Meta publishes the technical report for Muse Glimmer 30B

Meta published the technical report for Muse Glimmer 30B on 19 October 2026. The weights, under the Apache 2.0 licence, are on Hugging Face as meta-models/Muse-Glimmer-30B. The report is the new document. The model is the one Meta introduced in August.

Muse Glimmer is a dense model of 30 billion parameters, not a mixture of experts. Meta says it chose a dense network because the model had to fit a memory limit. Distillation trains that smaller model to follow Muse Spark, the teacher the paper calls frontier-class. A perception encoder takes images, alongside text, and the model returns text. The report then quantises the weights to about 4-bit so inference fits one GPU, aimed at machines with 32GB of dedicated memory. Meta says it kept grouped-query attention after a more compressed attention design did worse on long context.

Meta reports a lead over Gemma4-31B and Qwen3.6-27B on tool use, multi-step planning and agentic task completion. Those comparisons are company-reported. The radar chart shows the lead is uneven: Muse Glimmer sits outside the other two on some agent tests and mixed with them on coding tests.