
+        href="/#/advanced"
+        class="text-xs md:text-sm text-white/70 hover:text-exo-yellow transition-colors tracking-wider uppercase flex items-center gap-1.5 md:gap-2 cursor-pointer"
+        title="Advanced cluster settings"
+      >
+        <svg
+          class="w-4 h-4"
+          viewBox="0 0 24 24"
+          fill="none"
+          stroke="currentColor"
+          stroke-width="2"
+          stroke-linecap="round"
+          stroke-linejoin="round"
+        >
+          <circle cx="12" cy="12" r="3" />
+          <path
+            d="M19.4 15a1.65 1.65 0 0 0 .33 1.82l.06.06a2 2 0 0 1 0 2.83 2 2 0 0 1-2.83 0l-.06-.06a1.65 1.65 0 0 0-1.82-.33 1.65 1.65 0 0 0-1 1.51V21a2 2 0 0 1-4 0v-.09A1.65 1.65 0 0 0 9 19.4a1.65 1.65 0 0 0-1.82.33l-.06.06a2 2 0 0 1-2.83 0 2 2 0 0 1 0-2.83l.06-.06a1.65 1.65 0 0 0 .33-1.82 1.65 1.65 0 0 0-1.51-1H3a2 2 0 0 1 0-4h.09A1.65 1.65 0 0 0 4.6 9a1.65 1.65 0 0 0-.33-1.82l-.06-.06a2 2 0 0 1 0-2.83 2 2 0 0 1 2.83 0l.06.06a1.65 1.65 0 0 0 1.82.33H9a1.65 1.65 0 0 0 1-1.51V3a2 2 0 0 1 4 0v.09a1.65 1.65 0 0 0 1 1.51 1.65 1.65 0 0 0 1.82-.33l.06-.06a2 2 0 0 1 2.83 0 2 2 0 0 1 0 2.83l-.06.06a1.65 1.65 0 0 0-.33 1.82V9a1.65 1.65 0 0 0 1.51 1H21a2 2 0 0 1 0 4h-.09a1.65 1.65 0 0 0-1.51 1z"
+          />
+        </svg>
+        <span class="hidden sm:inline">Advanced</span>
+      </a>
+    {/if}
   </nav>
 </header>

dashboard/src/lib/components/PrefillDecodeDisaggregation.svelte

@@ -0,0 +1,565 @@
+<script lang="ts">
+  import { onMount, onDestroy } from "svelte";
+  import FamilyLogos from "$lib/components/FamilyLogos.svelte";
+  import {
+    instances,
+    instanceLinks,
+    nodeIdentities,
+    refreshState,
+    createInstanceLink,
+    updateInstanceLink,
+    deleteInstanceLink,
+    type Instance,
+  } from "$lib/stores/app.svelte";
+  import { deriveBaseModel, deriveFamily } from "$lib/utils/model_family";
+
+  type InstanceWrapper = {
+    MlxRingInstance?: Instance;
+    MlxJacclInstance?: Instance;
+    VllmInstance?: Instance;
+  };
+
+  let interval: ReturnType<typeof setInterval> | null = null;
+
+  onMount(() => {
+    refreshState();
+    interval = setInterval(refreshState, 3000);
+  });
+  onDestroy(() => {
+    if (interval) clearInterval(interval);
+  });
+
+  type InstanceRow = {
+    id: string;
+    modelId: string;
+    family: string;
+    baseModel: string;
+    nodeNames: string[];
+    nodeCount: number;
+  };
+
+  const instanceRows = $derived.by<InstanceRow[]>(() => {
+    const rows: InstanceRow[] = [];
+    const ids = nodeIdentities();
+    for (const [id, raw] of Object.entries(instances())) {
+      const wrapper = raw as InstanceWrapper;
+      const inst =
+        wrapper.MlxRingInstance ??
+        wrapper.MlxJacclInstance ??
+        wrapper.VllmInstance;
+      const modelId = inst?.shardAssignments?.modelId ?? "";
+      const nodeToRunner = inst?.shardAssignments?.nodeToRunner ?? {};
+      const nodeIds = Object.keys(nodeToRunner);
+      const nodeNames = nodeIds
+        .map((nodeId) => ids[nodeId]?.friendlyName ?? nodeId.slice(0, 6))
+        .filter((name) => !!name);
+      rows.push({
+        id,
+        modelId,
+        family: deriveFamily(modelId),
+        baseModel: deriveBaseModel(modelId),
+        nodeNames,
+        nodeCount: nodeIds.length,
+      });
+    }
+    rows.sort((a, b) => a.modelId.localeCompare(b.modelId));
+    return rows;
+  });
+
+  const instanceById = $derived(
+    Object.fromEntries(instanceRows.map((r) => [r.id, r])),
+  );
+
+  type LinkRow = {
+    linkId: string;
+    prefill: string[];
+    decode: string[];
+    families: string[];
+    multiNode: boolean;
+  };
+
+  const linkRows = $derived.by<LinkRow[]>(() => {
+    const rows: LinkRow[] = [];
+    for (const [, link] of Object.entries(instanceLinks())) {
+      const fams = new Set<string>();
+      let multiNode = false;
+      for (const id of [...link.prefillInstances, ...link.decodeInstances]) {
+        const r = instanceById[id];
+        if (r && r.baseModel) fams.add(r.baseModel.toLowerCase());
+        if (r && r.nodeCount > 1) multiNode = true;
+      }
+      rows.push({
+        linkId: link.linkId,
+        prefill: link.prefillInstances,
+        decode: link.decodeInstances,
+        families: Array.from(fams),
+        multiNode,
+      });
+    }
+    return rows;
+  });
+
+  let editingLinkId = $state<string | null>(null);
+  let editingPrefill = $state<Set<string>>(new Set());
+  let editingDecode = $state<Set<string>>(new Set());
+  let saving = $state(false);
+  let errorMessage = $state<string | null>(null);
+
+  function startCreate() {
+    editingLinkId = "new";
+    editingPrefill = new Set();
+    editingDecode = new Set();
+    errorMessage = null;
+  }
+
+  function startEdit(row: LinkRow) {
+    editingLinkId = row.linkId;
+    editingPrefill = new Set(row.prefill);
+    editingDecode = new Set(row.decode);
+    errorMessage = null;
+  }
+
+  function cancelEdit() {
+    editingLinkId = null;
+    editingPrefill = new Set();
+    editingDecode = new Set();
+    errorMessage = null;
+  }
+
+  type Role = "prefill" | "decode" | "none";
+
+  function roleOf(id: string): Role {
+    if (editingPrefill.has(id)) return "prefill";
+    if (editingDecode.has(id)) return "decode";
+    return "none";
+  }
+
+  function setRole(id: string, role: Role) {
+    const p = new Set(editingPrefill);
+    const d = new Set(editingDecode);
+    p.delete(id);
+    d.delete(id);
+    if (role === "prefill") p.add(id);
+    if (role === "decode") d.add(id);
+    editingPrefill = p;
+    editingDecode = d;
+  }
+
+  const editingFamilies = $derived.by<string[]>(() => {
+    const fams = new Set<string>();
+    for (const id of [...editingPrefill, ...editingDecode]) {
+      const r = instanceById[id];
+      if (r && r.baseModel) fams.add(r.baseModel.toLowerCase());
+    }
+    return Array.from(fams);
+  });
+
+  const editingMultiNode = $derived.by<string[]>(() => {
+    const names: string[] = [];
+    for (const id of [...editingPrefill, ...editingDecode]) {
+      const r = instanceById[id];
+      if (r && r.nodeCount > 1) {
+        names.push(r.baseModel || r.modelId);
+      }
+    }
+    return names;
+  });
+
+  const editingMismatch = $derived(editingFamilies.length > 1);
+  const canSave = $derived(
+    editingLinkId !== null &&
+      editingPrefill.size > 0 &&
+      editingDecode.size > 0 &&
+      !saving,
+  );
+
+  async function save() {
+    if (editingLinkId === null) return;
+    saving = true;
+    errorMessage = null;
+    try {
+      const prefill = Array.from(editingPrefill);
+      const decode = Array.from(editingDecode);
+      if (editingLinkId === "new") {
+        await createInstanceLink(prefill, decode);
+      } else {
+        await updateInstanceLink(editingLinkId, prefill, decode);
+      }
+      cancelEdit();
+      await refreshState();
+    } catch (err) {
+      errorMessage = err instanceof Error ? err.message : String(err);
+    } finally {
+      saving = false;
+    }
+  }
+
+  async function remove(linkId: string) {
+    if (!confirm("Remove this routing?")) return;
+    try {
+      await deleteInstanceLink(linkId);
+      if (editingLinkId === linkId) cancelEdit();
+      await refreshState();
+    } catch (err) {
+      errorMessage = err instanceof Error ? err.message : String(err);
+    }
+  }
+</script>
+
+<div class="font-mono text-foreground">
+  <div class="mb-6 space-y-4">
+    <details open class="group [&_summary::-webkit-details-marker]:hidden">
+      <summary
+        class="cursor-pointer list-none text-exo-yellow text-xs font-mono tracking-widest uppercase flex items-center gap-2 hover:opacity-80 transition-opacity"
+      >
+        <span
+          class="inline-block transition-transform group-open:rotate-90 text-exo-light-gray"
+          >▶</span
+        >
+        Prefill vs Decode
+      </summary>
+      <div class="mt-2 text-white/80 text-sm leading-relaxed">
+        Prefill is the compute-heavy pass that consumes the entire prompt and
+        builds a KV cache. Decode is the memory-bandwidth-bound loop that emits
+        tokens sequentially from that cache. The two phases have very different
+        bottlenecks, so running them on different hardware can be substantially
+        faster than doing both on one node.
+      </div>
+    </details>
+    <details class="group [&_summary::-webkit-details-marker]:hidden">
+      <summary
+        class="cursor-pointer list-none text-exo-yellow text-xs font-mono tracking-widest uppercase flex items-center gap-2 hover:opacity-80 transition-opacity"
+      >
+        <span
+          class="inline-block transition-transform group-open:rotate-90 text-exo-light-gray"
+          >▶</span
+        >
+        Linking Instances
+      </summary>
+      <div class="mt-2 text-white/80 text-sm leading-relaxed space-y-2">
+        <p>
+          A linked route here tells the cluster: when a request is sent to a
+          model in that cluster, the decode node (or the least active one if
+          there are multiple) will handle it. If it decides it must do a lot of
+          prefill not already cached in the prefix cache, it routes the request
+          to the prefill node over TCP IP. The prefill node streams the KV cache
+          back to the decode node which picks up from there.
+        </p>
+        <p>
+          Linked instances must be running the same model family — KV layouts
+          differ across architectures. More on the <a
+            class="text-exo-yellow underline underline-offset-2 hover:text-exo-yellow-darker transition-colors"
+            href="https://blog.exolabs.net/nvidia-dgx-spark/"
+            target="_blank"
+            rel="noreferrer noopener">blog</a
+          >.
+        </p>
+      </div>
+    </details>
+  </div>
+
+  {#if errorMessage}
+    <div
+      class="mb-4 px-4 py-3 bg-red-500/10 border border-red-500/40 text-red-300 text-sm"
+    >
+      {errorMessage}
+    </div>
+  {/if}
+
+  <section class="mt-12">
+    <h2
+      class="text-exo-yellow text-xs font-mono tracking-widest uppercase m-0 mb-3"
+    >
+      Existing routes
+    </h2>
+
+    {#if linkRows.length === 0}
+      {#if editingLinkId === null}
+        <div class="flex items-center justify-between">
+          <p class="text-exo-light-gray italic text-sm m-0">
+            No routes yet. Create one to enable remote prefill.
+          </p>
+          <button
+            class="px-3 py-1.5 text-xs font-mono tracking-wider uppercase bg-exo-yellow/15 border border-exo-yellow/50 text-exo-yellow hover:bg-exo-yellow/25 hover:border-exo-yellow/80 transition-colors"
+            onclick={startCreate}
+          >
+            + New route
+          </button>
+        </div>
+      {/if}
+    {:else}
+      {#if editingLinkId === null}
+        <div class="flex justify-end mb-3">
+          <button
+            class="px-3 py-1.5 text-xs font-mono tracking-wider uppercase bg-exo-yellow/15 border border-exo-yellow/50 text-exo-yellow hover:bg-exo-yellow/25 hover:border-exo-yellow/80 transition-colors"
+            onclick={startCreate}
+          >
+            + New route
+          </button>
+        </div>
+      {/if}
+      <div
+        class="bg-exo-dark-gray/60 border border-exo-medium-gray/40 flex flex-col"
+      >
+        {#each linkRows as row (row.linkId)}
+          {#if editingLinkId !== row.linkId}
+            <article
+              class="p-4 border-b border-exo-light-gray/25 last:border-b-0"
+            >
+              {#if row.multiNode}
+                <div
+                  class="mb-3 px-3 py-2 bg-red-500/10 border border-red-500/40 text-red-300 text-xs tracking-wide"
+                >
+                  ⚠ Multi-node instance detected. Remote prefill currently only
+                  works on single-node (rank-0) instances. This route will not
+                  function until that's supported.
+                </div>
+              {/if}
+              {#if row.families.length > 1}
+                <div
+                  class="mb-3 px-3 py-2 bg-amber-500/10 border border-amber-500/40 text-amber-300 text-xs tracking-wide"
+                >
+                  ⚠ Mixed model families: {row.families.join(", ")}
+                </div>
+              {/if}
+              <div
+                class="grid grid-cols-[1fr_auto_1fr_auto] items-center gap-x-3 gap-y-2"
+              >
+                <span
+                  class="inline-block justify-self-start text-[10px] font-mono tracking-widest uppercase px-2 py-0.5 bg-exo-yellow/15 border border-exo-yellow/40 text-exo-yellow"
+                  >Prefill</span
+                >
+                <span></span>
+                <span
+                  class="inline-block justify-self-start text-[10px] font-mono tracking-widest uppercase px-2 py-0.5 bg-exo-medium-gray/40 border border-exo-medium-gray/60 text-foreground"
+                  >Decode</span
+                >
+                <span></span>
+                <div class="min-w-0">
+                  <ul class="list-none p-0 m-0 flex flex-col gap-2">
+                    {#each row.prefill as id (id)}
+                      {@const r = instanceById[id]}
+                      {#if r}
+                        <li
+                          class="flex items-center gap-2 px-2.5 py-2 bg-exo-medium-gray/20 border border-exo-medium-gray/40"
+                        >
+                          <FamilyLogos family={r.family} />
+                          <div class="min-w-0 flex-1">
+                            <div
+                              class="text-exo-yellow text-xs font-mono truncate"
+                            >
+                              {r.baseModel || r.modelId}
+                            </div>
+                            <div
+                              class="text-exo-light-gray text-[11px] truncate"
+                            >
+                              {r.nodeNames.join(", ") || "?"}{r.nodeCount > 1
+                                ? ` (${r.nodeCount} nodes)`
+                                : ""}
+                            </div>
+                            <div
+                              class="text-exo-light-gray/40 text-[10px] font-mono truncate"
+                              title={r.id}
+                            >
+                              {r.id.slice(0, 8)}
+                            </div>
+                          </div>
+                        </li>
+                      {/if}
+                    {/each}
+                  </ul>
+                </div>
+                <div class="text-exo-yellow/60 text-xl px-2" aria-hidden="true">
+                  →
+                </div>
+                <div class="min-w-0">
+                  <ul class="list-none p-0 m-0 flex flex-col gap-2">
+                    {#each row.decode as id (id)}
+                      {@const r = instanceById[id]}
+                      {#if r}
+                        <li
+                          class="flex items-center gap-2 px-2.5 py-2 bg-exo-medium-gray/20 border border-exo-medium-gray/40"
+                        >
+                          <FamilyLogos family={r.family} />
+                          <div class="min-w-0 flex-1">
+                            <div
+                              class="text-exo-yellow text-xs font-mono truncate"
+                            >
+                              {r.baseModel || r.modelId}
+                            </div>
+                            <div
+                              class="text-exo-light-gray text-[11px] truncate"
+                            >
+                              {r.nodeNames.join(", ") || "?"}{r.nodeCount > 1
+                                ? ` (${r.nodeCount} nodes)`
+                                : ""}
+                            </div>
+                            <div
+                              class="text-exo-light-gray/40 text-[10px] font-mono truncate"
+                              title={r.id}
+                            >
+                              {r.id.slice(0, 8)}
+                            </div>
+                          </div>
+                        </li>
+                      {/if}
+                    {/each}
+                  </ul>
+                </div>
+                <div class="flex gap-2 pl-3">
+                  <button
+                    class="px-2 py-0.5 text-[11px] font-mono tracking-wider uppercase bg-exo-medium-gray/30 border border-exo-medium-gray/60 rounded text-foreground hover:border-exo-yellow/60 hover:text-exo-yellow disabled:opacity-40 disabled:cursor-not-allowed transition-colors"
+                    onclick={() => startEdit(row)}
+                    disabled={editingLinkId !== null}
+                  >
+                    Edit
+                  </button>
+                  <button
+                    class="px-2 py-0.5 text-[11px] font-mono tracking-wider uppercase bg-red-500/15 border border-red-500/40 rounded text-red-300 hover:bg-red-500/25 transition-colors"
+                    onclick={() => remove(row.linkId)}
+                  >
+                    Remove
+                  </button>
+                </div>
+              </div>
+            </article>
+          {/if}
+        {/each}
+      </div>
+    {/if}
+  </section>
+
+  {#if editingLinkId !== null && instanceRows.length === 0}
+    <section
+      class="mt-6 bg-exo-dark-gray/60 border border-exo-yellow/30 px-4 py-2.5 flex items-center justify-between gap-3"
+    >
+      <span class="text-exo-light-gray italic text-sm font-mono"
+        >No instances available.</span
+      >
+      <button
+        class="px-3 py-1 text-xs font-mono tracking-wider uppercase bg-exo-medium-gray/30 border border-exo-medium-gray/60 rounded text-foreground hover:border-exo-yellow/60 transition-colors"
+        onclick={cancelEdit}
+      >
+        Cancel
+      </button>
+    </section>
+  {:else if editingLinkId !== null}
+    <section class="mt-6 bg-exo-dark-gray/60 border border-exo-yellow/30 p-5">
+      <h2
+        class="text-exo-yellow text-xs font-mono tracking-widest uppercase m-0 mb-3"
+      >
+        {editingLinkId === "new" ? "New route" : "Edit route"}
+      </h2>
+
+      {#if editingMismatch}
+        <div
+          class="mb-3 px-3 py-2 bg-amber-500/10 border border-amber-500/40 text-amber-300 text-xs tracking-wide"
+        >
+          ⚠ Selected instances span multiple model families: <strong
+            >{editingFamilies.join(", ")}</strong
+          >. Linking across families produces a corrupt KV cache.
+        </div>
+      {/if}
+
+      {#if editingMultiNode.length > 0}
+        <div
+          class="mb-3 px-3 py-2 bg-red-500/10 border border-red-500/40 text-red-300 text-xs tracking-wide"
+        >
+          ⚠ Multi-node instance(s) selected: <strong
+            >{editingMultiNode.join(", ")}</strong
+          >. Remote prefill currently only works on single-node instances. This
+          route will not function until multi-node support lands.
+        </div>
+      {/if}
+
+      <p class="text-exo-light-gray text-xs mb-4">
+        Pick a role for each instance:
+        <span class="text-exo-yellow">Prefill</span>
+        serves KV cache,
+        <span class="text-foreground">Decode</span> consumes it.
+      </p>
+      <div
+        class="grid gap-2.5"
+        style="grid-template-columns: repeat(auto-fill, minmax(360px, 1fr));"
+      >
+        {#each instanceRows as row (row.id)}
+          {@const role = roleOf(row.id)}
+          <div
+            class="border p-3 flex flex-col gap-2.5 transition-colors {role ===
+            'prefill'
+              ? 'border-exo-yellow/60 bg-exo-dark-gray/60'
+              : role === 'decode'
+                ? 'border-exo-light-gray/60 bg-exo-dark-gray/60'
+                : 'border-exo-medium-gray/40 bg-exo-dark-gray/40'}"
+          >
+            <div class="flex items-center gap-2">
+              <FamilyLogos family={row.family} />
+              <div class="min-w-0 flex-1">
+                <div class="text-exo-yellow text-xs font-mono truncate">
+                  {row.baseModel || row.modelId}
+                </div>
+                <div class="text-exo-light-gray text-[11px] truncate">
+                  {row.nodeNames.join(", ") || "?"}{row.nodeCount > 1
+                    ? ` (${row.nodeCount} nodes)`
+                    : ""}
+                </div>
+                <div
+                  class="text-exo-light-gray/40 text-[10px] font-mono truncate"
+                  title={row.id}
+                >
+                  {row.id.slice(0, 8)}
+                </div>
+              </div>
+              {#if row.nodeCount > 1}
+                <span
+                  class="text-[9px] font-mono tracking-widest uppercase px-1.5 py-0.5 bg-red-500/15 border border-red-500/40 text-red-300"
+                  title="Multi-node instances are not supported by remote prefill yet."
+                  >Unsupported</span
+                >
+              {/if}
+            </div>
+            <div
+              class="flex rounded-md overflow-hidden border border-exo-light-gray/40 divide-x divide-exo-light-gray/40"
+            >
+              <button
+                class="flex-1 px-2 py-1 text-[11px] font-mono tracking-wider uppercase transition-colors {role ===
+                'prefill'
+                  ? 'bg-exo-yellow/20 text-exo-yellow'
+                  : 'bg-transparent text-white/80 hover:text-exo-yellow'}"
+                onclick={() =>
+                  setRole(row.id, role === "prefill" ? "none" : "prefill")}
+                >Prefill</button
+              >
+              <button
+                class="flex-1 px-2 py-1 text-[11px] font-mono tracking-wider uppercase transition-colors {role ===
+                'decode'
+                  ? 'bg-exo-medium-gray/50 text-foreground'
+                  : 'bg-transparent text-white/80 hover:text-foreground'}"
+                onclick={() =>
+                  setRole(row.id, role === "decode" ? "none" : "decode")}
+                >Decode</button
+              >
+            </div>
+          </div>
+        {/each}
+      </div>
+
+      <div class="flex gap-2 mt-5 justify-end">
+        <button
+          class="px-3 py-1.5 text-xs font-mono tracking-wider uppercase bg-exo-yellow/15 border border-exo-yellow/50 text-exo-yellow hover:bg-exo-yellow/25 hover:border-exo-yellow/80 disabled:opacity-40 disabled:cursor-not-allowed transition-colors"
+          onclick={save}
+          disabled={!canSave}
+        >
+          {saving ? "Saving..." : "Save route"}
+        </button>
+        <button
+          class="px-3 py-1.5 text-xs font-mono tracking-wider uppercase bg-exo-medium-gray/30 border border-exo-medium-gray/60 text-foreground hover:border-exo-yellow/60 disabled:opacity-40 disabled:cursor-not-allowed transition-colors"
+          onclick={cancelEdit}
+          disabled={saving}
+        >
+          Cancel
+        </button>
+      </div>
+    </section>
+  {/if}
+</div>

