Introducing Muse Glimmer
- ID
- 12956
- Status
- summarized
- Published
- 11 Aug 2026, 7:56 AM
- Fetched
- 11 Aug 2026, 8:59 AM
- Provider
- Simon Willison
- Category
- developer-ai
- Original URL
- https://simonwillison.net/2026/Aug/10/introducing-muse-glimmer/
- Source URL
- https://simonwillison.net/atom/everything/
Summary
- Score
- 7.5
- Created
- 11 Aug 2026, 8:59 AM
- Tags
- Audience
- developersvibe_codersai_ml_learnersai_agent_users
What happened
Meta released Muse Glimmer, a 30B parameter open-weights model under a clean Apache 2.0 license, optimized for agentic task completion, tool use, and multi-step reasoning. Simon Willison tested it locally via LM Studio (18.16 GB quantized), ran it as a coding agent against a Datasette checkout, and confirmed it works as a vision model for image description.
Why it matters
If you want a locally-runnable model for agentic coding and tool-use workflows, Muse Glimmer's Apache 2.0 license removes the Llama licensing friction for commercial use, and its 30B size means it fits on machines with 32GB+ RAM alongside other applications. Test it with your own coding-agent scaffolding before committing—Willison needed a patch for LLM 0.32 compatibility, so expect integration rough edges.
Discussion angle
Compare Muse Glimmer's Apache 2.0 license and 30B local-runnable size against current alternatives like Qwen or Llama for agentic coding—does the license change actually unlock new use cases, or is the model quality the bottleneck?