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vLLM Metal is a plugin that enables vLLM to run on Apple Silicon Macs using MLX as the primary compute backend. It unifies MLX and PyTorch under a single lowering path.

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Latest News 🔥

• [2026/10] Experimental Recursive Flint INT4 support is now available on the MLX backend, including concurrent serving.
• [2026/10] DiffusionGemma now supports Jev-like System 1 decisions on Metal, with median decision latency under 0.2 s on an M5 Pro. See the structured decisions guide.
• [2026/10] Desktop inference competes with your other applications for memory. Sleep mode lets an idle model server return memory to those apps without shutting down. Read Abhigith Neil Abraham's walkthrough.
• [2026/10] Run local models with vLLM Metal through llmman. See the setup recipe.
• [2026/09] SiliconBench, which evaluates vLLM Metal and other serving engines on speed, memory use, and output fidelity, was accepted at NeurIPS 2026's Evaluations and Datasets Track.
• [2026/09] Read our official vLLM announcement, covering concurrent serving on Apple Silicon and v0.28.0.
• [2026/08] vLLM Metal now uses M5 NAX tensor units to accelerate MHA, GQA, and MQA prefill.
• [2026/08] Qwen3.8 now runs on Metal! mlx-community/Qwen3.8-27B-8bit serves a 27B hybrid SDPA + GDN linear model on a single Apple Silicon Mac.
• [2026/04] We released the new version v0.2.0! Unified paged varlen Metal kernel is now the default attention backend. 83x TTFT, 3.6x throughput compared to v0.1.0.

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Architecture

Upstream vLLM supplies the API server, scheduler, and paged block manager; mlx_lm supplies the token-wise model layers; vllm-metal owns the request-aware attention path — the paged varlen kernel, M5 NAX prefill, and speculative decoding.

Requirements

• macOS 15 (Sequoia) or later, on Apple Silicon

Supported Models

vllm-metal supports a growing set of models on Apple Silicon. See the full matrix in docs/supported_models.md.

Installation

• Stable release: Install with Homebrew, then run vllm without activating an environment.

  brew tap vllm-project/vllm-metal https://github.com/vllm-project/vllm-metal
  brew install vllm-project/vllm-metal/vllm-metal

• Latest development build: Use the curl installer, then activate its environment. No compiler needed.

  curl -fsSL https://raw.githubusercontent.com/vllm-project/vllm-metal/main/install.sh | bash
  source ~/.venv-vllm-metal/bin/activate

• Contributing Python or kernel code: Follow the source setup for an editable checkout and native build tools.