dashboard/src/lib/stores/app.svelte.ts

@@ -74,6 +74,12 @@ export interface Instance {
   };
 }
 
+export interface RawInstanceLink {
+  linkId: string;
+  prefillInstances: string[];
+  decodeInstances: string[];
+}
+
 // Granular node state types from the new state structure
 interface RawNodeIdentity {
   modelId?: string;
@@ -223,6 +229,7 @@ interface RawStateResponse {
     }
   >;
   runners?: Record<string, unknown>;
+  instanceLinks?: Record<string, RawInstanceLink>;
   downloads?: Record<string, unknown[]>;
   // New granular node state fields
   nodeIdentities?: Record<string, RawNodeIdentity>;
@@ -541,6 +548,8 @@ class AppStore {
   topologyData = $state<TopologyData | null>(null);
   instances = $state<Record<string, unknown>>({});
   runners = $state<Record<string, unknown>>({});
+  instanceLinks = $state<Record<string, RawInstanceLink>>({});
+  featureFlags = $state<Record<string, boolean>>({});
   downloads = $state<Record<string, unknown[]>>({});
   nodeDisk = $state<
     Record<
@@ -1274,6 +1283,7 @@ class AppStore {
 
   startPolling() {
     this.fetchState();
+    this.fetchFeatureFlags();
     this.fetchInterval = setInterval(() => this.fetchState(), 1000);
   }
 
@@ -1285,6 +1295,16 @@ class AppStore {
     this.stopPreviewsPolling();
   }
 
+  async fetchFeatureFlags() {
+    try {
+      const response = await fetch("/v1/feature-flags");
+      if (!response.ok) return;
+      this.featureFlags = await response.json();
+    } catch {
+      // Silently ignore — defaults to all-disabled.
+    }
+  }
+
   async fetchState() {
     try {
       const response = await fetch("/state");
@@ -1310,6 +1330,11 @@ class AppStore {
       if (data.runners) {
         this.runners = data.runners;
       }
+      if (data.instanceLinks) {
+        this.instanceLinks = data.instanceLinks;
+      } else {
+        this.instanceLinks = {};
+      }
       if (data.downloads) {
         this.downloads = data.downloads;
       }
@@ -1670,7 +1695,15 @@ class AppStore {
               }
             }
           }
-          return { role: m.role, content: msgContent };
+          const out: {
+            role: string;
+            content: string;
+            reasoning_content?: string;
+          } = { role: m.role, content: msgContent };
+          if (m.role === "assistant" && m.thinking) {
+            out.reasoning_content = m.thinking;
+          }
+          return out;
         }),
       ];
 
@@ -1877,7 +1910,15 @@ class AppStore {
       const apiMessages = [
         systemPrompt,
         ...targetConversation.messages.slice(0, -1).map((m) => {
-          return { role: m.role, content: m.content };
+          const out: {
+            role: string;
+            content: string;
+            reasoning_content?: string;
+          } = { role: m.role, content: m.content };
+          if (m.role === "assistant" && m.thinking) {
+            out.reasoning_content = m.thinking;
+          }
+          return out;
         }),
       ];
 
@@ -2408,10 +2449,15 @@ class AppStore {
               contentParts.push({ type: "text", text: textContent });
             }
 
-            return {
-              role: m.role,
-              content: contentParts,
-            };
+            const out: {
+              role: string;
+              content: typeof contentParts;
+              reasoning_content?: string;
+            } = { role: m.role, content: contentParts };
+            if (m.role === "assistant" && m.thinking) {
+              out.reasoning_content = m.thinking;
+            }
+            return out;
           }
 
