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Meta 發佈 816B 參數 Muse Spark Open 開放權重,面向編碼及智能體任務

Meta releases 816B-parameter Muse Spark Open for coding and agent work

AI 導讀

Meta 發佈 Muse Spark Open 的開放權重,這款 816B 參數模型面向編碼及長時間運作的智能體任務。其上下文窗口最高為 1 million tokens;Meta 的測試中,模型在 JobBench 得分 61.8,在 MCP-Atlas 工具使用測試得分 89.2。

推薦理由

文章比較 Muse Spark Open 在編碼與工具調用基準上的表現,並交代開放權重的商用授權條件,呈現其能力側重與使用限制。

正文 · 原文

Meta releases 816B-parameter Muse Spark Open for coding and agent work

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Meta Platforms Inc. today released open weights for its Muse Spark artificial intelligence model, which had been proprietary since its April debut.

The release, called Muse Spark Open, is built for coding and long-running agent work. Meta describes it as the most capable open-weight model to come out of a U.S. lab so far. Only 42 billion of the model’s 816 billion parameters switch on for any given token. Prompts can mix text with images, audio or video, and Meta has set the context window at up to 1 million tokens.

The starting point was Muse Spark 1.2, shipped in August, and Meta then added safety post-training so the model holds up without the guardrails of Meta’s own services. Meta said Muse Spark Open cleared the release thresholds in its Meta Superintelligence Scaling Framework, with a full evaluation report still to come. A technical writeup from Hugging Face Inc. says training leaned on what Meta calls “real developer workflows,” including multi-file refactors and long debugging sessions.

Meta also tested the model away from the data center, on a pair of Apple Inc. Mac Studio desktops with M5 Ultra chips that Apple’s MLX framework linked into one system. The two machines had about a terabyte of memory between them.

Muse Code ran on that setup while the coding terminal worked through bug fixes and new features for the open-source Mastodon client Ice Cubes. Footage in DaVinci Resolve was the other test, and the model went through it frame by frame to pick out and crop the best shots for vertical video.

In Meta’s own benchmark 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 Inc. Nvidia Corp.’s Nemotron 3 Ultra trailed further at 27.2.

Chinese open models are stronger at coding. Kimi K3 led the Terminal-Bench 2.1 coding test at 85, and GLM 5.3 and Qwen3.8 both finished above Muse Spark Open’s 76.4.

On tool use the order flips, and Muse Spark Open’s 89.2 on MCP-Atlas beat every rival Meta listed, the Chinese models included. The benchmark gives a model plain-language tasks without naming the tools needed to complete them. Working out which of 220 tools across 36 live Model Context Protocol servers to call, and in what order, is left to the model.

The weights come with a new Muse Model License carrying what Meta calls “limited commercial terms,” and 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 have to show a “Built with Muse Spark Open” label. 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. The company’s most capable systems remain closed, and the Muse Wonder models introduced Monday are available only through the Meta Model API and Muse Code.

Seven inference providers offer hosted access at launch, Groq Inc. and Fireworks AI Inc. among them. The weights can also be downloaded from Hugging Face or from the model catalogs of Amazon Web Services Inc., Google LLC and Microsoft Corp.

Image: Meta

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來源:SiliconANGLE · siliconangle.com