fix: ruff lint and formatting for e2e test files

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

.dockerignore

@@ -0,0 +1,15 @@
+.venv/
+.direnv/
+target/
+.git/
+.idea/
+.pytest_cache/
+.ruff_cache/
+dashboard/node_modules/
+dashboard/.svelte-kit/
+dashboard/build/
+dist/
+*.pdb
+**/__pycache__
+**/.DS_Store
+.mlx_typings/

.github/workflows/e2e.yml

@@ -0,0 +1,29 @@
+name: e2e-tests
+
+on:
+  push:
+  pull_request:
+    branches:
+      - staging
+      - main
+
+jobs:
+  e2e:
+    runs-on: ubuntu-latest
+    timeout-minutes: 30
+    steps:
+      - name: Free up disk space
+        run: |
+          sudo rm -rf /usr/share/dotnet /usr/local/lib/android /opt/ghc \
+            /opt/hostedtoolcache /usr/local/share/boost /usr/share/swift \
+            /opt/microsoft /opt/az
+          docker system prune -af
+          df -h /
+
+      - name: Checkout repository
+        uses: actions/checkout@v4
+        with:
+          lfs: false
+
+      - name: Run E2E tests
+        run: python3 e2e/run_all.py

.mlx_typings/mlx_lm/models/step3p5.pyi

@@ -1,151 +0,0 @@
-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 .switch_layers import SwitchGLU
-
-@dataclass
-class ModelArgs(BaseModelArgs):
-    model_type: str
-    hidden_size: int
-    num_hidden_layers: int
-    vocab_size: int
-    num_attention_heads: int
-    num_attention_groups: int
-    head_dim: int
-    intermediate_size: int
-    rms_norm_eps: float
-    rope_theta: float
-    rope_scaling: Optional[Dict[str, Any]]
-    max_position_embeddings: int
-    sliding_window: int
-    layer_types: Optional[List[str]]
-    yarn_only_types: Optional[List[str]]
-    partial_rotary_factors: Optional[List[float]]
-    attention_other_setting: Optional[Dict[str, Any]]
-    use_head_wise_attn_gate: bool
-    moe_num_experts: int
-    moe_top_k: int
-    moe_intermediate_size: int
-    share_expert_dim: int
-    moe_layers_enum: Optional[str]
-    moe_router_scaling_factor: float
-    norm_expert_weight: bool
-    swiglu_limits: Optional[List[float]]
-    swiglu_limits_shared: Optional[List[float]]
-    tie_word_embeddings: bool
-
-class Step3p5MLP(nn.Module):
-    hidden_size: int
-    intermediate_size: int
-    gate_proj: nn.Linear
-    up_proj: nn.Linear
-    down_proj: nn.Linear
-    limit: Optional[float]
-
-    def __init__(
-        self, args: ModelArgs, intermediate_size: int, swiglu_limit: float = 0
-    ) -> None: ...
-    def __call__(self, x: mx.array) -> mx.array: ...
-
-class Step3p5MoEGate(nn.Module):
-    top_k: int
-    n_routed_experts: int
-    routed_scaling_factor: float
-    norm_topk_prob: bool
-    gate: nn.Linear
-    router_bias: mx.array
-
-    def __init__(self, args: ModelArgs) -> None: ...
-    def __call__(self, x: mx.array) -> tuple[mx.array, mx.array]: ...
-
-class Step3p5MoE(nn.Module):
-    gate: Step3p5MoEGate
-    switch_mlp: SwitchGLU
-    share_expert: Step3p5MLP
-    sharding_group: Optional[mx.distributed.Group]
-
-    def __init__(self, args: ModelArgs, layer_idx: int) -> None: ...
-    def __call__(self, x: mx.array) -> mx.array: ...
-
-class Step3p5Attention(nn.Module):
-    is_sliding: bool
-    num_heads: int
-    num_kv_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
-    use_head_wise_attn_gate: bool
-    g_proj: nn.Linear
-    rope: nn.Module
-
-    def __init__(self, args: ModelArgs, layer_idx: int) -> None: ...
-    def __call__(
-        self,
-        x: mx.array,
-        mask: Optional[mx.array] = None,
-        cache: Optional[Any] = None,
-    ) -> mx.array: ...
-
-class Step3p5DecoderLayer(nn.Module):
-    self_attn: Step3p5Attention
-    is_sliding: bool
-    is_moe_layer: bool
-    mlp: Step3p5MLP | Step3p5MoE
-    input_layernorm: nn.Module
-    post_attention_layernorm: nn.Module
-
-    def __init__(self, args: ModelArgs, layer_idx: int) -> None: ...
-    def __call__(
-        self,
-        x: mx.array,
-        mask: Optional[mx.array] = None,
-        cache: Optional[Any] = None,
-    ) -> mx.array: ...
-
-class Step3p5Model(nn.Module):
-    args: ModelArgs
-    vocab_size: int
-    num_layers: int
-    embed_tokens: nn.Embedding
-    layers: list[Step3p5DecoderLayer]
-    norm: nn.Module
-    _swa_idx: Optional[int]
-    _full_idx: Optional[int]
-
-    def __init__(self, args: ModelArgs) -> None: ...
-    def __call__(
-        self,
-        x: mx.array,
-        cache: Optional[List[Any]] = None,
-    ) -> mx.array: ...
-
-class Model(nn.Module):
-    args: ModelArgs
-    model_type: str
-    model: Step3p5Model
-    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 shard(self, group: Optional[mx.distributed.Group] = None) -> None: ...
-    @property
-    def layers(self) -> list[Step3p5DecoderLayer]: ...
-    def make_cache(self) -> list[Any]: ...
-    @property
-    def cast_predicate(self) -> Any: ...
-    @property
-    def quant_predicate(self) -> Any: ...

