add ability to turn on debug request logging

If `OLLAMA_DEBUG_LOG_REQUESTS` is set, then on server startup a temp
folder will be created. Upon any inference request, the body will be
logged to a file in this folder, as well as a small shell script to
"replay" the request using cURL.

This is just intended for debugging scenarios, not as something to turn
on normally.

envconfig/config.go

@@ -188,6 +188,8 @@ func LogLevel() slog.Level {
 var (
 	// FlashAttention enables the experimental flash attention feature.
 	FlashAttention = BoolWithDefault("OLLAMA_FLASH_ATTENTION")
+	// DebugLogRequests logs inference requests to disk for replay/debugging.
+	DebugLogRequests = Bool("OLLAMA_DEBUG_LOG_REQUESTS")
 	// KvCacheType is the quantization type for the K/V cache.
 	KvCacheType = String("OLLAMA_KV_CACHE_TYPE")
 	// NoHistory disables readline history.
@@ -273,26 +275,27 @@ type EnvVar struct {
 
 func AsMap() map[string]EnvVar {
 	ret := map[string]EnvVar{
-		"OLLAMA_DEBUG":             {"OLLAMA_DEBUG", LogLevel(), "Show additional debug information (e.g. OLLAMA_DEBUG=1)"},
-		"OLLAMA_FLASH_ATTENTION":   {"OLLAMA_FLASH_ATTENTION", FlashAttention(false), "Enabled flash attention"},
-		"OLLAMA_KV_CACHE_TYPE":     {"OLLAMA_KV_CACHE_TYPE", KvCacheType(), "Quantization type for the K/V cache (default: f16)"},
-		"OLLAMA_GPU_OVERHEAD":      {"OLLAMA_GPU_OVERHEAD", GpuOverhead(), "Reserve a portion of VRAM per GPU (bytes)"},
-		"OLLAMA_HOST":              {"OLLAMA_HOST", Host(), "IP Address for the ollama server (default 127.0.0.1:11434)"},
-		"OLLAMA_KEEP_ALIVE":        {"OLLAMA_KEEP_ALIVE", KeepAlive(), "The duration that models stay loaded in memory (default \"5m\")"},
-		"OLLAMA_LLM_LIBRARY":       {"OLLAMA_LLM_LIBRARY", LLMLibrary(), "Set LLM library to bypass autodetection"},
-		"OLLAMA_LOAD_TIMEOUT":      {"OLLAMA_LOAD_TIMEOUT", LoadTimeout(), "How long to allow model loads to stall before giving up (default \"5m\")"},
-		"OLLAMA_MAX_LOADED_MODELS": {"OLLAMA_MAX_LOADED_MODELS", MaxRunners(), "Maximum number of loaded models per GPU"},
-		"OLLAMA_MAX_QUEUE":         {"OLLAMA_MAX_QUEUE", MaxQueue(), "Maximum number of queued requests"},
-		"OLLAMA_MODELS":            {"OLLAMA_MODELS", Models(), "The path to the models directory"},
-		"OLLAMA_NOHISTORY":         {"OLLAMA_NOHISTORY", NoHistory(), "Do not preserve readline history"},
-		"OLLAMA_NOPRUNE":           {"OLLAMA_NOPRUNE", NoPrune(), "Do not prune model blobs on startup"},
-		"OLLAMA_NUM_PARALLEL":      {"OLLAMA_NUM_PARALLEL", NumParallel(), "Maximum number of parallel requests"},
-		"OLLAMA_ORIGINS":           {"OLLAMA_ORIGINS", AllowedOrigins(), "A comma separated list of allowed origins"},
-		"OLLAMA_SCHED_SPREAD":      {"OLLAMA_SCHED_SPREAD", SchedSpread(), "Always schedule model across all GPUs"},
-		"OLLAMA_MULTIUSER_CACHE":   {"OLLAMA_MULTIUSER_CACHE", MultiUserCache(), "Optimize prompt caching for multi-user scenarios"},
