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Meta releases 816B-parameter Muse Spark Open weights, claims top US open-weight model, runs on Apple Macs

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12

Why it matters

Meta released the weights for Muse Spark Open on Thursday, October 15, 2026, under the Muse Model License. The model is a mixture-of-experts system with about 816 billion parameters, roughly 42 billion active per token, and a context window of up to one million tokens. It accepts text, images, audio, and video and outputs text. Meta calls it the most capable US open-weight model to date. The weights are on Hugging Face and in cloud catalogs including Amazon SageMaker AI, Google Cloud Model Garden, and Microsoft's Foundry Model Catalog, and API providers offer hosted access. Apple worked with Meta on the launch. The model is designed to run locally across two Apple machines, with each holding half the weights. Engadget reports a requirement of at least 1 terabyte of RAM. The model card lists at least 700GB of GPU memory for NVFP4 and 2TB for the full BF16 weights. The release builds on Meta's August Muse Spark model, with added safety post-training intended to make it more robust when used without system guardrails.

Several points remain open. Meta's benchmarks compare the model mainly with US rivals such as Thinking Machines' Inkling and Nvidia's Nemotron 3 Ultra, and with Chinese open models. Those results come from Meta, and independent evaluations have not yet been published. Reporting says the weights sat in a gated repository behind an access-controlled form for four weeks before the public release. The reason for that period is not explained. The license is also not fully open. Its full terms beyond the requirements noted below are not yet analyzed in public reporting.

For attorneys, the license is the main item to review. It requires a visible notice in every product that uses the model and a separate agreement for large model-as-a-service providers. Teams evaluating the model for commercial use should confirm which of those obligations apply to them before treating "open" as a permissive license. Procurement and vendor contracts should also account for the cloud catalog listings and hosted API access, since those channels may carry different terms. The hardware requirements make local deployment a capital decision, not a casual one. Watch for independent benchmark results and any clarification of the license scope from Meta.

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