e2e/Dockerfile

@@ -0,0 +1,53 @@
+# Stage 1: Build the dashboard
+FROM node:22-slim AS dashboard
+WORKDIR /app/dashboard
+COPY dashboard/package.json dashboard/package-lock.json ./
+RUN npm ci
+COPY dashboard/ .
+RUN npm run build
+
+# Stage 2: Build and run exo
+FROM python:3.13-slim
+
+# Install system dependencies
+RUN apt-get update && apt-get install -y \
+    build-essential \
+    pkg-config \
+    libssl-dev \
+    curl \
+    protobuf-compiler \
+    iptables \
+    && rm -rf /var/lib/apt/lists/*
+
+# Install Rust nightly
+RUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y --default-toolchain nightly
+ENV PATH="/root/.cargo/bin:${PATH}"
+
+# Install uv
+COPY --from=ghcr.io/astral-sh/uv:latest /uv /usr/local/bin/uv
+
+WORKDIR /app
+
+# Copy dependency files first for better layer caching
+COPY pyproject.toml Cargo.toml uv.lock README.md ./
+COPY rust/ ./rust/
+COPY bench/pyproject.toml ./bench/pyproject.toml
+
+# Copy source and resources
+COPY src/ ./src/
+COPY resources/ ./resources/
+
+# Copy built dashboard from stage 1
+COPY --from=dashboard /app/dashboard/build ./dashboard/build/
+
+# Install Python deps and build Rust bindings, then clean up build artifacts
+# to keep the layer small (Rust target/ and cargo registry can be 1-2 GB)
+RUN uv sync && rm -rf /app/rust/target /root/.cargo/registry /root/.cargo/git
+
+# Wrap g++ with -fpermissive to fix MLX CPU JIT compilation with GCC 14
+# (GCC 14 treats _Float128/_Float32/_Float64 as built-in types, conflicting with MLX-generated code)
+RUN mv /usr/bin/g++ /usr/bin/g++.real && \
+    printf '#!/bin/sh\nexec /usr/bin/g++.real -fpermissive "$@"\n' > /usr/bin/g++ && \
+    chmod +x /usr/bin/g++
+
+CMD [".venv/bin/exo", "-v"]