-		"OLLAMA_CONTEXT_LENGTH":    {"OLLAMA_CONTEXT_LENGTH", ContextLength(), "Context length to use unless otherwise specified (default: 4k/32k/256k based on VRAM)"},
-		"OLLAMA_NEW_ENGINE":        {"OLLAMA_NEW_ENGINE", NewEngine(), "Enable the new Ollama engine"},
-		"OLLAMA_REMOTES":           {"OLLAMA_REMOTES", Remotes(), "Allowed hosts for remote models (default \"ollama.com\")"},
+		"OLLAMA_DEBUG":              {"OLLAMA_DEBUG", LogLevel(), "Show additional debug information (e.g. OLLAMA_DEBUG=1)"},
+		"OLLAMA_DEBUG_LOG_REQUESTS": {"OLLAMA_DEBUG_LOG_REQUESTS", DebugLogRequests(), "Log inference request bodies and replay curl commands to a temp directory"},
+		"OLLAMA_FLASH_ATTENTION":    {"OLLAMA_FLASH_ATTENTION", FlashAttention(false), "Enabled flash attention"},
+		"OLLAMA_KV_CACHE_TYPE":      {"OLLAMA_KV_CACHE_TYPE", KvCacheType(), "Quantization type for the K/V cache (default: f16)"},
+		"OLLAMA_GPU_OVERHEAD":       {"OLLAMA_GPU_OVERHEAD", GpuOverhead(), "Reserve a portion of VRAM per GPU (bytes)"},
+		"OLLAMA_HOST":               {"OLLAMA_HOST", Host(), "IP Address for the ollama server (default 127.0.0.1:11434)"},
+		"OLLAMA_KEEP_ALIVE":         {"OLLAMA_KEEP_ALIVE", KeepAlive(), "The duration that models stay loaded in memory (default \"5m\")"},
+		"OLLAMA_LLM_LIBRARY":        {"OLLAMA_LLM_LIBRARY", LLMLibrary(), "Set LLM library to bypass autodetection"},
+		"OLLAMA_LOAD_TIMEOUT":       {"OLLAMA_LOAD_TIMEOUT", LoadTimeout(), "How long to allow model loads to stall before giving up (default \"5m\")"},
+		"OLLAMA_MAX_LOADED_MODELS":  {"OLLAMA_MAX_LOADED_MODELS", MaxRunners(), "Maximum number of loaded models per GPU"},
+		"OLLAMA_MAX_QUEUE":          {"OLLAMA_MAX_QUEUE", MaxQueue(), "Maximum number of queued requests"},
+		"OLLAMA_MODELS":             {"OLLAMA_MODELS", Models(), "The path to the models directory"},
+		"OLLAMA_NOHISTORY":          {"OLLAMA_NOHISTORY", NoHistory(), "Do not preserve readline history"},
+		"OLLAMA_NOPRUNE":            {"OLLAMA_NOPRUNE", NoPrune(), "Do not prune model blobs on startup"},
+		"OLLAMA_NUM_PARALLEL":       {"OLLAMA_NUM_PARALLEL", NumParallel(), "Maximum number of parallel requests"},
+		"OLLAMA_ORIGINS":            {"OLLAMA_ORIGINS", AllowedOrigins(), "A comma separated list of allowed origins"},
+		"OLLAMA_SCHED_SPREAD":       {"OLLAMA_SCHED_SPREAD", SchedSpread(), "Always schedule model across all GPUs"},
+		"OLLAMA_MULTIUSER_CACHE":    {"OLLAMA_MULTIUSER_CACHE", MultiUserCache(), "Optimize prompt caching for multi-user scenarios"},
+		"OLLAMA_CONTEXT_LENGTH":     {"OLLAMA_CONTEXT_LENGTH", ContextLength(), "Context length to use unless otherwise specified (default: 4k/32k/256k based on VRAM)"},
+		"OLLAMA_NEW_ENGINE":         {"OLLAMA_NEW_ENGINE", NewEngine(), "Enable the new Ollama engine"},
+		"OLLAMA_REMOTES":            {"OLLAMA_REMOTES", Remotes(), "Allowed hosts for remote models (default \"ollama.com\")"},
 