           // Text-only message (original path)
@@ -2429,10 +2475,15 @@ class AppStore {
             }
           }
 
-          return {
-            role: m.role,
-            content: msgContent,
-          };
+          const out: {
+            role: string;
+            content: string;
+            reasoning_content?: string;
+          } = { role: m.role, content: msgContent };
+          if (m.role === "assistant" && m.thinking) {
+            out.reasoning_content = m.thinking;
+          }
+          return out;
         }),
       ];
 
@@ -3281,6 +3332,60 @@ class AppStore {
     }
   }
 
+  async createInstanceLink(
+    prefillInstances: string[],
+    decodeInstances: string[],
+  ): Promise<void> {
+    const response = await fetch("/v1/instance-links", {
+      method: "POST",
+      headers: { "Content-Type": "application/json" },
+      body: JSON.stringify({
+        prefill_instances: prefillInstances,
+        decode_instances: decodeInstances,
+      }),
+    });
+    if (!response.ok) {
+      throw new Error(
+        `Failed to create instance link: ${response.status} ${await response.text()}`,
+      );
+    }
+  }
+
+  async updateInstanceLink(
+    linkId: string,
+    prefillInstances: string[],
+    decodeInstances: string[],
+  ): Promise<void> {
+    const response = await fetch(
+      `/v1/instance-links/${encodeURIComponent(linkId)}`,
+      {
+        method: "PUT",
+        headers: { "Content-Type": "application/json" },
+        body: JSON.stringify({
+          prefill_instances: prefillInstances,
+          decode_instances: decodeInstances,
+        }),
+      },
+    );
+    if (!response.ok) {
+      throw new Error(
+        `Failed to update instance link: ${response.status} ${await response.text()}`,
+      );
+    }
+  }
+
+  async deleteInstanceLink(linkId: string): Promise<void> {
+    const response = await fetch(
+      `/v1/instance-links/${encodeURIComponent(linkId)}`,
+      { method: "DELETE" },
+    );
+    if (!response.ok) {
+      throw new Error(
+        `Failed to delete instance link: ${response.status} ${await response.text()}`,
+      );
+    }
+  }
+
   /**
    * Delete a downloaded model from a specific node
    */
@@ -3379,6 +3484,19 @@ export const prefillProgress = () => appStore.prefillProgress;
 export const topologyData = () => appStore.topologyData;
 export const instances = () => appStore.instances;
 export const runners = () => appStore.runners;
+export const instanceLinks = () => appStore.instanceLinks;
+export const featureFlags = () => appStore.featureFlags;
+export const createInstanceLink = (
+  prefillInstances: string[],
+  decodeInstances: string[],
+) => appStore.createInstanceLink(prefillInstances, decodeInstances);
+export const updateInstanceLink = (
+  linkId: string,
+  prefillInstances: string[],
+  decodeInstances: string[],
+) => appStore.updateInstanceLink(linkId, prefillInstances, decodeInstances);
+export const deleteInstanceLink = (linkId: string) =>
+  appStore.deleteInstanceLink(linkId);
 export const downloads = () => appStore.downloads;
 export const nodeDisk = () => appStore.nodeDisk;
 export const placementPreviews = () => appStore.placementPreviews;

dashboard/src/lib/utils/model_family.ts

@@ -0,0 +1,44 @@
+// Mirrors src/exo/shared/models/model_cards.py:derive_base_model
+const QUANT_SUFFIXES = new RegExp(
+  "[-_ ](?:MLX|MXFP[0-9]+|NVFP[0-9]+|GPTQ|AWQ|GGUF|fp16|bf16|fp8|int[0-9]+|[0-9]+(?:\\.[0-9]+)?bit|Q[0-9]+(?:_[A-Z0-9]+)?|gs[0-9]+)" +
+    "(?:[-_ ](?:MLX|Q[0-9]+|Int[0-9]+|[A-Z0-9]+|gs[0-9]+))*$",
+  "i",
+);
+
+function normalize(s: string): string {
+  return s
+    .replaceAll("-", " ")
+    .replaceAll("_", " ")
+    .replaceAll("  ", " ")
+    .trim();
+}
+
+export function deriveBaseModel(modelId: string): string {
+  const short = modelId.includes("/")
+    ? (modelId.split("/").pop() ?? modelId)
+    : modelId;
+  const stripped = short.replace(QUANT_SUFFIXES, "");
+  return normalize(stripped);
+}
+
+export function baseModelsCompatible(a: string, b: string): boolean {
+  return deriveBaseModel(a).toLowerCase() === deriveBaseModel(b).toLowerCase();
+}
+
+// Mirrors src/exo/shared/models/model_cards.py:derive_family
+export function deriveFamily(modelId: string): string {
+  const short = modelId.includes("/")
+    ? (modelId.split("/").pop() ?? modelId)
+    : modelId;
+  const stripped = short
+    .replace(QUANT_SUFFIXES, "")
+    .toLowerCase()
+    .replaceAll("_", "-");
+  const parts = stripped.split(/[-.]/);
+  const familyParts: string[] = [];
+  for (const p of parts) {
+    if (/^\d+$/.test(p) || /^\d+[bm]?$/i.test(p)) break;
+    familyParts.push(p);
+  }
+  return familyParts.length > 0 ? familyParts.join("-") : stripped;
+}

dashboard/src/routes/+page.svelte

@@ -3435,6 +3435,7 @@
             >
               <li>Connect nodes with TB5 cables</li>
               <li>Boot to Recovery (hold power 10s → Options)</li>
+              <li>Open Terminal from the Utilities menu</li>
               <li>
                 Run
                 <code class="text-yellow-300 bg-yellow-400/10 px-1 rounded"
@@ -4822,6 +4823,7 @@
                 >
                   <li>Connect nodes with TB5 cables</li>
                   <li>Boot to Recovery (hold power 10s → Options)</li>
+                  <li>Open Terminal from the Utilities menu</li>
                   <li>
                     Run
                     <code class="text-yellow-300 bg-yellow-400/10 px-1 rounded"
@@ -4968,6 +4970,7 @@
                   >
                     <li>Connect nodes with TB5 cables</li>
                     <li>Boot to Recovery (hold power 10s → Options)</li>
+                    <li>Open Terminal from the Utilities menu</li>
                     <li>
                       Run
                       <code

dashboard/src/routes/advanced/+page.svelte

@@ -0,0 +1,81 @@
+<script lang="ts">
+  import { browser } from "$app/environment";
+  import HeaderNav from "$lib/components/HeaderNav.svelte";
+  import PrefillDecodeDisaggregation from "$lib/components/PrefillDecodeDisaggregation.svelte";
+  import { featureFlags, refreshState } from "$lib/stores/app.svelte";
+  import { onMount } from "svelte";
+
+  type TabId = "prefill-decode";
+
+  const tabs: { id: TabId; label: string }[] = [
+    { id: "prefill-decode", label: "Prefill / Decode" },
+  ];
+
+  let activeTab = $state<TabId>(tabs[0].id);
+  let flagsLoaded = $state(false);
+
+  onMount(() => {
+    refreshState().finally(() => {
+      flagsLoaded = true;
+    });
+  });
+
+  const flags = $derived(featureFlags());
+  const enabled = $derived(flags["disaggregation"] === true);
+
+  $effect(() => {
+    if (browser && flagsLoaded && !enabled) {
+      // No advanced features enabled — bounce home.
+      window.location.hash = "/";
+    }
+  });
+</script>
+
+<div class="min-h-screen bg-exo-dark-gray flex flex-col">
+  <HeaderNav />
+
+  <main class="flex-1 max-w-[1100px] mx-auto w-full px-4 md:px-6 py-8">
+    {#if !flagsLoaded}
+      <div class="text-exo-light-gray/60 text-sm">Loading…</div>
+    {:else if !enabled}
+      <div class="text-exo-light-gray/60 text-sm">
+        No advanced features enabled. Set <code
+          class="text-exo-yellow font-mono">ENABLE_DISAGGREGATION=true</code
+        > on the cluster to access prefill/decode disaggregation.
+      </div>
+    {:else}
+      <div class="mb-4">
+        <h1
+          class="text-white text-xl md:text-2xl font-semibold tracking-wide mb-2"
+        >
+          Advanced
+        </h1>
+        <p class="text-exo-light-gray/60 text-sm">
+          Cluster-level configuration. Most users don't need anything here.
+        </p>
+      </div>
+
+      <div
+        class="flex flex-wrap gap-2 mb-6 border-b border-exo-light-gray/10 pb-3"
+      >
+        {#each tabs as tab (tab.id)}
+          <button
+            onclick={() => (activeTab = tab.id)}
+            class="px-3 py-1.5 text-xs rounded-md transition-all cursor-pointer
+              {activeTab === tab.id
+              ? 'bg-exo-yellow/15 text-exo-yellow border border-exo-yellow/30'
+              : 'text-exo-light-gray/60 hover:text-white/80 border border-transparent hover:border-exo-light-gray/20'}"
+          >
+            {tab.label}
+          </button>
+        {/each}
+      </div>
+
+      <div class="space-y-4">
+        {#if activeTab === "prefill-decode"}
+          <PrefillDecodeDisaggregation />
+        {/if}
+      </div>
+    {/if}
+  </main>
+</div>

dashboard/src/routes/integrations/+page.svelte

@@ -14,6 +14,7 @@
 
   let modelCapabilities = $state<Record<string, string[]>>({});
   let modelContextLengths = $state<Record<string, number>>({});
+  let modelReasoningDialects = $state<Record<string, string>>({});
 
   const runningModels = $derived.by(() => {
     const models: string[] = [];
@@ -88,10 +89,12 @@
   let codexModel = $state("");
   let codexMcpPath = $state("/Users/username");
   let openClawModel = $state("");
+  let piModel = $state("");
   $effect(() => {
     const def = modelsBySize.length > 0 ? modelsBySize[0] : "your-model-id";
     codexModel = def;
     openClawModel = def;
+    piModel = def;
   });
 
   const claudeShellCommand = $derived(
@@ -130,6 +133,7 @@
     for (const modelId of runningModels) {
       const caps = modelCapabilities[modelId] || [];
       const ctxLen = modelContextLengths[modelId] || 0;
+      const dialect = modelReasoningDialects[modelId];
       const entry: Record<string, unknown> = { name: modelId };
       if (ctxLen > 0) {
         entry.limit = { context: ctxLen, output: Math.min(ctxLen, 16384) };
@@ -137,6 +141,27 @@
       if (caps.includes("vision")) {
         entry.modalities = { input: ["text", "image"], output: ["text"] };
       }
+      // Reasoning round-trip: opencode's `interleaved` field tells the
+      // openai-compatible adapter to send the assistant's prior
+      // reasoning_content back in subsequent turns. Emit it for dialects
+      // whose chat templates use prior reasoning:
+      //   - `tool_conditional` (DeepSeek V3.2 / V4): wrapper preserves all
+      //     reasoning when tools are present.
+      //   - `post_last_user` (Qwen3-Thinking, GLM 4.5+, MiniMax M2.x):
+      //     Jinja template reads reasoning_content for assistant turns since
+      //     the last user message — exactly the tool-chain window.
+      //   - `channel` (gpt-oss / Harmony): the model's Jinja template reads
+      //     `message.thinking` rather than `message.reasoning_content`, but
+      //     the server bridges `reasoning_content` → `thinking` before
+      //     rendering, so the round-trip works through the standard field.
+      // `suffix` (Kimi): reasoning lives in content; no separate field path.
+      if (
+        dialect === "tool_conditional" ||
+        dialect === "post_last_user" ||
+        dialect === "channel"
+      ) {
+        entry.interleaved = { field: "reasoning_content" };
+      }
       models[modelId] = entry;
     }
     if (Object.keys(models).length === 0) {
@@ -218,6 +243,55 @@
     ),
   );
 