e2e/conftest.py

@@ -0,0 +1,182 @@
+"""Shared E2E test infrastructure for exo cluster tests."""
+
+import asyncio
+import json
+import os
+import sys
+from pathlib import Path
+from urllib.error import URLError
+from urllib.request import Request, urlopen
+
+E2E_DIR = Path(__file__).parent.resolve()
+TIMEOUT = int(os.environ.get("E2E_TIMEOUT", "120"))
+
+
+class Cluster:
+    """Async wrapper around a docker compose exo cluster."""
+
+    def __init__(self, name: str, overrides: list[str] | None = None):
+        self.name = name
+        self.project = f"e2e-{name}"
+        compose_files = [str(E2E_DIR / "docker-compose.yml")]
+        for path in overrides or []:
+            compose_files.append(str(E2E_DIR / path))
+        self._compose_base = [
+            "docker",
+            "compose",
+            "-p",
+            self.project,
+            *[arg for f in compose_files for arg in ("-f", f)],
+        ]
+
+    async def __aenter__(self):
+        return self
+
+    async def __aexit__(self, *exc):
+        await self.stop()
+
+    async def _run(self, *args: str, check: bool = True) -> str:
+        proc = await asyncio.create_subprocess_exec(
+            *self._compose_base,
+            *args,
+            stdout=asyncio.subprocess.PIPE,
+            stderr=asyncio.subprocess.STDOUT,
+        )
+        stdout, _ = await proc.communicate()
+        output = stdout.decode()
+        if check and proc.returncode != 0:
+            print(output, file=sys.stderr)
+            raise RuntimeError(
+                f"docker compose {' '.join(args)} failed (rc={proc.returncode})"
+            )
+        return output
+
+    async def build(self):
+        print("  Building images...")
+        await self._run("build", "--quiet")
+
+    async def start(self):
+        print("  Starting cluster...")
+        await self._run("up", "-d")
+
+    async def stop(self):
+        print("  Cleaning up...")
+        await self._run("down", "--timeout", "5", check=False)
+
+    async def logs(self) -> str:
+        return await self._run("logs", check=False)
+
+    async def exec(
+        self, service: str, *cmd: str, check: bool = True
+    ) -> tuple[int, str]:
+        """Run a command inside a running container. Returns (returncode, output)."""
+        proc = await asyncio.create_subprocess_exec(
+            *self._compose_base,
+            "exec",
+            "-T",
+            service,
+            *cmd,
+            stdout=asyncio.subprocess.PIPE,
+            stderr=asyncio.subprocess.STDOUT,
+        )
+        stdout, _ = await proc.communicate()
+        output = stdout.decode()
+        if check and proc.returncode != 0:
+            raise RuntimeError(
+                f"exec {' '.join(cmd)} in {service} failed (rc={proc.returncode})"
+            )
+        return proc.returncode, output
+
+    async def wait_for(self, description: str, check_fn, timeout: int = TIMEOUT):
+        """Poll check_fn every 2s until it returns True or timeout expires."""
+        print(f"  Waiting for {description}...")
+        deadline = asyncio.get_event_loop().time() + timeout
+        while asyncio.get_event_loop().time() < deadline:
+            if await check_fn():
+                print(f"  {description}")
+                return
+            await asyncio.sleep(2)
+        output = await self.logs()
+        print(f"--- cluster logs ---\n{output}\n---", file=sys.stderr)
+        raise TimeoutError(f"Timed out waiting for {description}")
+
+    async def assert_healthy(self):
+        """Verify the cluster formed correctly: nodes started, discovered each other, elected a master, API responds."""
+
+        async def both_nodes_started():
+            log = await self.logs()
+            return log.count("Starting node") >= 2
+
+        async def nodes_discovered():
+            log = await self.logs()
+            return log.count("ConnectionMessageType.Connected") >= 2
+
+        async def master_elected():
+            log = await self.logs()
+            return "demoting self" in log
+
+        async def api_responding():
+            try:
+                with urlopen("http://localhost:52415/v1/models", timeout=3) as resp:
+                    return resp.status == 200
+            except (URLError, OSError):
+                return False
+
+        await self.wait_for("Both nodes started", both_nodes_started)
+        await self.wait_for("Nodes discovered each other", nodes_discovered)
+        await self.wait_for("Master election resolved", master_elected)
+        await self.wait_for("API responding", api_responding)
+
+    async def _api(
+        self, method: str, path: str, body: dict | None = None, timeout: int = 30
+    ) -> dict:
+        """Make an API request to the cluster. Returns parsed JSON."""
+        url = f"http://localhost:52415{path}"
+        data = json.dumps(body).encode() if body else None
+        req = Request(
+            url, data=data, headers={"Content-Type": "application/json"}, method=method
+        )
+        loop = asyncio.get_event_loop()
+        resp_bytes = await loop.run_in_executor(
+            None, lambda: urlopen(req, timeout=timeout).read()
+        )
+        return json.loads(resp_bytes)
+
+    async def place_model(self, model: str, timeout: int = 600):
+        """Place a model instance on the cluster (triggers download) and wait until it's ready."""
+        await self._api("POST", "/place_instance", {"model_id": model})
+
+        async def model_ready():
+            try:
+                resp = await self._api("GET", "/v1/models")
+                return any(m.get("id") == model for m in resp.get("data", []))
+            except Exception:
+                return False
+
+        await self.wait_for(f"Model {model} ready", model_ready, timeout=timeout)
+
+    async def chat(
+        self, model: str, messages: list[dict], timeout: int = 600, **kwargs
+    ) -> dict:
+        """Send a chat completion request. Retries until model is downloaded and inference completes."""
+        body = json.dumps({"model": model, "messages": messages, **kwargs}).encode()
+        deadline = asyncio.get_event_loop().time() + timeout
+        last_error = None
+
+        while asyncio.get_event_loop().time() < deadline:
+            try:
+                req = Request(
+                    "http://localhost:52415/v1/chat/completions",
+                    data=body,
+                    headers={"Content-Type": "application/json"},
+                )
+                loop = asyncio.get_event_loop()
+                resp_bytes = await loop.run_in_executor(
+                    None, lambda r=req: urlopen(r, timeout=300).read()
+                )
+                return json.loads(resp_bytes)
+            except Exception as e:
+                last_error = e
+                await asyncio.sleep(5)
+
+        raise TimeoutError(f"Chat request failed after {timeout}s: {last_error}")