 		// Informational
 		"HTTP_PROXY":  {"HTTP_PROXY", String("HTTP_PROXY")(), "HTTP proxy"},

integration/basic_test.go

@@ -144,3 +144,47 @@ func TestUnicodeModelDir(t *testing.T) {
 	}
 	ChatTestHelper(ctx, t, req, blueSkyExpected)
 }
+
+// TestNumPredict verifies that when num_predict is set, the model generates
+// exactly that many tokens. It uses logprobs to count the actual tokens output.
+func TestNumPredict(t *testing.T) {
+	ctx, cancel := context.WithTimeout(context.Background(), 2*time.Minute)
+	defer cancel()
+
+	client, _, cleanup := InitServerConnection(ctx, t)
+	defer cleanup()
+
+	if err := PullIfMissing(ctx, client, "qwen3:0.6b"); err != nil {
+		t.Fatalf("failed to pull model: %v", err)
+	}
+
+	req := api.GenerateRequest{
+		Model:    "qwen3:0.6b",
+		Prompt:   "Write a long story.",
+		Stream:   &stream,
+		Logprobs: true,
+		Options: map[string]any{
+			"num_predict": 10,
+			"temperature": 0,
+			"seed":        123,
+		},
+	}
+
+	logprobCount := 0
+	var finalResponse api.GenerateResponse
+	err := client.Generate(ctx, &req, func(resp api.GenerateResponse) error {
+		logprobCount += len(resp.Logprobs)
+		if resp.Done {
+			finalResponse = resp
+		}
+		return nil
+	})
+	if err != nil {
+		t.Fatalf("generate failed: %v", err)
+	}
+
+	if logprobCount != 10 {
+		t.Errorf("expected 10 tokens (logprobs), got %d (EvalCount=%d, DoneReason=%s)",
+			logprobCount, finalResponse.EvalCount, finalResponse.DoneReason)
+	}
+}

runner/ollamarunner/runner.go

@@ -514,13 +514,6 @@ func (s *Server) forwardBatch(pendingBatch batchState) (nextBatch batchState, er
 			continue
 		}
 
-		// if past the num predict limit
-		if seq.numPredict > 0 && seq.numPredicted >= seq.numPredict {
-			s.removeSequence(seqIdx, llm.DoneReasonLength)
-			nextBatch.seqs[seqIdx] = nil
-			continue
-		}
-
 		if !s.cache.enabled {
 			seq.inputs = append(seq.cache.Inputs, seq.inputs...)
 			seq.cache.Inputs = []*input.Input{}
@@ -709,7 +702,6 @@ func (s *Server) computeBatch(activeBatch batchState) {
 			continue
 		}
 
-		seq.numPredicted++
 		nextToken := &input.Input{Token: 0} // placeholder we'll fill in after Compute/Floats
 		seq.inputs = []*input.Input{nextToken}
 		nextBatchTokens[i] = nextToken
@@ -745,7 +737,9 @@ func (s *Server) computeBatch(activeBatch batchState) {
 			logutil.Trace("computeBatch: sequence replaced, discarding its results", "batchID", activeBatch.id, "seqIdx", i)
 			continue
 		}
+
 		seq.lastUpdatedAt = t
+		seq.numPredicted++
 		if seq.numPredicted == 1 {
 			seq.processingDuration = seq.lastUpdatedAt.Sub(seq.startedAt)
 			seq.startedAt = seq.lastUpdatedAt
@@ -791,6 +785,13 @@ func (s *Server) computeBatch(activeBatch batchState) {
 		}
 
 		seq.pendingResponses = append(seq.pendingResponses, piece)
+
+		// if past the num predict limit
+		if seq.numPredict > 0 && seq.numPredicted >= seq.numPredict {
+			s.removeSequence(i, llm.DoneReasonLength)
+			continue
+		}
+
 		sequence := strings.Join(seq.pendingResponses, "")
 
