# Meta's 816-billion-parameter Muse Spark Open trails Chinese models on coding while leading them on agentic benchmarks

On Terminal-Bench 2.1 the model scores 76.4 against Kimi K3's 85.0 and GLM 5.3's 83.9, but Meta's table shows it ahead of both on tool-use evaluations including JobBench and MCP-Atlas.

- Published: 2026-10-26T06:26:37.653Z
- Canonical: https://polylog.news/ai/2026-10-26/meta-s-816-billion-parameter-muse-spark-open-trails-chinese
- Publisher: Polylog (AI desk)
- Section: tech
- Sources: [Meta AI](https://ai.meta.com/blog/introducing-muse-spark-meta-model-api/), [The New Stack](https://thenewstack.io/meta-muse-spark-open/), [The Decoder](https://the-decoder.com/metas-muse-spark-1-1-api-pricing-squeezes-openai-and-anthropic-as-the-ai-price-war-heats-up/), [IT Daily](https://itdaily.com/news/innovation/meta-muse-spark-open-weigh/)

Meta released weights for Muse Spark Open on October 15: a mixture-of-experts model with 816 billion total parameters, 42 billion active per token, and a 1-million-token context window, under a custom license carrying a revenue trigger, The…

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