Metais releasing Muse Glimmer under an Apache 2.0 licence for local AI agents that can run on a consumer GPU.
The company’s Superintelligence Labs has released the 30-billion-parameter model’s weights on Hugging Face. Meta says developers can use it for local coding, function calling, local agents, and LLM-as-a-judge evaluation.
The release targets an operational constraint facing AI teams: cloud-hosted models need network access and central infrastructure. Meta instead pitches Muse Glimmer for workloads that require an on-device model, including personal agents with access to schedules, messages, files, and other private context.
Meta’s benchmark tests put Muse Glimmer ahead of Gemma4-31B and Qwen3.6-27B on five of eight general-agentic benchmarks. The model scored 75.5 on MCP Atlas. Gemma4-31B reached 54.2, and Qwen3.6-27B recorded 62.5.
DeepSearch QA follows a similar pattern. Meta reports a score of 74.6 for Muse Glimmer, against 61.7 for Gemma4-31B and 71.1 for Qwen3.6-27B. The supplied announcement identifies both benchmarks as tests of an agent’s ability to work within scaffolds and complete multi-turn requests.
The model scored 23.5 on τ²-Banking. Gemma4-31B recorded 15.1. Qwen3.6-27B reached 16.7.
Muse Glimmer also posted 47.6 on WildClawBench, ahead of Gemma4-31B’s 37.6 and Qwen3.6-27B’s 43.2. Its GAIA2 result reached 43.3, compared with 36.4 and 40.0 respectively.
Other agent scores favour Qwen3.6-27B. Meta’s table gives that model 1,141 on GDPval-AA, against Muse Glimmer’s 953 and Gemma4-31B’s 811. Qwen3.6-27B also led SkillsBench with Skills at 46.6, where Muse Glimmer recorded 44.3.
OSWorld-Verified produced the largest gap in this group. Meta reports 75.6 for Qwen3.6-27B. Muse Glimmer reached 65.9, and Gemma4-31B scored 58.5.
These tests measure constrained tasks. They do not demonstrate how a local agent will behave after an organisation connects it to its own files, calendars, messaging systems, or internal tools.
Muse Glimmer’s coding results show a narrower comparison. The model led SWE-Bench Pro with a score of 51.2. Meta reports 36.9 for Gemma4-31B and 50.2 for Qwen3.6-27B.
SciCode produced a close result. Muse Glimmer scored 43.6, marginally above Gemma4-31B at 43.4. Qwen3.6-27B recorded 39.8.