By PYMNTS | October 15, 2026
Meta has introduced an open-weight model that can run on a user’s desktop using two Apple M5 Ultra Mac Studios with the latest MLX framework, Meta said in a Thursday (Oct. 15) press release.
The model, Muse Spark Open, is “the most capable U.S. open-weight model to date,” Meta said in the release. It is natively multimodal and has 816 billion total parameters (42 billion active) and a one million-token context window, according to the release.
Muse Spark Open is built for coding and agentic work, and it excels at long-horizon tasks, complex software engineering and multi-step reasoning, per the release.
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Meta Founder, Chairman and CEO Mark Zuckerberg said in a Thursday post on X: “Muse Spark Open — weights releasing today — runs great on new Mac Studios thanks to work with [Apple CEO John Ternus] and Apple.”
In a reply to Zuckerberg’s post, Ternus said: “Congrats to the team! Amazing to run a model of Muse Spark Open’s caliber and scale this efficiently, right from your desk. Mac Studio keeps pushing the boundaries of on-device AI!”
Apple published an article on its Machine Learning Research website that shows how AI researchers and developers can run Muse Spark Open, a frontier-class model, from their desk, using a version of MLX that was released Thursday.
Meta said in its press release that Muse Spark Open leverages the latest version of Apple’s MLX and was optimized to run on Mac Studio with M5 Ultra. The company said this combination is “the best way to run a powerful model on your own desktop.”
Two Mac Studios can hold an entire model and “behave like one supercomputer with a terabyte of unified memory,” Meta said in the release.
The Wall Street Journal reported Thursday that the total cost to buy the Macs needed to run Muse Spark Open is about $40,000 and that this combination will provide developers with the kind of computing power that could cost thousands of dollars a month when rented from cloud providers.
The Financial Times reported in September that American businesses are turning to lower-cost open-weight models to gain control over rising tech expenses.