Run Local Agentic AI Workflows with Meta’s Muse Glimmer on NVIDIA
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Michelle Horton
Author
Michelle Horton
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Terms in this piece · Glossary
open weights — A model whose trained parameters are published for anyone to download and run — unlike API-only models you can access but never possess.
context window — The maximum amount of text a model can consider at once — its working memory for the current conversation or task.
token — The chunk of text a model reads and writes in — roughly three-quarters of a word — and the unit AI usage is billed in.
Why it matters
Concrete numbers on running a capable open weightsA model whose trained parameters are published for anyone to download and run — unlike API-only models you can access but never possess.Full definition → agentic model locally, which changes the build-vs-API calculus for on-device agents.
Transcript
Meta returns to the open source ecosystem with the release of Muse Glimmer, a 30B open-weight dense model with a 120K+ context window built for local AI... Meta returns to the open source ecosystem with the release of Muse Glimmer, a 30B open-weight dense model with a 120K+ context window built for local AI agentic work. Optimized to run across a range of NVIDIA edge, desktop, and workstation AI platforms, Muse Glimmer delivers 20K tokens/sec on a single GPU, enabling always-on agents to process data locally and execute complex… Source
