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Meta's open-weight release gives developers a large, multimodal model with a 1M-token context window, and its sparse design activates 42 billion of 816 billion parameters per token. Most of the performance claims come from Meta's own benchmark table, and the full evaluation report hasn't been published yet. The article also notes that Chinese open models lead on coding benchmarks, so the "most capable U.S. open-weight model" framing is narrower than it may first appear.
Meta releases 816B-parameter Muse Spark Open for coding and agent work
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 […] The post Meta releases 816B-parameter Muse Spark Open for coding and agent work appeared first on SiliconANGLE.
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…
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