+  const piModelsJson = $derived.by(() => {
+    const models: Record<string, unknown>[] = [];
+    for (const modelId of runningModels) {
+      const caps = modelCapabilities[modelId] || [];
+      const ctxLen = modelContextLengths[modelId] || 0;
+      const entry: Record<string, unknown> = { id: modelId };
+      if (caps.includes("vision")) {
+        entry.input = ["text", "image"];
+      }
+      // Mark thinking-capable models so pi surfaces its thinking-level selector
+      // for them. exo capability strings: "thinking" (model emits reasoning
+      // content) and "thinking_toggle" (user can turn it on/off).
+      if (caps.includes("thinking") || caps.includes("thinking_toggle")) {
+        entry.reasoning = true;
+      }
+      if (ctxLen > 0) {
+        entry.contextWindow = ctxLen;
+      }
+      models.push(entry);
+    }
+    if (models.length === 0) {
+      models.push({ id: "your-model-id" });
+    }
+    return JSON.stringify(
+      {
+        providers: {
+          exo: {
+            baseUrl: `${apiUrl}/v1`,
+            api: "openai-completions",
+            apiKey: "exo",
+            compat: {
+              supportsDeveloperRole: false,
+              // exo's OpenAI surface takes a boolean `enable_thinking` toggle,
+              // not graded effort levels, so disable pi's `reasoning_effort`
+              // parameter and use the matching top-level-boolean format.
+              supportsReasoningEffort: false,
+              thinkingFormat: "qwen",
+            },
+            models,
+          },
+        },
+      },
+      null,
+      2,
+    );
+  });
+
+  const piShellCommand = $derived(`pi --provider exo --model ${piModel}`);
+
   const ollamaCommand = $derived(
     `OLLAMA_HOST=${apiUrl}/ollama ollama run ${modelsBySize.length > 0 ? modelsBySize[0] : "your-model-id"}`,
   );
@@ -277,6 +351,7 @@
     "OpenCode",
     "Codex",
     "OpenClaw",
+    "Pi",
     "Open WebUI",
     "n8n",
     "Firefox",
@@ -298,16 +373,25 @@
     try {
       const resp = await fetch("/v1/models");
       const data = (await resp.json()) as {
-        data: { id: string; capabilities: string[]; context_length: number }[];
+        data: {
+          id: string;
+          capabilities: string[];
+          context_length: number;
+          reasoning_dialect?: string;
+        }[];
       };
       const caps: Record<string, string[]> = {};
       const ctxs: Record<string, number> = {};
+      const dialects: Record<string, string> = {};
       for (const model of data.data) {
         caps[model.id] = model.capabilities || [];
         if (model.context_length > 0) ctxs[model.id] = model.context_length;
+        if (model.reasoning_dialect)
+          dialects[model.id] = model.reasoning_dialect;
       }
       modelCapabilities = caps;
       modelContextLengths = ctxs;
+      modelReasoningDialects = dialects;
     } catch {
       /* ignore */
     }
@@ -515,6 +599,33 @@
           config={`openclaw doctor --fix${(modelCapabilities[openClawModel] || []).includes("vision") ? `\nopenclaw models set-image exo/${openClawModel}` : ""}\nopenclaw gateway &\nopenclaw dashboard`}
           language="bash"
         />
+      {:else if activeTab === "Pi"}
+        {#if runningModels.length > 1}
+          <div class="text-xs">
+            <span
+              class="text-exo-light-gray/50 text-[10px] uppercase tracking-wider block mb-1"
+              >Model</span
+            >
+            <select bind:value={piModel} class={selectClass}>
+              {#each runningModels as model}
+                <option value={model}>{model.split("/").pop()}</option>
+              {/each}
+            </select>
+          </div>
+        {/if}
+        <IntegrationCard
+          title="Models Config"
+          subtitle="~/.pi/agent/models.json"
+          description="Register exo as a custom provider in pi. Create or edit this file, then run pi and pick an exo model via /model. Install pi with: npm install -g @mariozechner/pi-coding-agent"
+          config={piModelsJson}
+        />
+        <IntegrationCard
+          title="Shell Command"
+          subtitle="Run in terminal"
+          description="Launch pi directly with the exo provider and model selected."
+          config={piShellCommand}
+          language="bash"
+        />
       {:else if activeTab === "Open WebUI"}
         <IntegrationCard
           title="1. Start Open WebUI"

package-lock.json

@@ -0,0 +1,6 @@
+{
+  "name": "exo",
+  "lockfileVersion": 3,
+  "requires": true,
+  "packages": {}
+}

pyproject.toml

@@ -3,7 +3,7 @@ name = "exo"
 version = "0.3.70"
 description = "Exo"
 readme = "README.md"
-requires-python = ">=3.13"
+requires-python = "==3.13.*"
 dependencies = [
   "aiofiles>=24.1.0",
   "aiohttp>=3.12.14",
@@ -15,11 +15,11 @@ dependencies = [
   "huggingface-hub>=1.8.0",
   "psutil>=7.0.0",
   "loguru>=0.7.3",
-  "exo-pyo3-bindings",                       # rust bindings
+  "exo-pyo3-bindings",                         # rust bindings
   "anyio==4.11.0",
-  "mlx==0.31.1; sys_platform == 'darwin'",
-  "mlx-lm",
-  "tiktoken>=0.12.0",                        # required for kimi k2 tokenizer
+  "mlx==0.31.2; sys_platform == 'darwin'",
+  "mlx-lm; sys_platform=='darwin'",
+  "tiktoken>=0.12.0",                          # required for kimi k2 tokenizer
   "hypercorn>=0.18.0",
   "openai-harmony>=0.0.8",
   "httpx>=0.28.1",
@@ -28,8 +28,8 @@ dependencies = [
   "python-multipart>=0.0.21",
   "msgspec>=0.19.0",
   "zstandard>=0.23.0",
-  "mlx-vlm>=0.3.11",
-  "transformers>=5.0.0,<5.4.0",
+  "mlx-vlm>=0.3.11; sys_platform == 'darwin'",
+  "transformers>=5.6.2",
 ]
 
 [project.scripts]
@@ -49,15 +49,24 @@ dev = [
 [project.optional-dependencies]
 build = ["nanobind"]
 cpu = [
+  "mlx==0.31.1; sys_platform == 'linux'",
   "mlx-cpu==0.31.1; sys_platform == 'linux'",
+  "mlx-lm; sys_platform == 'linux'",
+  "mlx-vlm>=0.3.11; sys_platform== 'linux'",
   "torch>=2.10.0; sys_platform == 'linux'",
 ]
 cuda12 = [
+  "mlx==0.31.1; sys_platform == 'linux'",
   "mlx-cuda-12==0.31.1; sys_platform == 'linux'",
+  "mlx-lm; sys_platform == 'linux'",
+  "mlx-vlm>=0.3.11; sys_platform== 'linux'",
   "torch>=2.10.0; sys_platform == 'linux'",
 ]
 cuda13 = [
+  "mlx==0.31.1; sys_platform == 'linux'",
   "mlx-cuda-13==0.31.1; sys_platform == 'linux'",
+  "mlx-lm; sys_platform == 'linux'",
+  "mlx-vlm>=0.3.11; sys_platform== 'linux'",
   "torch>=2.10.0; sys_platform == 'linux'",
 ]
 
@@ -71,11 +80,11 @@ members = ["rust/exo_pyo3_bindings", "bench"]
 [tool.uv.sources]
 exo-pyo3-bindings = { workspace = true }
 mlx = { git = "https://github.com/rltakashige/mlx-jaccl-fix-small-recv.git", branch = "address-rdma-gpu-locks", marker = "sys_platform == 'darwin'" }
-mlx-lm = { git = "https://github.com/rltakashige/mlx-lm", branch = "leo/fix-arrayscache-leak" }
+mlx-lm = { git = "https://github.com/rltakashige/mlx-lm", branch = "leo/deepseek-v4" }
 torch = [
   { index = "pytorch-cu130", marker = "sys_platform == 'linux' and extra == 'cuda13' and extra != 'cpu' and extra != 'cuda12'" },
   { index = "pytorch-cu120", marker = "sys_platform == 'linux' and extra == 'cuda12' and extra != 'cpu' and extra != 'cuda13'" },
-  { index = "pytorch-cpu", marker = "sys_platform == 'linux' and extra == 'cpu' and extra != 'cuda12' and extra != 'cuda13'" },
+  { index = "pytorch-cpu", marker = "(extra != 'cuda12' and extra != 'cuda13' and sys_platform == 'linux') or sys_platform == 'darwin'" },
 ]
 vllm = { git = "https://github.com/hmellor/vllm.git", branch = "transformers-v5" }
 
@@ -148,7 +157,11 @@ required-version = ">=0.8.6"
 prerelease = "allow"
 environments = ["sys_platform == 'darwin'", "sys_platform == 'linux'"]
 conflicts = [[{ extra = "cuda12" }, { extra = "cuda13" }, { extra = "cpu" }]]
-constraint-dependencies = ["transformers>=5.0.0,<5.4.0"]
+constraint-dependencies = ["transformers>=5.6.2"]
+override-dependencies = [
+  "mlx==0.31.1; sys_platform=='linux'",
+  "mlx; sys_platform=='darwin'",
+]
 
 [tool.uv.extra-build-dependencies]
 miniaudio = ["setuptools", "cffi", "pycparser"]

python/parts.nix

@@ -5,14 +5,13 @@ let
     workspaceRoot = ../.;
   };
 
-  mkPythonSet = { pkgs, lib, self' }:
+  mkPythonSet = { pkgs, lib, self', members }:
     let
       inherit (pkgs.stdenv.hostPlatform) isLinux isDarwin isx86_64;
       inherit (pkgs.config) cudaSupport;
       inherit (pkgs) cudaPackages;
       cuda13Support = cudaSupport && cudaPackages.cudaMajorVersion == "13";
       libmlx_source = if cuda13Support then "mlx-cuda-13" else if cudaSupport then "mlx-cuda-12" else "mlx-cpu";
-      uv_extra = if cuda13Support then "cuda13" else if cudaSupport then "cuda12" else "cpu";
       python = pkgs.python313;
       cudaLibs = with cudaPackages; [
         cuda_cudart
@@ -51,7 +50,7 @@ let
           '';
         };
       };
-      buildSystemsOverlay = final: prev: { } //
+      buildSystemsOverlay = final: prev:
         lib.optionalAttrs isDarwin
           {
             mlx = prev.mlx.overrideAttrs (old:
@@ -81,7 +80,7 @@ let
                 nativeBuildInputs = (old.nativeBuildInputs or [ ]) ++ [ pkgs.cmake self'.packages.metal-toolchain ];
                 # TODO: non-sdk_26 support
                 buildInputs = (old.buildInputs or [ ])
-                  ++ [ gguf-tools pkgs.fmt pkgs.nlohmann_json pkgs.apple-sdk_26 ];
+                ++ [ gguf-tools pkgs.fmt pkgs.nlohmann_json pkgs.apple-sdk_26 ];
                 patches = [
                   (pkgs.replaceVars ../nix/darwin-build-fixes.patch {
                     sdkVersion = pkgs.apple-sdk_26.version;
@@ -113,42 +112,42 @@ let
                 MACOSX_DEPLOYMENT_TARGET = pkgs.apple-sdk_26.version;
               });
           } // lib.optionalAttrs isLinux {
-        mlx = prev.mlx.overrideAttrs (old: {
-          buildInputs = old.buildInputs ++ lib.optionals cudaSupport cudaLibs;
-          autoPatchelfIgnoreMissingDeps = lib.optionals cudaSupport [ "libcuda.so.1" ];
-          postInstall = (old.postInstall or "") + ''
-            cp -r "${final.${libmlx_source}}/${final.python.sitePackages}/mlx" "$out/${final.python.sitePackages}/mlx/"
-          '';
-        });
-      } // lib.optionalAttrs cudaSupport {
-        "${libmlx_source}" = prev."${libmlx_source}".overrideAttrs (old: {
-          buildInputs = old.buildInputs ++ cudaLibs;
-          autoPatchelfIgnoreMissingDeps = [ "libcuda.so.1" ];
-        });
-        nvidia-cufile = prev.nvidia-cufile.overrideAttrs (old: {
-          buildInputs = old.buildInputs ++ [ pkgs.rdma-core ];
-          autoPatchelfIgnoreMissingDeps = [ "libcuda.so.1" ];
-        });
-        nvidia-cusolver = prev.nvidia-cusolver.overrideAttrs (old: {
-          buildInputs = old.buildInputs ++ cudaLibs;
-          autoPatchelfIgnoreMissingDeps = [ "libcuda.so.1" ];
-        });
-        nvidia-nvshmem-cu13 = prev.nvidia-nvshmem-cu13.overrideAttrs (old: {
-          buildInputs = old.buildInputs ++ [ pkgs.rdma-core pkgs.pmix pkgs.libfabric pkgs.ucx pkgs.openmpi ];
-          autoPatchelfIgnoreMissingDeps = [ "libcuda.so.1" ];
-        });
-        nvidia-cusparse = prev.nvidia-cusparse.overrideAttrs (old: {
-          buildInputs = old.buildInputs ++ [ cudaLibs ];
-          autoPatchelfIgnoreMissingDeps = [ "libcuda.so.1" ];
-        });
-        torch = prev.torch.overrideAttrs (old: {
-          buildInputs = old.buildInputs ++ cudaLibs;
-          autoPatchelfIgnoreMissingDeps = [ "libcuda.so.1" ];
-        });
-      };
+          mlx = prev.mlx.overrideAttrs (old: {
+            buildInputs = old.buildInputs ++ lib.optionals cudaSupport cudaLibs;
+            autoPatchelfIgnoreMissingDeps = lib.optionals cudaSupport [ "libcuda.so.1" ];
+            postInstall = ''
+              cp -r "${final.${libmlx_source}}/${final.python.sitePackages}/mlx" "$out/${final.python.sitePackages}/mlx/"
+            '';
+          });
+        } // lib.optionalAttrs cudaSupport {
+          "${libmlx_source}" = prev."${libmlx_source}".overrideAttrs (old: {
+            buildInputs = old.buildInputs ++ cudaLibs;
+            autoPatchelfIgnoreMissingDeps = [ "libcuda.so.1" ];
+          });
+          nvidia-cufile = prev.nvidia-cufile.overrideAttrs (old: {
+            buildInputs = old.buildInputs ++ [ pkgs.rdma-core ];
+            autoPatchelfIgnoreMissingDeps = [ "libcuda.so.1" ];
+          });
+          nvidia-cusolver = prev.nvidia-cusolver.overrideAttrs (old: {
+            buildInputs = old.buildInputs ++ cudaLibs;
+            autoPatchelfIgnoreMissingDeps = [ "libcuda.so.1" ];
+          });
+          nvidia-nvshmem-cu13 = prev.nvidia-nvshmem-cu13.overrideAttrs (old: {
+            buildInputs = old.buildInputs ++ [ pkgs.rdma-core pkgs.pmix pkgs.libfabric pkgs.ucx pkgs.openmpi ];
+            autoPatchelfIgnoreMissingDeps = [ "libcuda.so.1" ];
+          });
+          nvidia-cusparse = prev.nvidia-cusparse.overrideAttrs (old: {
+            buildInputs = old.buildInputs ++ [ cudaLibs ];
+            autoPatchelfIgnoreMissingDeps = [ "libcuda.so.1" ];
+          });
+          torch = prev.torch.overrideAttrs (old: {
+            buildInputs = old.buildInputs ++ cudaLibs;
+            autoPatchelfIgnoreMissingDeps = [ "libcuda.so.1" ];
+          });
+        };
       pyprojectOverlay = workspace.mkPyprojectOverlay {
         sourcePreference = "wheel";
-        dependencies = { exo = [ uv_extra ]; exo-bench = [ ]; };
+        dependencies = members;
       };
       editableOverlay = workspace.mkEditablePyprojectOverlay {
         # Use environment variable pointing to editable root directory
@@ -165,8 +164,8 @@ let
           buildSystemsOverlay
         ]
       );
-
-      mkApp = cmd: name: members: pkgs.writeShellApplication {
+      venv = name: (pythonSet.mkVirtualEnv "${name}-env" members).overrideAttrs (_: { venvSkip = [ "lib/python${python.pythonVersion}/site-packages/mlx/share/cmake/*" ]; });
+      mkApp = cmd: name: pkgs.writeShellApplication {
         inherit name;
         runtimeEnv = {
           EXO_DASHBOARD_DIR = self'.packages.dashboard;
@@ -174,17 +173,17 @@ let
         };
         runtimeInputs = [
           # mlx and mlx-cuda ship clashing cmake files - we dont need them at runtime anyway
-          ((pythonSet.mkVirtualEnv "${name}-env" members).overrideAttrs (_: { venvSkip = [ "lib/python${python.pythonVersion}/site-packages/mlx/share/cmake/*" ]; }))
+          (venv name)
         ]
         ++ lib.optionals isDarwin [ pkgs.macmon ];
         text = "exec " + lib.optionalString cudaSupport "${lib.getExe pkgs.nix-gl-host} " + cmd;
       };
     in
     {
-      inherit pythonSet;
+      inherit venv;
       editablePythonSet = pythonSet.overrideScope editableOverlay;
-      mkPythonScript = members: name: path: mkApp ''python ${path} "$@"'' name members;
-      mkExo = name: members: mkApp ''exo "$@"'' name members;
+      mkPythonScript = path: mkApp ''python ${path} "$@"'';
+      mkExo = mkApp ''exo "$@"'';
     };
 in
 {
@@ -192,16 +191,21 @@ in
     { self', pkgs, unfreePkgs, lib, ... }:
     let
       inherit (pkgs.stdenv.hostPlatform) isLinux;
-      inherit (mkPythonSet { inherit self' pkgs lib; }) pythonSet editablePythonSet mkPythonScript mkExo;
-
-      exoVenv = pythonSet.mkVirtualEnv "exo-env" { exo = lib.optionals isLinux [ "cpu" ]; };
+      inherit (mkPythonSet { inherit self' pkgs lib; members = { exo = [ "cpu" ]; }; }) editablePythonSet mkExo;
 
