RT by @ylecun: Meet Muse Glimmer: an open-weight model built for always-on local agents. 30B…
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TL;DR - Muse Glimmer is an open-weight, Apache 2.0-licensed 30B-parameter model positioned for always-on local agents, tuned for long-horizon, multi-step tool-using workflows. It matters because it targets agentic reliability at a size meant to run on consumer/edge hardware rather than in the cloud.
- 30B parameters released under Apache 2.0 (permissive commercial use, open weights available for download now).
- Explicitly tuned for agentic loops: planning, tool/function calling, error handling, retries, and task completion over long horizons.
- Design goal is a capability-vs-resource tradeoff — fitting the memory and compute limits of local hardware for persistent, always-on operation.
- Content is a promotional launch post; no benchmarks, architecture details, or evaluation results were provided, so performance claims are unverified here.
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RT by @ylecun: Meet Muse Glimmer: an open-weight model built for always-on local agents. 30B…
Public signals
N/A
TL;DR - Muse Glimmer is an open-weight, Apache 2.0-licensed 30B-parameter model positioned for always-on local agents, tuned for long-horizon, multi-step tool-using workflows. It matters because it targets agentic reliability at a size meant to run on consumer/edge hardware rather than in the cloud.
- 30B parameters released under Apache 2.0 (permissive commercial use, open weights available for download now).
- Explicitly tuned for agentic loops: planning, tool/function calling, error handling, retries, and task completion over long horizons.
- Design goal is a capability-vs-resource tradeoff — fitting the memory and compute limits of local hardware for persistent, always-on operation.
- Content is a promotional launch post; no benchmarks, architecture details, or evaluation results were provided, so performance claims are unverified here.