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Meta open-sources Muse Glimmer, a 30B model for local AI agents

Meta releases open-weight Muse Glimmer under Apache 2.0, enabling local agentic AI workflows on consumer GPUs and laptops.

Meta open-sources Muse Glimmer, a 30B model for local AI agents
simonwillison.net

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Summary, timeline and people extracted by Claude from 24 items across 5 sources · 3h ago. Quotes are verbatim.

Meta released Muse Glimmer, a 30-billion-parameter open-weight model designed to run agentic AI workflows on local hardware, available under an Apache 2.0 license. The model supports text and image input, achieves strong performance on task completion benchmarks, and runs on consumer GPUs with under 20GB memory, enabling users to run AI agents locally without cloud services. The release represents Meta's return to open-weight model distribution and aligns with broader industry interest in edge AI deployment.

  • Meta released Muse Glimmer, a 30B open-weight model under Apache 2.0 license enabling commercial use and local deployment without restrictions.
  • The model runs on consumer GPUs with under 20GB memory and delivers 20K+ tokens/sec, supporting planning, tool calls, and coding for agentic AI workflows.
  • NVIDIA and AMD immediately announced hardware optimization and support, with edge performance of 25-36 tokens/s on Jetson devices.
  • The release aligns Meta's actions with Zuckerberg's stated philosophy on open AI access, enabling locally-runnable AI without cloud dependencies.

How it unfolded

  1. Reddit users note the contrast between Zuckerberg's manifesto on open AI governance and Meta's same-day release of a commercially-usable, locally-runnable model under permissive licensing.

    “On the same day Zuckerberg pu[blished a manifesto saying no single company should control AI], Meta dropped Muse Glimmer...no cloud, no subscription, no one else's servers touching your data.”

    Dapper-Tale-4021 · r/artificial ↗
  2. Analysis Technical deep-dive and testing

    Simon Willison publishes detailed hands-on testing, demonstrating image analysis and code generation capabilities, highlighting the model's suitability for local use with 32GB+ RAM systems.

    “Muse Glimmer is a brand new 30B model under a clean Apache 2.0 license (a step up from the janky Llama licenses of old).”

    Simon Willison · Hacker News ↗
  3. The New Stack and other publications emphasize that Muse Glimmer enables agentic workflows to run on local hardware, with The New Stack publishing analysis of the model's design for end-to-end task completion.

  4. Meta launched Muse Glimmer, a 30-billion-parameter open-weight model under Apache 2.0 license, designed for local agentic AI workflows on consumer hardware. The model supports 120K+ context window and delivers up to 20K tokens/sec on a single GPU.

  5. NVIDIA and AMD announce compatibility, with NVIDIA reporting 20K tokens/sec on desktop GPU and 25-36 tokens/s on Jetson edge devices, while AMD highlights optimization for Ryzen AI Max+ systems.

    “Great to see @AIatMeta back publishing open models 🙌 Muse Glimmer is a 30B open-weight dense model with a 120K+ context window, built for long-running agents, delivering up to 20K tokens/sec on a single GPU.”

    @nvidiaai · X ↗
  6. Reaction LM Studio integrates model

    LM Studio announces Muse Glimmer 30B is live in their platform, calling it the strongest model of its size class they've tested.

    “Muse Glimmer 30B is live in LM Studio! It's a new open source model from Meta. Apache 2.0 license, fit right on your laptop. It is the strongest model of its size class we've tested.”

    @lmstudio · X ↗

What people are saying verbatim

“Muse Glimmer is a brand new 30B model under a clean Apache 2.0 license (a step up from the janky Llama licenses of old).”

Simon Willison, Tech writer · simonwillison.net ↗

“Great to see @AIatMeta back publishing open models 🙌 Muse Glimmer is a 30B open-weight dense model with a 120K+ context window, built for long-running agents, delivering up to 20K tokens/sec on a single GPU.”

@nvidiaai, NVIDIA AI account · X ↗

“Muse Glimmer 30B is live in LM Studio! It's a new open source model from Meta. Apache 2.0 license, fit right on your laptop. It is the strongest model of its size class we've tested.”

@lmstudio, LM Studio · X ↗

“Muse Glimmer (high) scores 35 on the Artificial Analysis Intelligence Index, placing it well above average among comparable models (median: 9).”

Artificial Analysis, AI model evaluation service · artificialanalysis.ai ↗

“On the same day Zuckerberg pu[blished a manifesto saying no single company should control AI], Meta dropped Muse Glimmer...no cloud, no subscription, no one else's servers touching your data.”

Dapper-Tale-4021, Reddit commenter · r/artificial ↗

“Congrats to @AIatMeta on Muse Glimmer, a 30B dense model for local AI agents, now supported on NVIDIA Jetson. 🎉 Muse Glimmer delivers up to 25 tokens/s on Jetson Orin and up to 36 tokens/s on Jetson Thor.”

@nvidiarobotics, NVIDIA Robotics · X ↗

Voices from the web unedited

  • Great to see @Meta recommit to open weights with Muse Glimmer. We @digitalocean are eagerly awaiting Muse Spark 1.2 Open Weights!! At 57 on the Artificial Analysis Intelligence Index, open weights for @AIatMeta Spark would put near-frontier intelligence into builders' hands and [image]

    @paddixX · techmeme1d agoview on X ↗
  • Great to see @AIatMeta back publishing open models 🙌 Muse Glimmer is a 30B open-weight dense model with a 120K+ context window, built for long-running agents, delivering up to 20K tokens/sec on a single GPU. It's optimized to run locally across NVIDIA edge, desktop, and

    @nvidiaaiX · techmeme1d agoview on X ↗
  • Congrats to @AIatMeta on Muse Glimmer, a 30B dense model for local AI agents, now supported on NVIDIA Jetson. 🎉 Muse Glimmer delivers up to 25 tokens/s on Jetson Orin and up to 36 tokens/s on Jetson Thor. Try it for yourself with our Jetson AI Lab tutorial 👉

    @nvidiaroboticsX · techmeme1d agoview on X ↗
  • Muse Glimmer 30B is live in LM Studio! It's a new open source model from Meta. Apache 2.0 license, fit right on your laptop. It is the strongest model of its size class we've tested.

    @lmstudioX · techmeme1d agoview on X ↗
  • Fun demo with Muse Glimmer: ask the model to deploy itself to the HuggingFace inference endpoint and optimize the inference efficiency

    @jack_w_raeX · techmeme1d agoview on X ↗