       # Virtual environment with dev dependencies for testing
-      testVenv = pythonSet.mkVirtualEnv "exo-test-env" {
-        exo = [ "dev" ] ++ lib.optionals isLinux [ "cpu" ]; # Include pytest, pytest-asyncio, pytest-env
+      testVenv = (mkPythonSet {
+        inherit self' pkgs lib; members = {
+        exo = [ "dev" "cpu" ]; # Include pytest, pytest-asyncio, pytest-env
       };
+      }).venv "exo-test";
 
-      mkBenchScript = mkPythonScript { exo-bench = [ ]; };
+      mkBenchScript = (mkPythonSet {
+        inherit self' pkgs lib; members = {
+        exo = [ "cpu" ];
+        exo-bench = [ ]; # Include pytest, pytest-asyncio, pytest-env
+      };
+      }).mkPythonScript;
 
       mkSimplePythonScript = name: path: pkgs.writeShellApplication {
         inherit name;
@@ -212,9 +216,7 @@ in
     in
     {
       packages = {
-        exo = mkExo "exo" { exo = lib.optionals isLinux [ "cpu" ]; };
-        # for devShell
-        exo-venv = exoVenv;
+        exo = mkExo "exo";
         editableVenv = editablePythonSet.mkVirtualEnv "exo-dev-env" { exo = [ "dev" ]; };
         # for running tests in ci
         exo-test-env = testVenv;
@@ -224,8 +226,8 @@ in
         # used by ./tests/run_exo_on.sh
         exo-get-all-models-on-cluster = mkSimplePythonScript "exo-get-all-models-on-cluster" (inputs.self + /tests/get_all_models_on_cluster.py);
       } // lib.optionalAttrs isLinux {
-        exo-cuda-12 = (mkPythonSet { inherit self' lib; inherit (unfreePkgs.pkgsCuda.cudaPackages_12) pkgs; }).mkExo "exo-cuda-12" { exo = [ "cuda12" ]; };
-        exo-cuda-13 = (mkPythonSet { inherit self' lib; inherit (unfreePkgs.pkgsCuda.cudaPackages_13) pkgs; }).mkExo "exo-cuda-13" { exo = [ "cuda13" ]; };
+        exo-cuda-12 = (mkPythonSet { inherit self' lib; inherit (unfreePkgs.pkgsCuda.cudaPackages_12) pkgs; members = { exo = [ "cuda12" ]; }; }).mkExo "exo-cuda-12";
+        exo-cuda-13 = (mkPythonSet { inherit self' lib; inherit (unfreePkgs.pkgsCuda.cudaPackages_13) pkgs; members = { exo = [ "cuda13" ]; }; }).mkExo "exo-cuda-13";
       };
 
       checks = {
@@ -235,19 +237,11 @@ in
           touch $out
         '';
 
-        typecheck = pkgs.runCommand "typecheck"
-          {
-            nativeBuildInputs = [
-              testVenv
-              pkgs.basedpyright
-            ];
-          }
-          ''
-            cd ${inputs.self}
-            export HOME=$TMPDIR
-            basedpyright --pythonpath ${testVenv}/bin/python --project ${inputs.self}/pyproject.toml
-            touch $out
-          '';
+        typecheck = pkgs.runCommand "typecheck" { nativeBuildInputs = [ testVenv ]; } ''
+          cd ${inputs.self}
+          basedpyright
+          touch $out
+        '';
       };
     };
 }

resources/inference_model_cards/mlx-community--DeepSeek-V3.1-4bit.toml

@@ -8,6 +8,7 @@ family = "deepseek"
 quantization = "4bit"
 base_model = "DeepSeek V3.1"
 capabilities = ["text", "thinking", "thinking_toggle"]
+reasoning_dialect = "post_last_user"
 
 context_length = 131072
 

resources/inference_model_cards/mlx-community--DeepSeek-V3.1-8bit.toml

@@ -8,6 +8,7 @@ family = "deepseek"
 quantization = "8bit"
 base_model = "DeepSeek V3.1"
 capabilities = ["text", "thinking", "thinking_toggle"]
+reasoning_dialect = "post_last_user"
 
 context_length = 131072
 

resources/inference_model_cards/mlx-community--DeepSeek-V3.2-4bit.toml

@@ -8,6 +8,7 @@ family = "deepseek"
 quantization = "4bit"
 base_model = "DeepSeek V3.2"
 capabilities = ["text", "thinking", "thinking_toggle"]
+reasoning_dialect = "tool_conditional"
 
 context_length = 131072
 

resources/inference_model_cards/mlx-community--DeepSeek-V3.2-8bit.toml

@@ -8,6 +8,7 @@ family = "deepseek"
 quantization = "8bit"
 base_model = "DeepSeek V3.2"
 capabilities = ["text", "thinking", "thinking_toggle"]
+reasoning_dialect = "tool_conditional"
 
 context_length = 131072
 

resources/inference_model_cards/mlx-community--DeepSeek-V4-Flash.toml

@@ -0,0 +1,21 @@
+model_id = "mlx-community/DeepSeek-V4-Flash"
+n_layers = 43
+hidden_size = 4096
+num_key_value_heads = 1
+supports_tensor = true
+tasks = ["TextGeneration"]
+family = "deepseek"
+quantization = "8bit"
+base_model = "DeepSeek V4 Flash"
+capabilities = ["text", "thinking", "thinking_toggle"]
+reasoning_dialect = "tool_conditional"
+
+context_length = 1048576
+
+[storage_size]
+in_bytes = 155095760030
+
+# Source: https://huggingface.co/deepseek-ai/DeepSeek-V4-Flash
+[sampling_defaults]
+temperature = 1.0
+top_p = 1.0

resources/inference_model_cards/mlx-community--DeepSeek-V4-Pro.toml

@@ -0,0 +1,21 @@
+model_id = "mlx-community/DeepSeek-V4-Pro"
+n_layers = 61
+hidden_size = 7168
+num_key_value_heads = 1
+supports_tensor = true
+tasks = ["TextGeneration"]
+family = "deepseek"
+quantization = "8bit"
+base_model = "DeepSeek V4 Pro"
+capabilities = ["text", "thinking", "thinking_toggle"]
+reasoning_dialect = "tool_conditional"
+
+context_length = 1048576
+
+[storage_size]
+in_bytes = 849681803879
+
+# Source: https://huggingface.co/deepseek-ai/DeepSeek-V4-Pro
+[sampling_defaults]
+temperature = 1.0
+top_p = 1.0

resources/inference_model_cards/mlx-community--GLM-4.5-Air-8bit.toml

@@ -8,7 +8,7 @@ family = "glm"
 quantization = "8bit"
 base_model = "GLM 4.5 Air"
 capabilities = ["text", "thinking", "thinking_toggle"]
-
+reasoning_dialect = "post_last_user"
 context_length = 131072
 
 [storage_size]

resources/inference_model_cards/mlx-community--GLM-4.5-Air-bf16.toml

@@ -8,7 +8,7 @@ family = "glm"
 quantization = "bf16"
 base_model = "GLM 4.5 Air"
 capabilities = ["text", "thinking", "thinking_toggle"]
-
+reasoning_dialect = "post_last_user"
 context_length = 131072
 
 [storage_size]

resources/inference_model_cards/mlx-community--GLM-4.7-4bit.toml

@@ -8,7 +8,7 @@ family = "glm"
 quantization = "4bit"
 base_model = "GLM 4.7"
 capabilities = ["text", "thinking", "thinking_toggle"]
-
+reasoning_dialect = "post_last_user"
 context_length = 202752
 
 [storage_size]

resources/inference_model_cards/mlx-community--GLM-4.7-6bit.toml

@@ -8,7 +8,7 @@ family = "glm"
 quantization = "6bit"
 base_model = "GLM 4.7"
 capabilities = ["text", "thinking", "thinking_toggle"]
-
+reasoning_dialect = "post_last_user"
 context_length = 202752
 
 [storage_size]

resources/inference_model_cards/mlx-community--GLM-4.7-8bit-gs32.toml

@@ -8,7 +8,7 @@ family = "glm"
 quantization = "8bit"
 base_model = "GLM 4.7"
 capabilities = ["text", "thinking", "thinking_toggle"]
-
+reasoning_dialect = "post_last_user"
 context_length = 202752
 
 [storage_size]

resources/inference_model_cards/mlx-community--GLM-4.7-Flash-4bit.toml

@@ -8,7 +8,7 @@ family = "glm"
 quantization = "4bit"
 base_model = "GLM 4.7 Flash"
 capabilities = ["text", "thinking", "thinking_toggle"]
-
+reasoning_dialect = "post_last_user"
 context_length = 202752
 
 [storage_size]

resources/inference_model_cards/mlx-community--GLM-4.7-Flash-5bit.toml

@@ -8,7 +8,7 @@ family = "glm"
 quantization = "5bit"
 base_model = "GLM 4.7 Flash"
 capabilities = ["text", "thinking", "thinking_toggle"]
-
+reasoning_dialect = "post_last_user"
 context_length = 202752
 
 [storage_size]

resources/inference_model_cards/mlx-community--GLM-4.7-Flash-6bit.toml

@@ -8,7 +8,7 @@ family = "glm"
 quantization = "6bit"
 base_model = "GLM 4.7 Flash"
 capabilities = ["text", "thinking", "thinking_toggle"]
-
+reasoning_dialect = "post_last_user"
 context_length = 202752
 
 [storage_size]

resources/inference_model_cards/mlx-community--GLM-4.7-Flash-8bit.toml

@@ -8,7 +8,7 @@ family = "glm"
 quantization = "8bit"
 base_model = "GLM 4.7 Flash"
 capabilities = ["text", "thinking", "thinking_toggle"]
-
+reasoning_dialect = "post_last_user"
 context_length = 202752
 
 [storage_size]

resources/inference_model_cards/mlx-community--GLM-5-8bit.toml

@@ -8,7 +8,7 @@ family = "glm"
 quantization = "8bit"
 base_model = "GLM-5"
 capabilities = ["text", "thinking"]
-
+reasoning_dialect = "post_last_user"
 context_length = 202752
 