e2e/docker-compose.yml

@@ -0,0 +1,18 @@
+services:
+  exo-node-1:
+    build:
+      context: ..
+      dockerfile: e2e/Dockerfile
+    environment:
+      - EXO_LIBP2P_NAMESPACE=docker-e2e
+    command: [".venv/bin/exo", "-v"]
+    ports:
+      - "52415:52415"
+
+  exo-node-2:
+    build:
+      context: ..
+      dockerfile: e2e/Dockerfile
+    environment:
+      - EXO_LIBP2P_NAMESPACE=docker-e2e
+    command: [".venv/bin/exo", "-v"]

e2e/run_all.py

@@ -0,0 +1,75 @@
+#!/usr/bin/env python3
+"""Discovers and runs all E2E tests in e2e/test_*.py.
+
+Tests with '# slow' on the first line of their docstring are skipped
+unless --slow is passed or E2E_SLOW=1 is set.
+"""
+
+import os
+import subprocess
+import sys
+from pathlib import Path
+
+E2E_DIR = Path(__file__).parent.resolve()
+
+
+def is_slow(test_file: Path) -> bool:
+    """Check if the test file is marked as slow (has '# slow' in first 3 lines)."""
+    with open(test_file) as f:
+        for line in f:
+            if line.strip().startswith("#"):
+                continue
+            if line.strip().startswith('"""') or line.strip().startswith("'''"):
+                # Read into the docstring
+                for doc_line in f:
+                    if "slow" in doc_line.lower() and doc_line.strip().startswith(
+                        "slow"
+                    ):
+                        return True
+                    if '"""' in doc_line or "'''" in doc_line:
+                        break
+            break
+    return False
+
+
+def main():
+    run_slow = "--slow" in sys.argv or os.environ.get("E2E_SLOW") == "1"
+    test_files = sorted(E2E_DIR.glob("test_*.py"))
+    if not test_files:
+        print("No test files found")
+        sys.exit(1)
+
+    passed = 0
+    failed = 0
+    skipped = 0
+    failures = []
+
+    for test_file in test_files:
+        name = test_file.stem
+        if is_slow(test_file) and not run_slow:
+            print(f"=== {name} === SKIPPED (slow, use --slow to run)")
+            skipped += 1
+            continue
+
+        print(f"=== {name} ===")
+        result = subprocess.run([sys.executable, str(test_file)])
+        if result.returncode == 0:
+            passed += 1
+        else:
+            failed += 1
+            failures.append(name)
+        print()
+
+    total = passed + failed + skipped
+    print("================================")
+    print(
+        f"{passed}/{total} tests passed" + (f", {skipped} skipped" if skipped else "")
+    )
+
+    if failed:
+        print(f"Failed: {' '.join(failures)}")
+        sys.exit(1)
+
+
+if __name__ == "__main__":
+    main()

e2e/snapshots/inference.json

@@ -0,0 +1,8 @@
+{
+  "model": "mlx-community/Qwen3-0.6B-4bit",
+  "seed": 42,
+  "temperature": 0,
+  "prompt": "What is 2+2? Reply with just the number.",
+  "max_tokens": 32,
+  "content": "<think>\nOkay, so I need to figure out what 2+2 is. Let me think. Well, if you add 2 and 2 together"
+}