 		if ok, stop := common.FindStop(sequence, seq.stop); ok {

server/inference_request_log.go

@@ -0,0 +1,144 @@
+package server
+
+import (
+	"bytes"
+	"fmt"
+	"io"
+	"log/slog"
+	"os"
+	"path/filepath"
+	"strings"
+	"sync/atomic"
+	"time"
+
+	"github.com/gin-gonic/gin"
+
+	"github.com/ollama/ollama/envconfig"
+)
+
+type inferenceRequestLogger struct {
+	dir     string
+	counter uint64
+}
+
+func newInferenceRequestLogger() (*inferenceRequestLogger, error) {
+	dir, err := os.MkdirTemp("", "ollama-request-logs-*")
+	if err != nil {
+		return nil, err
+	}
+
+	return &inferenceRequestLogger{dir: dir}, nil
+}
+
+func (s *Server) initRequestLogging() error {
+	if !envconfig.DebugLogRequests() {
+		return nil
+	}
+
+	requestLogger, err := newInferenceRequestLogger()
+	if err != nil {
+		return fmt.Errorf("enable OLLAMA_DEBUG_LOG_REQUESTS: %w", err)
+	}
+
+	s.requestLogger = requestLogger
+	slog.Info(fmt.Sprintf("request debug logging enabled; inference request logs will be stored in %s and include request bodies and replay curl commands", requestLogger.dir))
+
+	return nil
+}
+
+func (s *Server) withInferenceRequestLogging(route string, handlers ...gin.HandlerFunc) []gin.HandlerFunc {
+	if s.requestLogger == nil {
+		return handlers
+	}
+
+	return append([]gin.HandlerFunc{s.requestLogger.middleware(route)}, handlers...)
+}
+
+func (l *inferenceRequestLogger) middleware(route string) gin.HandlerFunc {
+	return func(c *gin.Context) {
+		if c.Request == nil {
+			c.Next()
+			return
+		}
+
+		method := c.Request.Method
+		host := c.Request.Host
+		scheme := "http"
+		if c.Request.TLS != nil {
+			scheme = "https"
+		}
+		contentType := c.GetHeader("Content-Type")
+
+		var body []byte
+		if c.Request.Body != nil {
+			var err error
+			body, err = io.ReadAll(c.Request.Body)
+			c.Request.Body = io.NopCloser(bytes.NewReader(body))
+			if err != nil {
+				slog.Warn("failed to read request body for debug logging", "route", route, "error", err)
+			}
+		}
+
+		c.Next()
+		l.log(route, method, scheme, host, contentType, body)
+	}
+}
+
+func (l *inferenceRequestLogger) log(route, method, scheme, host, contentType string, body []byte) {
+	if l == nil || l.dir == "" {
+		return
+	}
+
+	if contentType == "" {
+		contentType = "application/json"
+	}
+	if host == "" || scheme == "" {
+		base := envconfig.Host()
+		if host == "" {
+			host = base.Host
+		}
+		if scheme == "" {
+			scheme = base.Scheme
+		}
+	}
+
+	routeForFilename := sanitizeRouteForFilename(route)
+	timestamp := fmt.Sprintf("%s-%06d", time.Now().UTC().Format("20060102T150405.000000000Z"), atomic.AddUint64(&l.counter, 1))
+	bodyFilename := fmt.Sprintf("%s_%s_body.json", timestamp, routeForFilename)
+	curlFilename := fmt.Sprintf("%s_%s_request.sh", timestamp, routeForFilename)
+	bodyPath := filepath.Join(l.dir, bodyFilename)
+	curlPath := filepath.Join(l.dir, curlFilename)
+
+	if err := os.WriteFile(bodyPath, body, 0o600); err != nil {
+		slog.Warn("failed to write debug request body", "route", route, "error", err)
+		return
+	}
+
+	url := fmt.Sprintf("%s://%s%s", scheme, host, route)
+	curl := fmt.Sprintf("#!/bin/sh\nSCRIPT_DIR=\"$(CDPATH= cd -- \"$(dirname -- \"$0\")\" && pwd)\"\ncurl --request %s --url %q --header %q --data-binary @\"${SCRIPT_DIR}/%s\"\n", method, url, "Content-Type: "+contentType, bodyFilename)
+	if err := os.WriteFile(curlPath, []byte(curl), 0o600); err != nil {
+		slog.Warn("failed to write debug request replay command", "route", route, "error", err)
+		return
+	}
+
+	slog.Info(fmt.Sprintf("logged to %s, replay using curl with `sh %s`", bodyPath, curlPath))
+}
+
+func sanitizeRouteForFilename(route string) string {
+	route = strings.TrimPrefix(route, "/")
+	if route == "" {
+		return "root"
+	}
+
+	var b strings.Builder
+	b.Grow(len(route))
+	for _, r := range route {
+		if ('a' <= r && r <= 'z') || ('A' <= r && r <= 'Z') || ('0' <= r && r <= '9') {
+			b.WriteRune(r)
+		} else {
+			b.WriteByte('_')
+		}
+	}
+
+	return b.String()
+}

server/routes.go

@@ -81,6 +81,7 @@ type Server struct {
 	addr          net.Addr
 	sched         *Scheduler
 	defaultNumCtx int
+	requestLogger *inferenceRequestLogger
 }
 
 func init() {
@@ -1583,24 +1584,24 @@ func (s *Server) GenerateRoutes(rc *ollama.Registry) (http.Handler, error) {
 