 [storage_size]

resources/inference_model_cards/mlx-community--GLM-5-MXFP4-Q8.toml

@@ -8,7 +8,7 @@ family = "glm"
 quantization = "MXFP4-Q8"
 base_model = "GLM-5"
 capabilities = ["text", "thinking"]
-
+reasoning_dialect = "post_last_user"
 context_length = 202752
 
 [storage_size]

resources/inference_model_cards/mlx-community--GLM-5-bf16.toml

@@ -8,7 +8,7 @@ family = "glm"
 quantization = "bf16"
 base_model = "GLM-5"
 capabilities = ["text", "thinking"]
-
+reasoning_dialect = "post_last_user"
 context_length = 202752
 
 [storage_size]

resources/inference_model_cards/mlx-community--GLM-5.1-DQ4plus-q8.toml

@@ -0,0 +1,21 @@
+model_id = "mlx-community/GLM-5.1-DQ4plus-q8"
+n_layers = 78
+hidden_size = 6144
+num_key_value_heads = 64
+supports_tensor = true
+tasks = ["TextGeneration"]
+family = "glm"
+quantization = "8bit"
+base_model = "GLM-5.1"
+capabilities = ["text", "thinking"]
+reasoning_dialect = "post_last_user"
+context_length = 202752
+
+[storage_size]
+in_bytes = 465173655552
+
+# Source: https://huggingface.co/zai-org/GLM-5.1
+# Source: https://docs.z.ai/api-reference/llm/chat-completion
+[sampling_defaults]
+temperature = 1.0
+top_p = 0.95

resources/inference_model_cards/mlx-community--GLM-5.1-MXFP4-Q8.toml

@@ -0,0 +1,21 @@
+model_id = "mlx-community/GLM-5.1-MXFP4-Q8"
+n_layers = 78
+hidden_size = 6144
+num_key_value_heads = 64
+supports_tensor = true
+tasks = ["TextGeneration"]
+family = "glm"
+quantization = "MXFP4-Q8"
+base_model = "GLM-5.1"
+capabilities = ["text", "thinking"]
+reasoning_dialect = "post_last_user"
+context_length = 202752
+
+[storage_size]
+in_bytes = 405480321024
+
+# Source: https://huggingface.co/zai-org/GLM-5.1
+# Source: https://docs.z.ai/api-reference/llm/chat-completion
+[sampling_defaults]
+temperature = 1.0
+top_p = 0.95

resources/inference_model_cards/mlx-community--GLM-5.1.toml

@@ -0,0 +1,21 @@
+model_id = "mlx-community/GLM-5.1"
+n_layers = 78
+hidden_size = 6144
+num_key_value_heads = 64
+supports_tensor = true
+tasks = ["TextGeneration"]
+family = "glm"
+quantization = "bf16"
+base_model = "GLM-5.1"
+capabilities = ["text", "thinking"]
+reasoning_dialect = "post_last_user"
+context_length = 202752
+
+[storage_size]
+in_bytes = 1487822475264
+
+# Source: https://huggingface.co/zai-org/GLM-5.1
+# Source: https://docs.z.ai/api-reference/llm/chat-completion
+[sampling_defaults]
+temperature = 1.0
+top_p = 0.95

resources/inference_model_cards/mlx-community--Kimi-K2-Thinking.toml

@@ -8,7 +8,7 @@ family = "kimi"
 quantization = ""
 base_model = "Kimi K2"
 capabilities = ["text", "thinking", "thinking_toggle"]
-
+reasoning_dialect = "suffix"
 context_length = 262144
 
 [storage_size]

resources/inference_model_cards/mlx-community--Kimi-K2.5.toml

@@ -8,7 +8,7 @@ family = "kimi"
 quantization = ""
 base_model = "Kimi K2.5"
 capabilities = ["text", "thinking", "thinking_toggle", "vision"]
-
+reasoning_dialect = "suffix"
 context_length = 262144
 
 [storage_size]

resources/inference_model_cards/mlx-community--Kimi-K2.6-mlx-DQ3_K_M-q8.toml

@@ -0,0 +1,33 @@
+model_id = "mlx-community/Kimi-K2.6-mlx-DQ3_K_M-q8"
+n_layers = 61
+hidden_size = 7168
+num_key_value_heads = 64
+supports_tensor = true
+tasks = ["TextGeneration"]
+family = "kimi"
+quantization = "3bit"
+base_model = "Kimi K2.6"
+capabilities = ["text", "thinking", "thinking_toggle", "vision"]
+reasoning_dialect = "suffix"
+context_length = 262144
+
+[storage_size]
+in_bytes = 470628683776
+
+[vision]
+image_token_id = 163605
+model_type = "kimi_vl"
+weights_repo = "exolabs/Kimi-K2.6-vision"
+processor_repo = "moonshotai/Kimi-K2.6"
+
+# Source: https://huggingface.co/moonshotai/Kimi-K2.6
+[sampling_defaults]
+temperature = 1.0
+top_p = 0.95
+min_p = 0.01
+
+# Source: https://huggingface.co/moonshotai/Kimi-K2.6
+[sampling_defaults.non_thinking]
+temperature = 0.6
+top_p = 0.95
+min_p = 0.01

resources/inference_model_cards/mlx-community--MiniMax-M2.1-3bit.toml

@@ -8,7 +8,7 @@ family = "minimax"
 quantization = "3bit"
 base_model = "MiniMax M2.1"
 capabilities = ["text", "thinking", "thinking_toggle"]
-
+reasoning_dialect = "post_last_user"
 context_length = 196608
 
 [storage_size]

resources/inference_model_cards/mlx-community--MiniMax-M2.1-8bit.toml

@@ -8,7 +8,7 @@ family = "minimax"
 quantization = "8bit"
 base_model = "MiniMax M2.1"
 capabilities = ["text", "thinking", "thinking_toggle"]
-
+reasoning_dialect = "post_last_user"
 context_length = 196608
 
 [storage_size]

resources/inference_model_cards/mlx-community--MiniMax-M2.5-4bit.toml

@@ -8,7 +8,7 @@ family = "minimax"
 quantization = "4bit"
 base_model = "MiniMax M2.5"
 capabilities = ["text", "thinking"]
-
+reasoning_dialect = "post_last_user"
 context_length = 196608
 
 [storage_size]

resources/inference_model_cards/mlx-community--MiniMax-M2.5-6bit.toml

@@ -8,7 +8,7 @@ family = "minimax"
 quantization = "6bit"
 base_model = "MiniMax M2.5"
 capabilities = ["text", "thinking"]
-
+reasoning_dialect = "post_last_user"
 context_length = 196608
 
 [storage_size]

resources/inference_model_cards/mlx-community--MiniMax-M2.5-8bit.toml

@@ -8,7 +8,7 @@ family = "minimax"
 quantization = "8bit"
 base_model = "MiniMax M2.5"
 capabilities = ["text", "thinking"]
-
+reasoning_dialect = "post_last_user"
 context_length = 196608
 
 [storage_size]

resources/inference_model_cards/mlx-community--MiniMax-M2.7-4bit-mxfp4.toml

@@ -8,7 +8,7 @@ family = "minimax"
 quantization = "4bit-mxfp4"
 base_model = "MiniMax M2.7"
 capabilities = ["text", "thinking"]
-
+reasoning_dialect = "post_last_user"
 context_length = 196608
 
 [storage_size]

resources/inference_model_cards/mlx-community--MiniMax-M2.7-4bit.toml

@@ -8,7 +8,7 @@ family = "minimax"
 quantization = "4bit"
 base_model = "MiniMax M2.7"
 capabilities = ["text", "thinking"]
-
+reasoning_dialect = "post_last_user"
 context_length = 196608
 
 [storage_size]

resources/inference_model_cards/mlx-community--MiniMax-M2.7-5bit.toml

@@ -8,7 +8,7 @@ family = "minimax"
 quantization = "5bit"
 base_model = "MiniMax M2.7"
 capabilities = ["text", "thinking"]
-
+reasoning_dialect = "post_last_user"
 context_length = 196608
 
 [storage_size]

resources/inference_model_cards/mlx-community--MiniMax-M2.7-6bit.toml

@@ -8,7 +8,7 @@ family = "minimax"
 quantization = "6bit"
 base_model = "MiniMax M2.7"
 capabilities = ["text", "thinking"]
-
+reasoning_dialect = "post_last_user"
 context_length = 196608
 
 [storage_size]

resources/inference_model_cards/mlx-community--MiniMax-M2.7-8bit.toml

@@ -8,7 +8,7 @@ family = "minimax"
 quantization = "8bit"
 base_model = "MiniMax M2.7"
 capabilities = ["text", "thinking"]
-
+reasoning_dialect = "post_last_user"
 context_length = 196608
 
 [storage_size]

resources/inference_model_cards/mlx-community--MiniMax-M2.7.toml

@@ -8,7 +8,7 @@ family = "minimax"
 quantization = "bf16"
 base_model = "MiniMax M2.7"
 capabilities = ["text", "thinking"]
-
+reasoning_dialect = "post_last_user"
 context_length = 196608
 
 [storage_size]

resources/inference_model_cards/mlx-community--Qwen3-Next-80B-A3B-Thinking-4bit.toml

@@ -8,7 +8,7 @@ family = "qwen"
 quantization = "4bit"
 base_model = "Qwen3 Next 80B"
 capabilities = ["text", "thinking", "thinking_toggle"]
-
+reasoning_dialect = "post_last_user"
 context_length = 262144
 
 [storage_size]

resources/inference_model_cards/mlx-community--Qwen3-Next-80B-A3B-Thinking-8bit.toml

@@ -8,7 +8,7 @@ family = "qwen"
 quantization = "8bit"
 base_model = "Qwen3 Next 80B"
 capabilities = ["text", "thinking", "thinking_toggle"]
-
+reasoning_dialect = "post_last_user"
 context_length = 262144
 
 [storage_size]

resources/inference_model_cards/mlx-community--Qwen3.5-122B-A10B-4bit.toml

@@ -8,7 +8,7 @@ family = "qwen"
 quantization = "4bit"
 base_model = "Qwen3.5 122B A10B"
 capabilities = ["text", "thinking", "thinking_toggle", "vision"]
-
+reasoning_dialect = "post_last_user"
 context_length = 262144
 
 [storage_size]

resources/inference_model_cards/mlx-community--Qwen3.5-122B-A10B-6bit.toml

@@ -8,7 +8,7 @@ family = "qwen"
 quantization = "6bit"
 base_model = "Qwen3.5 122B A10B"
 capabilities = ["text", "thinking", "thinking_toggle", "vision"]
-
+reasoning_dialect = "post_last_user"
 context_length = 262144
 
 [storage_size]

resources/inference_model_cards/mlx-community--Qwen3.5-122B-A10B-8bit.toml

@@ -8,7 +8,7 @@ family = "qwen"
 quantization = "8bit"
 base_model = "Qwen3.5 122B A10B"
 capabilities = ["text", "thinking", "thinking_toggle", "vision"]
-
+reasoning_dialect = "post_last_user"
 context_length = 262144
 
 [storage_size]

resources/inference_model_cards/mlx-community--Qwen3.5-122B-A10B-bf16.toml

@@ -8,7 +8,7 @@ family = "qwen"
 quantization = "bf16"
 base_model = "Qwen3.5 122B A10B"
 capabilities = ["text", "thinking", "thinking_toggle", "vision"]
-
+reasoning_dialect = "post_last_user"
 context_length = 262144
 
 [storage_size]

resources/inference_model_cards/mlx-community--Qwen3.5-27B-4bit.toml

@@ -8,7 +8,7 @@ family = "qwen"
 quantization = "4bit"
 base_model = "Qwen3.5 27B"
 capabilities = ["text", "thinking", "thinking_toggle", "vision"]
-
+reasoning_dialect = "post_last_user"
 context_length = 262144
 
 [storage_size]

resources/inference_model_cards/mlx-community--Qwen3.5-27B-8bit.toml

@@ -8,7 +8,7 @@ family = "qwen"
 quantization = "8bit"
 base_model = "Qwen3.5 27B"
 capabilities = ["text", "thinking", "thinking_toggle", "vision"]
-
+reasoning_dialect = "post_last_user"
 context_length = 262144
 
 [storage_size]

resources/inference_model_cards/mlx-community--Qwen3.5-2B-MLX-8bit.toml

@@ -8,7 +8,7 @@ family = "qwen"
 quantization = "8bit"
 base_model = "Qwen3.5 2B"
 capabilities = ["text", "thinking", "thinking_toggle", "vision"]
-
+reasoning_dialect = "post_last_user"
 context_length = 262144
 
 [storage_size]

resources/inference_model_cards/mlx-community--Qwen3.5-35B-A3B-4bit.toml

@@ -8,7 +8,7 @@ family = "qwen"
 quantization = "4bit"
 base_model = "Qwen3.5 35B A3B"
 capabilities = ["text", "thinking", "thinking_toggle", "vision"]
-
+reasoning_dialect = "post_last_user"
 context_length = 262144
 
 [storage_size]

resources/inference_model_cards/mlx-community--Qwen3.5-35B-A3B-8bit.toml

@@ -8,7 +8,7 @@ family = "qwen"
 quantization = "8bit"
 base_model = "Qwen3.5 35B A3B"
 capabilities = ["text", "thinking", "thinking_toggle", "vision"]
-
+reasoning_dialect = "post_last_user"
 context_length = 262144
 
