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  1. Open sourceReach 72

    Meta's 816B open model runs on two Mac Studios

    Meta just dropped Muse Spark Open, an open-weight model with 816B total parameters (42B active) and a 1M-token context window designed for coding and agentic tasks. Leveraging the MLX framework, it is the first model in its class capable of running locally on two Apple M5 Ultra Mac Studios. Why it matters: massive agentic supercomputing no longer requires a cloud cluster.

  2. Open sourceReach 48

    Apple quietly open-sources MLX to run models on Mac chips

    Apple just quietly dropped MLX and MLX Data, a new machine learning framework tailored specifically for Apple Silicon. Inspired by PyTorch and Jax, it takes advantage of unified memory so CPUs and GPUs can process tasks without moving data, packing enough punch to train and run models like Llama and Stable Diffusion locally. Why it matters: Apple is finally giving developers the tools to turn MacBooks into capable generative AI workstations.