vmlx

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Inference Engine

Distributed Inference (Multi-Mac)

Run models too large for a single Mac across 2+ machines. Each Mac loads a subset of transformer layers and they communicate hidden states over the network.

# On worker Macs:
pip install vmlx
vmlx-worker --secret mysecret

# On coordinator Mac (runs the server):
vmlx serve JANGQ-AI/Qwen3.5-Coder-Rerank-397B-A27B-JANG_2L --distributed --cluster-secret mysecret

5-Layer Cache Architecture

Request -> Tokens
    |
L1: Memory-Aware Prefix Cache (or Paged Cache)
    | miss
L2: Disk Cache (or Block Disk Store)
    | miss
Inference -> float16 KV states
    |
KV Quantization -> q4/q8 for storage
    |
Store back into L1 + L2

Tool Calling

Auto-detected parsers for every major model family:

qwen - llama - mistral - hermes - deepseek - glm47 - minimax - nemotron - granite - functionary - xlam - kimi - step3p5

Reasoning / Thinking Mode

Auto-detected reasoning parsers that extract <think> blocks:

qwen3 (Qwen3, QwQ, StepFun) - minimax_m2 (MiniMax M2/M2.5/M2.7) - deepseek_r1 (DeepSeek R1, Gemma 3, GLM, Phi-4) - openai_gptoss (GLM Flash, GPT-OSS)

Audio

API Gateway

The desktop app runs an API Gateway on a single port (default 8080) that routes requests to all loaded models by name. Run multiple models simultaneously and access them all through one URL.

# All models accessible through the gateway
curl http://localhost:8080/v1/chat/completions \
  -d '{"model": "Qwen3.5-122B", "messages": [{"role": "user", "content": "Hi"}]}'

# Works with Ollama CLI too
OLLAMA_HOST=http://localhost:8080 ollama run Qwen3.5-122B

The gateway supports OpenAI, Anthropic, and Ollama wire formats. Configure the port in the API tab.

Endpoints

OpenAI / Anthropic

Ollama

curl Examples

Chat completion (streaming)

curl http://localhost:8000/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "local",
    "messages": [{"role": "user", "content": "Explain quantum computing in 3 sentences."}],
    "stream": true,
    "temperature": 0.7
  }'

Chat completion with thinking mode

curl http://localhost:8000/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "local",
    "messages": [{"role": "user", "content": "Solve: what is 23 * 47?"}],
    "enable_thinking": true,
    "stream": true
  }'

Tool calling

curl http://localhost:8000/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "local",
    "messages": [{"role": "user", "content": "What is the weather in Tokyo?"}],
    "tools": [{
      "type": "function",
      "function": {
        "name": "get_weather",
        "description": "Get current weather for a location",
        "parameters": {
          "type": "object",
          "properties": {
            "location": {"type": "string", "description": "City name"}
          },
          "required": ["location"]
        }
      }
    }]
  }'

Anthropic Messages API

curl http://localhost:8000/v1/messages \
  -H "Content-Type: application/json" \
  -H "x-api-key: not-needed" \
  -H "anthropic-version: 2023-06-01" \
  -d '{
    "model": "local",
    "max_tokens": 1024,
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Embeddings

curl http://localhost:8000/v1/embeddings \
  -H "Content-Type: application/json" \
  -d '{
    "model": "local",
    "input": "The quick brown fox jumps over the lazy dog"
  }'

Text-to-speech

curl http://localhost:8000/v1/audio/speech \
  -H "Content-Type: application/json" \
  -d '{
    "model": "kokoro",
    "input": "Hello, welcome to vMLX!",
    "voice": "af_heart"
  }' --output speech.wav

Speech-to-text

curl http://localhost:8000/v1/audio/transcriptions \
  -F file=@audio.wav \
  -F model=whisper

Image generation

curl http://localhost:8000/v1/images/generations \
  -H "Content-Type: application/json" \
  -d '{
    "model": "schnell",
    "prompt": "A mountain landscape at sunset",
    "size": "1024x1024"
  }'

Reranking

curl http://localhost:8000/v1/rerank \
  -H "Content-Type: application/json" \
  -d '{
    "model": "local",
    "query": "What is machine learning?",
    "documents": [
      "ML is a subset of AI",
      "The weather is sunny today",
      "Neural networks learn from data"
    ]
  }'

Cache stats

curl http://localhost:8000/v1/cache/stats

Health check

curl http://localhost:8000/health

Optional Dependencies

pip install vmlx              # Core: text LLMs, VLMs, embeddings, reranking
pip install vmlx[image]       # + Image generation (mflux)
pip install vmlx[jang]        # + JANG quantization tools
pip install vmlx[dev]         # + Development/testing tools
pip install vmlx[image,jang]  # Multiple extras