 [storage_size]

resources/inference_model_cards/mlx-community--Qwen3.5-397B-A17B-4bit.toml

@@ -8,7 +8,7 @@ family = "qwen"
 quantization = "4bit"
 base_model = "Qwen3.5 397B A17B"
 capabilities = ["text", "thinking", "thinking_toggle", "vision"]
-
+reasoning_dialect = "post_last_user"
 context_length = 262144
 
 [storage_size]

resources/inference_model_cards/mlx-community--Qwen3.5-397B-A17B-6bit.toml

@@ -8,7 +8,7 @@ family = "qwen"
 quantization = "6bit"
 base_model = "Qwen3.5 397B A17B"
 capabilities = ["text", "thinking", "thinking_toggle", "vision"]
-
+reasoning_dialect = "post_last_user"
 context_length = 262144
 
 [storage_size]

resources/inference_model_cards/mlx-community--Qwen3.5-397B-A17B-8bit.toml

@@ -8,7 +8,7 @@ family = "qwen"
 quantization = "8bit"
 base_model = "Qwen3.5 397B A17B"
 capabilities = ["text", "thinking", "thinking_toggle", "vision"]
-
+reasoning_dialect = "post_last_user"
 context_length = 262144
 
 [storage_size]

resources/inference_model_cards/mlx-community--Qwen3.5-9B-4bit.toml

@@ -8,7 +8,7 @@ family = "qwen"
 quantization = "4bit"
 base_model = "Qwen3.5 9B"
 capabilities = ["text", "thinking", "thinking_toggle", "vision"]
-
+reasoning_dialect = "post_last_user"
 context_length = 262144
 
 [storage_size]

resources/inference_model_cards/mlx-community--Qwen3.5-9B-8bit.toml

@@ -8,7 +8,7 @@ family = "qwen"
 quantization = "8bit"
 base_model = "Qwen3.5 9B"
 capabilities = ["text", "thinking", "thinking_toggle", "vision"]
-
+reasoning_dialect = "post_last_user"
 context_length = 262144
 
 [storage_size]

resources/inference_model_cards/mlx-community--Qwen3.6-27B-4bit.toml

@@ -0,0 +1,35 @@
+model_id = "mlx-community/Qwen3.6-27B-4bit"
+n_layers = 64
+hidden_size = 5120
+num_key_value_heads = 4
+supports_tensor = true
+tasks = ["TextGeneration"]
+family = "qwen"
+quantization = "4bit"
+base_model = "Qwen3.6 27B"
+capabilities = ["text", "thinking", "thinking_toggle", "vision"]
+reasoning_dialect = "post_last_user"
+context_length = 262144
+
+[storage_size]
+in_bytes = 16054262240
+
+# Source: https://huggingface.co/Qwen/Qwen3.6-27B#best-practices
+# Source: https://unsloth.ai/docs/models/qwen3.5
+[sampling_defaults]
+temperature = 1.0
+top_p = 0.95
+top_k = 20
+min_p = 0.0
+repetition_penalty = 1.0
+presence_penalty = 1.5
+
+# Source: https://huggingface.co/Qwen/Qwen3.6-27B#best-practices
+# Source: https://unsloth.ai/docs/models/qwen3.5
+[sampling_defaults.non_thinking]
+temperature = 0.7
+top_p = 0.8
+top_k = 20
+min_p = 0.0
+repetition_penalty = 1.0
+presence_penalty = 1.5

resources/inference_model_cards/mlx-community--Qwen3.6-27B-8bit.toml

@@ -0,0 +1,35 @@
+model_id = "mlx-community/Qwen3.6-27B-8bit"
+n_layers = 64
+hidden_size = 5120
+num_key_value_heads = 4
+supports_tensor = true
+tasks = ["TextGeneration"]
+family = "qwen"
+quantization = "8bit"
+base_model = "Qwen3.6 27B"
+capabilities = ["text", "thinking", "thinking_toggle", "vision"]
+reasoning_dialect = "post_last_user"
+context_length = 262144
+
+[storage_size]
+in_bytes = 29500938720
+
+# Source: https://huggingface.co/Qwen/Qwen3.6-27B#best-practices
+# Source: https://unsloth.ai/docs/models/qwen3.5
+[sampling_defaults]
+temperature = 1.0
+top_p = 0.95
+top_k = 20
+min_p = 0.0
+repetition_penalty = 1.0
+presence_penalty = 1.5
+
+# Source: https://huggingface.co/Qwen/Qwen3.6-27B#best-practices
+# Source: https://unsloth.ai/docs/models/qwen3.5
+[sampling_defaults.non_thinking]
+temperature = 0.7
+top_p = 0.8
+top_k = 20
+min_p = 0.0
+repetition_penalty = 1.0
+presence_penalty = 1.5

resources/inference_model_cards/mlx-community--Qwen3.6-27B-bf16.toml

@@ -0,0 +1,35 @@
+model_id = "mlx-community/Qwen3.6-27B-bf16"
+n_layers = 64
+hidden_size = 5120
+num_key_value_heads = 4
+supports_tensor = true
+tasks = ["TextGeneration"]
+family = "qwen"
+quantization = "bf16"
+base_model = "Qwen3.6 27B"
+capabilities = ["text", "thinking", "thinking_toggle", "vision"]
+reasoning_dialect = "post_last_user"
+context_length = 262144
+
+[storage_size]
+in_bytes = 54713457120
+
+# Source: https://huggingface.co/Qwen/Qwen3.6-27B#best-practices
+# Source: https://unsloth.ai/docs/models/qwen3.5
+[sampling_defaults]
+temperature = 1.0
+top_p = 0.95
+top_k = 20
+min_p = 0.0
+repetition_penalty = 1.0
+presence_penalty = 1.5
+
+# Source: https://huggingface.co/Qwen/Qwen3.6-27B#best-practices
+# Source: https://unsloth.ai/docs/models/qwen3.5
+[sampling_defaults.non_thinking]
+temperature = 0.7
+top_p = 0.8
+top_k = 20
+min_p = 0.0
+repetition_penalty = 1.0
+presence_penalty = 1.5

resources/inference_model_cards/mlx-community--Qwen3.6-35B-A3B-4bit.toml

@@ -8,7 +8,7 @@ family = "qwen"
 quantization = "4bit"
 base_model = "Qwen3.6 35B A3B"
 capabilities = ["text", "thinking", "thinking_toggle", "vision"]
-
+reasoning_dialect = "post_last_user"
 context_length = 262144
 
 [storage_size]

resources/inference_model_cards/mlx-community--Qwen3.6-35B-A3B-5bit.toml

@@ -8,7 +8,7 @@ family = "qwen"
 quantization = "5bit"
 base_model = "Qwen3.6 35B A3B"
 capabilities = ["text", "thinking", "thinking_toggle", "vision"]
-
+reasoning_dialect = "post_last_user"
 context_length = 262144
 
 [storage_size]

resources/inference_model_cards/mlx-community--Qwen3.6-35B-A3B-8bit.toml

@@ -8,7 +8,7 @@ family = "qwen"
 quantization = "8bit"
 base_model = "Qwen3.6 35B A3B"
 capabilities = ["text", "thinking", "thinking_toggle", "vision"]
-
+reasoning_dialect = "post_last_user"
 context_length = 262144
 
 [storage_size]

resources/inference_model_cards/mlx-community--Qwen3.6-35B-A3B-bf16.toml

@@ -8,7 +8,7 @@ family = "qwen"
 quantization = "bf16"
 base_model = "Qwen3.6 35B A3B"
 capabilities = ["text", "thinking", "thinking_toggle", "vision"]
-
+reasoning_dialect = "post_last_user"
 context_length = 262144
 
 [storage_size]

resources/inference_model_cards/mlx-community--gpt-oss-120b-MXFP4-Q8.toml

@@ -8,7 +8,7 @@ family = "gpt-oss"
 quantization = "MXFP4-Q8"
 base_model = "GPT-OSS 120B"
 capabilities = ["text", "thinking"]
-
+reasoning_dialect = "channel"
 context_length = 131072
 
 [storage_size]

resources/inference_model_cards/mlx-community--gpt-oss-20b-MXFP4-Q8.toml

@@ -8,7 +8,7 @@ family = "gpt-oss"
 quantization = "MXFP4-Q8"
 base_model = "GPT-OSS 20B"
 capabilities = ["text", "thinking"]
-
+reasoning_dialect = "channel"
 context_length = 131072
 
 [storage_size]

resources/inference_model_cards/moonshotai--Kimi-K2.6.toml

@@ -0,0 +1,33 @@
+model_id = "moonshotai/Kimi-K2.6"
+n_layers = 61
+hidden_size = 7168
+num_key_value_heads = 64
+supports_tensor = true
+tasks = ["TextGeneration"]
+family = "kimi"
+quantization = ""
+base_model = "Kimi K2.6"
+capabilities = ["text", "thinking", "thinking_toggle", "vision"]
+
+context_length = 262144
+
+[storage_size]
+in_bytes = 595148192736
+
+[vision]
+image_token_id = 163605
+model_type = "kimi_vl"
+weights_repo = "exolabs/Kimi-K2.6-vision"
+processor_repo = "moonshotai/Kimi-K2.6"
+
+# Source: https://huggingface.co/moonshotai/Kimi-K2.6
+[sampling_defaults]
+temperature = 1.0
+top_p = 0.95
+min_p = 0.01
+
+# Source: https://huggingface.co/moonshotai/Kimi-K2.6
+[sampling_defaults.non_thinking]
+temperature = 0.6
+top_p = 0.95
+min_p = 0.01

src/exo/api/adapters/chat_completions.py

@@ -131,9 +131,13 @@ async def chat_request_to_text_generation(
                         multimodal_content.append({"type": "text", "text": part.text})
                     else:
                         multimodal_content.append({"type": "image"})
-                chat_template_messages.append(
-                    {"role": msg.role, "content": multimodal_content}
-                )
+                multimodal_msg: dict[str, Any] = {
+                    "role": msg.role,
+                    "content": multimodal_content,
+                }
+                if msg.reasoning_content is not None:
+                    multimodal_msg["reasoning_content"] = msg.reasoning_content
+                chat_template_messages.append(multimodal_msg)
                 continue
             msg_copy = msg.model_copy(update={"content": content})
 
@@ -168,6 +172,8 @@ async def chat_request_to_text_generation(
         min_p=request.min_p,
         repetition_penalty=request.repetition_penalty,
         repetition_context_size=request.repetition_context_size,
+        presence_penalty=request.presence_penalty,
+        frequency_penalty=request.frequency_penalty,
         images=images,
     )
 

src/exo/api/adapters/responses.py

@@ -113,6 +113,23 @@ def _extract_content(content: str | list[ResponseContentPart]) -> str:
     )
 
 
+def _append_tool_call(
+    chat_template_messages: list[dict[str, Any]], tool_call: dict[str, Any]
+) -> None:
+    if chat_template_messages:
+        prev = chat_template_messages[-1]
+        if prev.get("role") == "assistant" and isinstance(prev.get("content"), str):
+            existing: list[dict[str, Any]] | None = prev.get("tool_calls")
+            if existing is None:
+                prev["tool_calls"] = [tool_call]
+            else:
+                existing.append(tool_call)
+            return
+    chat_template_messages.append(
+        {"role": "assistant", "content": "", "tool_calls": [tool_call]}
+    )
+
+
 async def responses_request_to_text_generation(
     request: ResponsesRequest,
 ) -> TextGenerationTaskParams:
@@ -182,59 +199,44 @@ async def responses_request_to_text_generation(
                     | McpCallInputItem()
                     | CustomToolCallInputItem()
                 ):
-                    chat_template_messages.append(
+                    _append_tool_call(
+                        chat_template_messages,
                         {
-                            "role": "assistant",
-                            "content": "",
-                            "tool_calls": [
-                                {
-                                    "id": item.call_id,
-                                    "type": "function",
-                                    "function": {
-                                        "name": item.name,
-                                        "arguments": item.arguments,
-                                    },
-                                }
-                            ],
-                        }
+                            "id": item.call_id,
+                            "type": "function",
+                            "function": {
+                                "name": item.name,
+                                "arguments": item.arguments,
+                            },
+                        },
                     )
                 case (
                     LocalShellCallInputItem()
                     | ShellCallInputItem()
                     | ComputerCallInputItem()
                 ):
-                    chat_template_messages.append(
+                    _append_tool_call(
+                        chat_template_messages,
                         {
-                            "role": "assistant",
-                            "content": "",
-                            "tool_calls": [
-                                {
-                                    "id": item.call_id,
-                                    "type": "function",
-                                    "function": {
-                                        "name": item.type,
-                                        "arguments": json.dumps(item.action),
-                                    },
-                                }
-                            ],
-                        }
+                            "id": item.call_id,
+                            "type": "function",
+                            "function": {
+                                "name": item.type,
+                                "arguments": json.dumps(item.action),
+                            },
+                        },
                     )
                 case ApplyPatchCallInputItem():
-                    chat_template_messages.append(
+                    _append_tool_call(
+                        chat_template_messages,
                         {
-                            "role": "assistant",
-                            "content": "",
-                            "tool_calls": [
-                                {
-                                    "id": item.call_id,
-                                    "type": "function",
-                                    "function": {
-                                        "name": "apply_patch",
-                                        "arguments": json.dumps({"patch": item.patch}),
-                                    },
-                                }
-                            ],
-                        }
+                            "id": item.call_id,
+                            "type": "function",
+                            "function": {
+                                "name": "apply_patch",
+                                "arguments": json.dumps({"patch": item.patch}),
+                            },
+                        },
                     )
                 case (
                     WebSearchCallInputItem()
@@ -254,21 +256,16 @@ async def responses_request_to_text_generation(
                         args = {"prompt": item.prompt}
                     else:
                         args = {"query": item.query}
-                    chat_template_messages.append(
+                    _append_tool_call(
+                        chat_template_messages,
                         {
-                            "role": "assistant",
-                            "content": "",
-                            "tool_calls": [
-                                {
-                                    "id": item.call_id,
-                                    "type": "function",
-                                    "function": {
-                                        "name": item.type,
-                                        "arguments": json.dumps(args),
-                                    },
-                                }
-                            ],
-                        }
+                            "id": item.call_id,
+                            "type": "function",
+                            "function": {
+                                "name": item.type,
+                                "arguments": json.dumps(args),
+                            },
+                        },
                     )
                 case (
                     FunctionCallOutputInputItem()
@@ -320,21 +317,16 @@ async def responses_request_to_text_generation(
                             }
                         )
                 case McpApprovalRequestInputItem():
-                    chat_template_messages.append(
+                    _append_tool_call(
+                        chat_template_messages,
                         {
-                            "role": "assistant",
-                            "content": "",
-                            "tool_calls": [
-                                {
-                                    "id": item.call_id,
-                                    "type": "function",
-                                    "function": {
-                                        "name": item.name,
-                                        "arguments": item.arguments,
-                                    },
-                                }
-                            ],
-                        }
+                            "id": item.call_id,
+                            "type": "function",
+                            "function": {
+                                "name": item.name,
+                                "arguments": item.arguments,
+                            },
+                        },
                     )
                 case McpApprovalResponseInputItem():
                     chat_template_messages.append(

