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unified memory

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RESEARCH · 1 SOURCE · Apple Machine Learning Research

MLX enables local and multi‑Mac inference of Muse Spark Open (816B) on Mac Studio

The MLX array framework added Apple Silicon support and demonstrates running frontier LLMs locally and in a distributed setup on Mac Studio. Using the latest MLX release and RDMA over Thunderbolt, a four‑node Mac Studio cluster runs Muse Spark Open (816B, MoE, NVFP4) at >36 tokens/s; smaller models (Qwen 3.8 and Mistral Medium 3.5) can fit on a single 512GB Mac Studio. Benchmarks with mlx_lm.benchmark report up to 4.6× faster time‑to‑first‑token and ~1.6× higher tokens/s on M5 Ultra versus M3 Ultra, and modest peak power (~200–300W) for inference.

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