e2e/test_cluster_formation.py

@@ -0,0 +1,22 @@
+"""Test: Basic cluster formation.
+
+Verifies two nodes discover each other, elect a master, and the API responds.
+"""
+
+import asyncio
+import sys
+
+sys.path.insert(0, str(__import__("pathlib").Path(__file__).parent))
+from conftest import Cluster
+
+
+async def main():
+    async with Cluster("cluster_formation") as cluster:
+        await cluster.build()
+        await cluster.start()
+        await cluster.assert_healthy()
+        print("PASSED: cluster_formation")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

e2e/test_inference_snapshot.py

@@ -0,0 +1,82 @@
+"""Test: Deterministic inference output (snapshot test).
+slow
+
+Sends a chat completion request with a fixed seed and temperature=0,
+then verifies the output matches a known-good snapshot. This ensures
+inference produces consistent results across runs.
+
+Requires a machine that can run MLX inference at reasonable speed (Apple Silicon).
+Run with: python3 e2e/run_all.py --slow  or  E2E_SLOW=1 python3 e2e/run_all.py
+"""
+
+import asyncio
+import json
+import sys
+from pathlib import Path
+
+sys.path.insert(0, str(Path(__file__).parent))
+from conftest import Cluster
+
+MODEL = "mlx-community/Qwen3-0.6B-4bit"
+SEED = 42
+PROMPT = "What is 2+2? Reply with just the number."
+MAX_TOKENS = 32
+SNAPSHOT_FILE = Path(__file__).parent / "snapshots" / "inference.json"
+
+
+async def main():
+    async with Cluster("inference_snapshot") as cluster:
+        await cluster.build()
+        await cluster.start()
+        await cluster.assert_healthy()
+
+        # Launch the model instance (triggers download + placement)
+        print(f"  Launching model {MODEL}...")
+        await cluster.place_model(MODEL)
+
+        print(f"  Sending chat completion (seed={SEED}, temperature=0)...")
+        resp = await cluster.chat(
+            model=MODEL,
+            messages=[{"role": "user", "content": PROMPT}],
+            seed=SEED,
+            temperature=0,
+            max_tokens=MAX_TOKENS,
+        )
+
+        content = resp["choices"][0]["message"]["content"]
+        print(f"  Response: {content!r}")
+
+        # Load or create snapshot
+        if SNAPSHOT_FILE.exists():
+            snapshot = json.loads(SNAPSHOT_FILE.read_text())
+            expected = snapshot["content"]
+            assert content == expected, (
+                f"Snapshot mismatch!\n"
+                f"  Expected: {expected!r}\n"
+                f"  Got:      {content!r}\n"
+                f"  Delete {SNAPSHOT_FILE} to regenerate."
+            )
+            print("  Output matches snapshot")
+        else:
+            SNAPSHOT_FILE.parent.mkdir(parents=True, exist_ok=True)
+            SNAPSHOT_FILE.write_text(
+                json.dumps(
+                    {
+                        "model": MODEL,
+                        "seed": SEED,
+                        "temperature": 0,
+                        "prompt": PROMPT,
+                        "max_tokens": MAX_TOKENS,
+                        "content": content,
+                    },
+                    indent=2,
+                )
+                + "\n"
+            )
+            print(f"  Snapshot created: {SNAPSHOT_FILE}")
+
+        print("PASSED: inference_snapshot")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

e2e/test_no_internet.py

@@ -0,0 +1,47 @@
+"""Test: Cluster works without internet access.
+
+Verifies exo functions correctly when containers can talk to each other
+but cannot reach the internet. Uses iptables to block all outbound traffic
+except private subnets and multicast (for mDNS discovery).
+"""
+
+import asyncio
+import sys
+
+sys.path.insert(0, str(__import__("pathlib").Path(__file__).parent))
+from conftest import Cluster
+
+
+async def main():
+    async with Cluster(
+        "no_internet",
+        overrides=["tests/no_internet/docker-compose.override.yml"],
+    ) as cluster:
+        await cluster.build()
+        await cluster.start()
+        await cluster.assert_healthy()
+
+        # Verify internet is actually blocked from inside the containers
+        for node in ["exo-node-1", "exo-node-2"]:
+            rc, _ = await cluster.exec(
+                node,
+                "curl",
+                "-sf",
+                "--max-time",
+                "3",
+                "https://huggingface.co",
+                check=False,
+            )
+            assert rc != 0, f"{node} should not be able to reach the internet"
+            print(f"  {node}: internet correctly blocked")
+
+        # Verify exo detected no internet connectivity
+        log = await cluster.logs()
+        assert "Internet connectivity: False" in log, "exo should detect no internet"
+        print("  exo correctly detected no internet connectivity")
+
+        print("PASSED: no_internet")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

