
What happened
Meta released open weights for Muse Spark Open, an 816B-parameter model built for coding and long-running agent work, with up to a 1 million token context window.
Why it matters
Meta calls it the most capable open-weight model from a U.S. lab so far, and it scored 61.8 on the JobBench agent test versus 31.1 for Thinking Machines Lab's Inkling.
WHO IT HITSDevelopers and teams that build on open-weight models can now download Muse Spark Open's weights from Hugging Face or the AWS, Google and Microsoft catalogs, though any company selling it as a hosted service above $20 million in gross revenue over 12 months needs a separate agreement with Meta.
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Meta's decision to release open weights for Muse Spark Open marks a shift for a model that had been proprietary since its April debut. The company built it on Muse Spark 1.2, shipped in August, and then added safety post-training so the model holds up without the guardrails of Meta's own services. Meta says the release cleared the thresholds in its Meta Superintelligence Scaling Framework, with a full evaluation report still to come.
The company is positioning the release carefully. The weights come with a new Muse Model License carrying "limited commercial terms," and while no fee applies to developers who adapt the model or ship it inside their own software, Meta requires a separate agreement from any company that sells the model as a hosted service and has passed $20 million in gross revenue over a 12-month period. Products built on it must carry a "Built with Muse Spark Open" label, and military and critical infrastructure uses are off-limits. Meta's previous open-weight release was the much smaller Muse Glimmer, a 30 billion-parameter model that went out in August, and the company's most capable systems remain closed.
The benchmark picture is mixed. In Meta's own table, Muse Spark Open scored 61.8 on the JobBench agent test, more than twice the 31.1 recorded by Inkling, the U.S. open model from Thinking Machines Lab, while Nvidia's Nemotron 3 Ultra trailed at 27.2. But Chinese open models are stronger at coding, with Kimi K3 leading the Terminal-Bench 2.1 coding test at 85 and GLM 5.3 and Qwen3.8 both finishing above Muse Spark Open's 76.4. On tool use, the order flips: Muse Spark Open's 89.2 on MCP-Atlas beat every rival Meta listed, the Chinese models included.
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