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oMLX inference server updated for Apple Silicon, supports multiple large models

By PulseAugur Editorial · [1 sources] ·

oMLX, an LLM inference server built on Apple's MLX framework, has been updated to version 0.6.4. This new version offers an OpenAI- and Anthropic-compatible API, continuous batching, and a dual-tier KV cache system utilizing both RAM and SSD. On a Mac M5 Max with 128 GB of unified memory, users can now run multiple large models concurrently, such as Qwen3.6-35B-A3B-MLX-8bit and Qwen2.5-VL-32B-mlx-4bit, with performance gains of up to 1.88x in code generation. AI

IMPACT Enables running multiple large local LLMs on Apple Silicon, improving developer productivity and data privacy for sensitive tasks.

RANK_REASON The item details a specific software tool's update and installation guide, rather than a core AI model release or research.

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

oMLX inference server updated for Apple Silicon, supports multiple large models

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The item details a specific software tool's update and installation guide, rather than a core AI model release or research.
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COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · Javier Cañete Arroyo ·

    How to install and tune oMLX on M5 Max 128 GB

    <p><strong>oMLX is an LLM inference server built on MLX, the framework Apple shipped in December 2023 for Apple Silicon. It adds continuous batching, two-tier KV cache (RAM + SSD), and an OpenAI- and Anthropic-compatible API.</strong></p> <p>On a Mac M5 Max with 128 GB of unified…

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