Steven Gonsalvez

Software Engineer

Muse Glimmer: 30B-parameter model optimized for always-on local agent workflows

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LLM model optimized for agent workflows

The text below is an automated extraction of the article at https://research.meta.ai/blog/introducing-muse-glimmer-open-agentic-model, stored verbatim in the public cerebro-vault repository. Copyright remains with the original publisher (research.meta.ai).

Introducing Muse Glimmer: An Open Agentic Model That Runs on Your Device Today, we're introducing Muse Glimmer, the next model from Meta Superintelligence Labs, and open sourcing the model weights under a permissive Apache 2.0 license. Muse Glimmer is a 30-billion-parameter model optimized for always-on local agent workflows. It’s small enough to run on a Mac or PC with a single consumer GPU, enabling use cases that range from local agents and function calling, to local coding, and LLM-as-a-judge evaluation. Muse Glimmer delivers strong performance on key agentic use cases and benchmarks compa

Community take

30B open models are competitive but need 32-64GB memory, blocking consumer adoption.

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