 	// Inference
 	r.GET("/api/ps", s.PsHandler)
-	r.POST("/api/generate", s.GenerateHandler)
-	r.POST("/api/chat", s.ChatHandler)
+	r.POST("/api/generate", s.withInferenceRequestLogging("/api/generate", s.GenerateHandler)...)
+	r.POST("/api/chat", s.withInferenceRequestLogging("/api/chat", s.ChatHandler)...)
 	r.POST("/api/embed", s.EmbedHandler)
 	r.POST("/api/embeddings", s.EmbeddingsHandler)
 
 	// Inference (OpenAI compatibility)
-	r.POST("/v1/chat/completions", middleware.ChatMiddleware(), s.ChatHandler)
-	r.POST("/v1/completions", middleware.CompletionsMiddleware(), s.GenerateHandler)
+	r.POST("/v1/chat/completions", s.withInferenceRequestLogging("/v1/chat/completions", middleware.ChatMiddleware(), s.ChatHandler)...)
+	r.POST("/v1/completions", s.withInferenceRequestLogging("/v1/completions", middleware.CompletionsMiddleware(), s.GenerateHandler)...)
 	r.POST("/v1/embeddings", middleware.EmbeddingsMiddleware(), s.EmbedHandler)
 	r.GET("/v1/models", middleware.ListMiddleware(), s.ListHandler)
 	r.GET("/v1/models/:model", middleware.RetrieveMiddleware(), s.ShowHandler)
-	r.POST("/v1/responses", middleware.ResponsesMiddleware(), s.ChatHandler)
+	r.POST("/v1/responses", s.withInferenceRequestLogging("/v1/responses", middleware.ResponsesMiddleware(), s.ChatHandler)...)
 	// OpenAI-compatible image generation endpoints
 	r.POST("/v1/images/generations", middleware.ImageGenerationsMiddleware(), s.GenerateHandler)
 	r.POST("/v1/images/edits", middleware.ImageEditsMiddleware(), s.GenerateHandler)
 
 	// Inference (Anthropic compatibility)
-	r.POST("/v1/messages", middleware.AnthropicMessagesMiddleware(), s.ChatHandler)
+	r.POST("/v1/messages", s.withInferenceRequestLogging("/v1/messages", middleware.AnthropicMessagesMiddleware(), s.ChatHandler)...)
 
 	if rc != nil {
 		// wrap old with new
@@ -1650,6 +1651,9 @@ func Serve(ln net.Listener) error {
 	}
 
 	s := &Server{addr: ln.Addr()}
+	if err := s.initRequestLogging(); err != nil {
+		return err
+	}
 