e2e/tests/no_internet/docker-compose.override.yml

@@ -0,0 +1,32 @@
+# Block all outbound internet traffic using iptables while preserving:
+#   - Multicast (224.0.0.0/4) for mDNS peer discovery
+#   - Private subnets (10/8, 172.16/12, 192.168/16) for inter-container communication
+#   - Loopback (127/8)
+# Requires NET_ADMIN capability for iptables.
+services:
+  exo-node-1:
+    cap_add:
+      - NET_ADMIN
+    entrypoint: ["/bin/sh", "-c"]
+    command:
+      - |
+        iptables -A OUTPUT -d 127.0.0.0/8 -j ACCEPT
+        iptables -A OUTPUT -d 10.0.0.0/8 -j ACCEPT
+        iptables -A OUTPUT -d 172.16.0.0/12 -j ACCEPT
+        iptables -A OUTPUT -d 192.168.0.0/16 -j ACCEPT
+        iptables -A OUTPUT -d 224.0.0.0/4 -j ACCEPT
+        iptables -A OUTPUT -j REJECT
+        exec .venv/bin/exo -v
+  exo-node-2:
+    cap_add:
+      - NET_ADMIN
+    entrypoint: ["/bin/sh", "-c"]
+    command:
+      - |
+        iptables -A OUTPUT -d 127.0.0.0/8 -j ACCEPT
+        iptables -A OUTPUT -d 10.0.0.0/8 -j ACCEPT
+        iptables -A OUTPUT -d 172.16.0.0/12 -j ACCEPT
+        iptables -A OUTPUT -d 192.168.0.0/16 -j ACCEPT
+        iptables -A OUTPUT -d 224.0.0.0/4 -j ACCEPT
+        iptables -A OUTPUT -j REJECT
+        exec .venv/bin/exo -v

resources/inference_model_cards/mlx-community--Step-3.5-Flash-4bit.toml

@@ -1,12 +0,0 @@
-model_id = "mlx-community/Step-3.5-Flash-4bit"
-n_layers = 45
-hidden_size = 4096
-supports_tensor = true
-tasks = ["TextGeneration"]
-family = "step"
-quantization = "4bit"
-base_model = "Step 3.5 Flash"
-capabilities = ["text", "thinking"]
-
-[storage_size]
-in_bytes = 114572190076

resources/inference_model_cards/mlx-community--Step-3.5-Flash-6bit.toml

@@ -1,12 +0,0 @@
-model_id = "mlx-community/Step-3.5-Flash-6bit"
-n_layers = 45
-hidden_size = 4096
-supports_tensor = true
-tasks = ["TextGeneration"]
-family = "step"
-quantization = "6bit"
-base_model = "Step 3.5 Flash"
-capabilities = ["text", "thinking"]
-
-[storage_size]
-in_bytes = 159039627774

resources/inference_model_cards/mlx-community--Step-3.5-Flash-8Bit.toml

@@ -1,12 +0,0 @@
-model_id = "mlx-community/Step-3.5-Flash-8Bit"
-n_layers = 45
-hidden_size = 4096
-supports_tensor = true
-tasks = ["TextGeneration"]
-family = "step"
-quantization = "8bit"
-base_model = "Step 3.5 Flash"
-capabilities = ["text", "thinking"]
-
-[storage_size]
-in_bytes = 209082699847

src/exo/shared/models/model_cards.py

@@ -189,7 +189,6 @@ class ConfigData(BaseModel):
             ["MiniMaxM2ForCausalLM"],
             ["LlamaForCausalLM"],
             ["GptOssForCausalLM"],
-            ["Step3p5ForCausalLM"],
         ]
 