src/exo/api/main.py

@@ -79,6 +79,8 @@ from exo.api.types import (
     ImageListItem,
     ImageListResponse,
     ImageSize,
+    InstanceLinkBody,
+    InstanceLinkResponse,
     ModelList,
     ModelListModel,
     PlaceInstanceParams,
@@ -122,6 +124,7 @@ from exo.master.placement import place_instance as get_instance_placements
 from exo.shared.apply import apply
 from exo.shared.constants import (
     DASHBOARD_DIR,
+    ENABLE_DISAGGREGATION,
     EXO_CACHE_HOME,
     EXO_EVENT_LOG_DIR,
     EXO_IMAGE_CACHE_DIR,
@@ -154,6 +157,7 @@ from exo.shared.types.commands import (
     DeleteCustomModelCard,
     DeleteDownload,
     DeleteInstance,
+    DeleteInstanceLink,
     DownloadCommand,
     ForwarderCommand,
     ForwarderDownloadCommand,
@@ -161,6 +165,7 @@ from exo.shared.types.commands import (
     ImageGeneration,
     PlaceInstance,
     SendInputChunk,
+    SetInstanceLink,
     StartDownload,
     TaskCancelled,
     TaskFinished,
@@ -174,6 +179,7 @@ from exo.shared.types.events import (
     InstanceDeleted,
     TracesMerged,
 )
+from exo.shared.types.instance_link import InstanceLink, InstanceLinkId
 from exo.shared.types.memory import Memory
 from exo.shared.types.state import State
 from exo.shared.types.tasks import (
@@ -185,7 +191,10 @@ from exo.shared.types.tasks import (
 from exo.shared.types.tasks import (
     TextGeneration as TextGenerationTask,
 )
-from exo.shared.types.text_generation import Base64Image, TextGenerationTaskParams
+from exo.shared.types.text_generation import (
+    Base64ImageHash,
+    TextGenerationTaskParams,
+)
 from exo.shared.types.worker.downloads import DownloadCompleted
 from exo.shared.types.worker.instances import Instance, InstanceId, InstanceMeta
 from exo.shared.types.worker.shards import Sharding
@@ -212,6 +221,17 @@ def _ensure_seed(params: AdvancedImageParams | None) -> AdvancedImageParams:
     return params
 
 
+def _require_disaggregation_enabled() -> None:
+    if not ENABLE_DISAGGREGATION:
+        raise HTTPException(
+            status_code=HTTPStatus.NOT_FOUND,
+            detail=(
+                "Prefill/decode disaggregation is disabled. "
+                "Set ENABLE_DISAGGREGATION=true to enable."
+            ),
+        )
+
+
 class API:
     def __init__(
         self,
@@ -234,6 +254,7 @@ class API:
         self.node_id: NodeId = node_id
         self.last_completed_election: int = 0
         self.port = port
+        self._sent_image_hashes: set[str] = set()
 
         self.paused: bool = False
         self.paused_ev: anyio.Event = anyio.Event()
@@ -283,6 +304,7 @@ class API:
         self.event_receiver.close()
         self.event_receiver = event_receiver
         self._tg.start_soon(self._apply_state)
+        self._sent_image_hashes = set()
 
     def unpause(self, result_clock: int):
         logger.info("Unpausing API")
@@ -323,6 +345,11 @@ class API:
         self.app.get("/instance/previews")(self.get_placement_previews)
         self.app.get("/instance/{instance_id}")(self.get_instance)
         self.app.delete("/instance/{instance_id}")(self.delete_instance)
+        self.app.get("/v1/instance-links")(self.list_instance_links)
+        self.app.post("/v1/instance-links")(self.create_instance_link)
+        self.app.put("/v1/instance-links/{link_id}")(self.update_instance_link)
+        self.app.delete("/v1/instance-links/{link_id}")(self.delete_instance_link)
+        self.app.get("/v1/feature-flags")(self.get_feature_flags)
         self.app.get("/models")(self.get_models)
         self.app.get("/v1/models")(self.get_models)
         self.app.post("/models/add")(self.add_custom_model)
@@ -331,7 +358,9 @@ class API:
         self.app.post("/v1/chat/completions", response_model=None)(
             self.chat_completions
         )
-        self.app.post("/bench/chat/completions")(self.bench_chat_completions)
+        self.app.post("/bench/chat/completions", response_model=None)(
+            self.bench_chat_completions
+        )
         self.app.post("/v1/images/generations", response_model=None)(
             self.image_generations
         )
@@ -610,6 +639,49 @@ class API:
             instance_id=instance_id,
         )
 
+    async def get_feature_flags(self) -> dict[str, bool]:
+        return {"disaggregation": ENABLE_DISAGGREGATION}
+
+    async def list_instance_links(self) -> list[InstanceLink]:
+        if not ENABLE_DISAGGREGATION:
+            return []
+        return list(self.state.instance_links.values())
+
+    async def create_instance_link(
+        self, body: InstanceLinkBody
+    ) -> InstanceLinkResponse:
+        _require_disaggregation_enabled()
+        return await self._set_instance_link(InstanceLinkId(), body)
+
+    async def update_instance_link(
+        self, link_id: InstanceLinkId, body: InstanceLinkBody
+    ) -> InstanceLinkResponse:
+        _require_disaggregation_enabled()
+        return await self._set_instance_link(link_id, body)
+
+    async def _set_instance_link(
+        self, link_id: InstanceLinkId, body: InstanceLinkBody
+    ) -> InstanceLinkResponse:
+        command = SetInstanceLink(
+            link_id=link_id,
+            prefill_instances=list(body.prefill_instances),
+            decode_instances=list(body.decode_instances),
+        )
+        await self._send(command)
+        return InstanceLinkResponse(
+            message="Command received.", command_id=command.command_id
+        )
+
+    async def delete_instance_link(
+        self, link_id: InstanceLinkId
+    ) -> InstanceLinkResponse:
+        _require_disaggregation_enabled()
+        command = DeleteInstanceLink(link_id=link_id)
+        await self._send(command)
+        return InstanceLinkResponse(
+            message="Command received.", command_id=command.command_id
+        )
+
     async def cancel_command(self, command_id: CommandId) -> CancelCommandResponse:
         """Cancel an active command by closing its stream and notifying workers."""
         sender = self._text_generation_queues.get(
@@ -737,8 +809,6 @@ class API:
             "TODO: we should send a notification to the user to download the model"
         )
 
-    _sent_image_hashes: set[str] = set()
-
     async def _send_text_generation_with_images(
         self, task_params: TextGenerationTaskParams
     ) -> TextGeneration:
@@ -750,23 +820,19 @@ class API:
             return command
 
         hashes = [hashlib.sha256(img.encode("ascii")).hexdigest() for img in images]
+        all_hashes = {idx: Base64ImageHash(h) for idx, h in enumerate(hashes)}
+        task_params = task_params.model_copy(
+            update={"images": [], "image_hashes": all_hashes}
+        )
+        command = TextGeneration(task_params=task_params)
 
-        cached_hashes: dict[int, str] = {}
         new_images: list[tuple[int, str]] = []
         for idx, (img, h) in enumerate(zip(images, hashes, strict=True)):
-            if h in self._sent_image_hashes:
-                cached_hashes[idx] = h
-            else:
+            if h not in self._sent_image_hashes:
                 self._sent_image_hashes.add(h)
                 new_images.append((idx, img))
 
-        wrapped_hashes = {idx: Base64Image(h) for idx, h in cached_hashes.items()}
-
         if not new_images:
-            task_params = task_params.model_copy(
-                update={"images": [], "image_hashes": wrapped_hashes}
-            )
-            command = TextGeneration(task_params=task_params)
             await self._send(command)
             return command
 
@@ -775,16 +841,6 @@ class API:
             for i in range(0, len(img_data), EXO_MAX_CHUNK_SIZE):
                 all_chunks.append((img_idx, img_data[i : i + EXO_MAX_CHUNK_SIZE]))
 
-        task_params = task_params.model_copy(
-            update={
-                "images": [],
-                "image_hashes": wrapped_hashes,
-                "total_input_chunks": len(all_chunks),
-                "image_count": len(new_images),
-            }
-        )
-        command = TextGeneration(task_params=task_params)
-
         for global_idx, (img_idx, chunk_data) in enumerate(all_chunks):
             await self._send(
                 SendInputChunk(
@@ -840,7 +896,7 @@ class API:
 
     async def bench_chat_completions(
         self, payload: BenchChatCompletionRequest
-    ) -> BenchChatCompletionResponse:
+    ) -> BenchChatCompletionResponse | StreamingResponse:
         task_params = await chat_request_to_text_generation(payload)
         resolved_model = await self._resolve_and_validate_text_model(
             ModelId(task_params.model)
@@ -857,6 +913,22 @@ class API:
 
         command = await self._send_text_generation_with_images(task_params)
 
+        if payload.stream:
+            return StreamingResponse(
+                with_sse_keepalive(
+                    generate_chat_stream(
+                        command.command_id,
+                        self._token_chunk_stream(command.command_id),
+                    ),
+                ),
+                media_type="text/event-stream",
+                headers={
+                    "Cache-Control": "no-cache",
+                    "Connection": "close",
+                    "X-Accel-Buffering": "no",
+                },
+            )
+
         return await self._collect_text_generation_with_stats(command.command_id)
 
     async def _resolve_and_validate_text_model(self, model_id: ModelId) -> ModelId:
@@ -1674,6 +1746,7 @@ class API:
                     quantization=card.quantization,
                     base_model=card.base_model,
                     capabilities=card.capabilities,
+                    reasoning_dialect=card.reasoning_dialect,
                     context_length=card.context_length,
                 )
                 for card in cards

src/exo/api/types/__init__.py

@@ -34,6 +34,8 @@ from .api import ImageGenerationTaskParams as ImageGenerationTaskParams
 from .api import ImageListItem as ImageListItem
 from .api import ImageListResponse as ImageListResponse
 from .api import ImageSize as ImageSize
+from .api import InstanceLinkBody as InstanceLinkBody
+from .api import InstanceLinkResponse as InstanceLinkResponse
 from .api import Logprobs as Logprobs
 from .api import LogprobsContentItem as LogprobsContentItem
 from .api import ModelList as ModelList

src/exo/api/types/api.py

@@ -8,7 +8,7 @@ from pydantic import BaseModel, Field, field_validator
 from exo.shared.models.model_cards import ModelCard, ModelId
 from exo.shared.types.common import CommandId, NodeId
 from exo.shared.types.memory import Memory
-from exo.shared.types.text_generation import ReasoningEffort
+from exo.shared.types.text_generation import ReasoningDialect, ReasoningEffort
 from exo.shared.types.worker.instances import Instance, InstanceId, InstanceMeta
 from exo.shared.types.worker.shards import Sharding, ShardMetadata
 from exo.utils.pydantic_ext import FrozenModel
@@ -48,6 +48,7 @@ class ModelListModel(BaseModel):
     quantization: str = Field(default="")
     base_model: str = Field(default="")
     capabilities: list[str] = Field(default_factory=list)
+    reasoning_dialect: ReasoningDialect = "none"
 
 
 class ModelList(BaseModel):
@@ -295,6 +296,16 @@ class CancelCommandResponse(BaseModel):
     command_id: CommandId
 
 
+class InstanceLinkBody(BaseModel):
+    prefill_instances: list[InstanceId]
+    decode_instances: list[InstanceId]
+
+
+class InstanceLinkResponse(BaseModel):
+    message: str
+    command_id: CommandId
+
+
 ImageSize = Literal[
     "auto",
     "512x512",