 	var rc *ollama.Registry
 	if useClient2 {

server/routes_request_log_test.go

@@ -0,0 +1,128 @@
+package server
+
+import (
+	"io"
+	"net/http"
+	"net/http/httptest"
+	"os"
+	"path/filepath"
+	"strings"
+	"testing"
+
+	"github.com/gin-gonic/gin"
+)
+
+func TestInferenceRequestLoggerMiddlewareWritesReplayArtifacts(t *testing.T) {
+	gin.SetMode(gin.TestMode)
+
+	logDir := t.TempDir()
+	requestLogger := &inferenceRequestLogger{dir: logDir}
+
+	const route = "/v1/chat/completions"
+	const requestBody = `{"model":"test-model","messages":[{"role":"user","content":"hello"}]}`
+
+	var bodySeenByHandler string
+
+	r := gin.New()
+	r.POST(route, requestLogger.middleware(route), func(c *gin.Context) {
+		body, err := io.ReadAll(c.Request.Body)
+		if err != nil {
+			t.Fatalf("failed to read body in handler: %v", err)
+		}
+
+		bodySeenByHandler = string(body)
+		c.Status(http.StatusOK)
+	})
+
+	req := httptest.NewRequest(http.MethodPost, route, strings.NewReader(requestBody))
+	req.Host = "127.0.0.1:11434"
+	req.Header.Set("Content-Type", "application/json")
+	w := httptest.NewRecorder()
+	r.ServeHTTP(w, req)
+
+	if w.Code != http.StatusOK {
+		t.Fatalf("expected status 200, got %d", w.Code)
+	}
+
+	if bodySeenByHandler != requestBody {
+		t.Fatalf("handler body mismatch:\nexpected: %s\ngot: %s", requestBody, bodySeenByHandler)
+	}
+
+	bodyFiles, err := filepath.Glob(filepath.Join(logDir, "*_v1_chat_completions_body.json"))
+	if err != nil {
+		t.Fatalf("failed to glob body logs: %v", err)
+	}
+	if len(bodyFiles) != 1 {
+		t.Fatalf("expected 1 body log, got %d (%v)", len(bodyFiles), bodyFiles)
+	}
+
+	curlFiles, err := filepath.Glob(filepath.Join(logDir, "*_v1_chat_completions_request.sh"))
+	if err != nil {
+		t.Fatalf("failed to glob curl logs: %v", err)
+	}
+	if len(curlFiles) != 1 {
+		t.Fatalf("expected 1 curl log, got %d (%v)", len(curlFiles), curlFiles)
+	}
+
+	bodyData, err := os.ReadFile(bodyFiles[0])
+	if err != nil {
+		t.Fatalf("failed to read body log: %v", err)
+	}
+	if string(bodyData) != requestBody {
+		t.Fatalf("body log mismatch:\nexpected: %s\ngot: %s", requestBody, string(bodyData))
+	}
+
+	curlData, err := os.ReadFile(curlFiles[0])
+	if err != nil {
+		t.Fatalf("failed to read curl log: %v", err)
+	}
+
+	curlString := string(curlData)
+	if !strings.Contains(curlString, "http://127.0.0.1:11434"+route) {
+		t.Fatalf("curl log does not contain expected route URL: %s", curlString)
+	}
+
+	bodyFileName := filepath.Base(bodyFiles[0])
+	if !strings.Contains(curlString, "@\"${SCRIPT_DIR}/"+bodyFileName+"\"") {
+		t.Fatalf("curl log does not reference sibling body file: %s", curlString)
+	}
+}
+
+func TestNewInferenceRequestLoggerCreatesDirectory(t *testing.T) {
+	requestLogger, err := newInferenceRequestLogger()
+	if err != nil {
+		t.Fatalf("expected no error creating request logger: %v", err)
+	}
+	t.Cleanup(func() {
+		_ = os.RemoveAll(requestLogger.dir)
+	})
+
+	if requestLogger == nil || requestLogger.dir == "" {
+		t.Fatalf("expected request logger directory to be set")
+	}
+
+	info, err := os.Stat(requestLogger.dir)
+	if err != nil {
+		t.Fatalf("expected directory to exist: %v", err)
+	}
+	if !info.IsDir() {
+		t.Fatalf("expected %q to be a directory", requestLogger.dir)
+	}
+}
+
+func TestSanitizeRouteForFilename(t *testing.T) {
+	tests := []struct {
+		route string
+		want  string
+	}{
+		{route: "/api/generate", want: "api_generate"},
+		{route: "/v1/chat/completions", want: "v1_chat_completions"},
+		{route: "/v1/messages", want: "v1_messages"},
+	}
+
+	for _, tt := range tests {
+		if got := sanitizeRouteForFilename(tt.route); got != tt.want {
+			t.Fatalf("sanitizeRouteForFilename(%q) = %q, want %q", tt.route, got, tt.want)
+		}
+	}
+}

server/sched.go

@@ -417,9 +417,9 @@ func (s *Scheduler) load(req *LlmRequest, f *ggml.GGML, systemInfo ml.SystemInfo
 		numParallel = 1
 	}
 
-	// `mllama`, `qwen3vl`, and `qwen3vlmoe` are snowflakes and uses an encoder cache which cannot be used with num_parallel > 1
+	// Some architectures are not safe with num_parallel > 1.
 	// ref: https://github.com/ollama/ollama/issues/4165
-	if slices.Contains([]string{"mllama", "qwen3vl", "qwen3vlmoe"}, req.model.Config.ModelFamily) && numParallel != 1 {
+	if slices.Contains([]string{"mllama", "qwen3vl", "qwen3vlmoe", "qwen3next", "lfm2", "lfm2moe"}, req.model.Config.ModelFamily) && numParallel != 1 {
 		numParallel = 1
 		slog.Warn("model architecture does not currently support parallel requests", "architecture", req.model.Config.ModelFamily)
 	}