     @model_validator(mode="before")

src/exo/worker/engines/mlx/auto_parallel.py

@@ -35,9 +35,6 @@ from mlx_lm.models.qwen3_moe import Model as Qwen3MoeModel
 from mlx_lm.models.qwen3_moe import Qwen3MoeSparseMoeBlock
 from mlx_lm.models.qwen3_next import Model as Qwen3NextModel
 from mlx_lm.models.qwen3_next import Qwen3NextDecoderLayer, Qwen3NextSparseMoeBlock
-from mlx_lm.models.step3p5 import Model as Step35Model
-from mlx_lm.models.step3p5 import Step3p5MLP as Step35MLP
-from mlx_lm.models.step3p5 import Step3p5Model as Step35InnerModel
 from transformers.models.qwen3.modeling_qwen3 import Qwen3DecoderLayer
 
 from exo.shared.logging import logger
@@ -267,19 +264,6 @@ def pipeline_auto_parallel(
             )
         )
 
-    if isinstance(inner_model_instance, Step35InnerModel):
-        inner_model_instance.num_layers = len(layers)
-        sliding_layers = [
-            i for i, layer in enumerate(layers) if getattr(layer, "is_sliding", False)
-        ]
-        full_layers = [
-            i
-            for i, layer in enumerate(layers)
-            if not getattr(layer, "is_sliding", True)
-        ]
-        inner_model_instance._swa_idx = 0 if not sliding_layers else sliding_layers[0]
-        inner_model_instance._full_idx = 0 if not full_layers else full_layers[0]
-
     _set_layers(model, layers)
 
     assert isinstance(layers, list), (
@@ -443,14 +427,6 @@ def tensor_auto_parallel(
             all_to_sharded_linear_in_place,
             sharded_to_all_linear_in_place,
         )
-    elif isinstance(model, Step35Model):
-        tensor_parallel_sharding_strategy = Step35ShardingStrategy(
-            group,
-            all_to_sharded_linear,
-            sharded_to_all_linear,
-            all_to_sharded_linear_in_place,
-            sharded_to_all_linear_in_place,
-        )
     else:
         raise ValueError(f"Unsupported model type: {type(model)}")
 
@@ -1005,46 +981,3 @@ class GptOssShardingStrategy(TensorParallelShardingStrategy):
             layer.mlp.sharding_group = self.group  # pyright: ignore[reportAttributeAccessIssue]
             mx.eval(layer)
         return model
-
-
-class Step35ShardingStrategy(TensorParallelShardingStrategy):
-    def shard_model(
-        self,
-        model: nn.Module,
-        timeout_seconds: float,
-        on_timeout: TimeoutCallback | None,
-    ) -> nn.Module:
-        model = cast(Step35Model, model)
-
-        for layer in model.layers:
-            eval_with_timeout(
-                layer.parameters(), timeout_seconds / len(model.layers), on_timeout
-            )
-            layer.self_attn.q_proj = self.all_to_sharded_linear(layer.self_attn.q_proj)
-            layer.self_attn.k_proj = self.all_to_sharded_linear(layer.self_attn.k_proj)
-            layer.self_attn.v_proj = self.all_to_sharded_linear(layer.self_attn.v_proj)
-            layer.self_attn.o_proj = self.sharded_to_all_linear(layer.self_attn.o_proj)
-
-            layer.self_attn.num_heads //= self.N
-            layer.self_attn.num_kv_heads //= self.N
-
-            if getattr(layer.self_attn, "use_head_wise_attn_gate", False):
-                layer.self_attn.g_proj = self.all_to_sharded_linear(
-                    layer.self_attn.g_proj
-                )
-
-            if isinstance(layer.mlp, Step35MLP):
-                layer.mlp.gate_proj = self.all_to_sharded_linear(layer.mlp.gate_proj)
-                layer.mlp.up_proj = self.all_to_sharded_linear(layer.mlp.up_proj)
-                layer.mlp.down_proj = self.sharded_to_all_linear(layer.mlp.down_proj)
-            else:
-                layer.mlp.sharding_group = self.group
-                self.all_to_sharded_linear_in_place(layer.mlp.share_expert.gate_proj)
-                self.all_to_sharded_linear_in_place(layer.mlp.share_expert.up_proj)
-                self.sharded_to_all_linear_in_place(layer.mlp.share_expert.down_proj)
-                self.all_to_sharded_linear_in_place(layer.mlp.switch_mlp.gate_proj)
-                self.all_to_sharded_linear_in_place(layer.mlp.switch_mlp.up_proj)
-                self.sharded_to_all_linear_in_place(layer.mlp.switch_mlp.down_proj)
-
-            mx.eval(layer)
-        return model