Meta's Muse Spark Open lands on OpenRouter with 1M context
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Muse Spark Open from @AIatMeta is now available on OpenRouter! - strongest open-weight model from a US lab - built for agentic coding - 1M context - fully multimodal: image, video, audio and PDF input - $1.25/M in, $4.25/M out https://t.co/BvLwsmvQvZ
Launching day 0 on OpenRouter with @baseten @FireworksAI_HQ @nebiusai and @togethercompute https://t.co/uHdZPxlebI
Context
OpenRouter, the service that puts many models behind one API, says Meta's Muse Spark Open was available to call through it on launch day, served by four providers, Baseten, Fireworks, Nebius and Together (OpenRouter thread). Because the model's weights are open, outside companies like these can host it themselves rather than relying on Meta's servers; OpenRouter lists it at $1.25 per million input and $4.25 per million output tokens, with a 1 million token and input in images, video, audio and PDFs as well as text. OpenRouter describes it as built for agentic coding and as the strongest model from a US lab. Its model page could not be read, so these specifics rest on the announcement post.
The "strongest" claim is OpenRouter's, but Artificial Analysis's independent benchmarking, published hours later and covered separately, points the same way: it describes Muse Spark Open as an 816-billion-parameter model with 42 billion active per token and scores it 39 on its Intelligence Index, the highest of any US open-weights model, ahead of NVIDIA's Nemotron 3.5 Super VL at 26 (Artificial Analysis thread). The same analysis qualifies the "built for agentic coding" framing, though: among the nine highest-scoring open-weights models, it ranks last on the index's four agentic evaluations and fourth on the other six combined.
- inference — Running a trained model to get answers — the phase where AI is actually used, as opposed to trained.
- token — The chunk of text a model reads and writes in — roughly three-quarters of a word — and the unit AI usage is billed in.
- context window — The maximum amount of text a model can consider at once — its working memory for the current conversation or task.
- open weights — A model whose trained parameters are published for anyone to download and run — unlike API-only models you can access but never possess.
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