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Meta releases open-weight Muse Glimmer model for agentic tasks

By PulseAugur Editorial · [9 sources] ·

Meta has released Muse Glimmer, a new 30B parameter open-weight model licensed under Apache 2.0. The model is designed for end-to-end agentic task completion, reliable tool use, and multi-step reasoning, showing strong performance on benchmarks like DeepSearch QA and SWE-Bench. However, its memory requirements, around 24-32 GB after compression, may limit its local usability on many consumer laptops, and early benchmarks suggest it may be less efficient than competitors like Qwen. AI

IMPACT Sets a new standard for open-weight models in agentic task completion, though high memory requirements may limit adoption.

RANK_REASON Frontier-lab model release with system card.

Read on Mastodon — sigmoid.social →

AI-generated summary · Google Gemini · from 9 sources. How we write summaries →

Meta releases open-weight Muse Glimmer model for agentic tasks

COVERAGE [9]

  1. Simon Willison TIER_1 English(EN) ·

    Introducing Muse Glimmer

    <p><strong><a href="https://research.meta.ai/blog/introducing-muse-glimmer-open-agentic-model">Introducing Muse Glimmer</a></strong></p> Meta are back in the open weights game! Muse Glimmer is a brand new 30B model under a clean Apache 2.0 license (a step up from the janky Llama …

  2. Mastodon — sigmoid.social TIER_1 English(EN) · [email protected] ·

    Muse Glimmer requires 24-32 GB of memory after 4-bit compression. That leaves most laptops with 8-16 GB unable to run it locally. Performance benchmarks outside

    Muse Glimmer requires 24-32 GB of memory after 4-bit compression. That leaves most laptops with 8-16 GB unable to run it locally. Performance benchmarks outside Meta's own testing remain sparse. https://www. implicator.ai/meta-releases-30 b-open-weight-muse-glimmer-and-promises-s…

    LINKS implicator.ai/meta-releases-30b-open-weig…
  3. dev.to — LLM tag TIER_1 English(EN) · Tran Tien Van ·

    Muse Glimmer Production Readiness: A Practical Test Plan

    <p>A reported 30-billion-parameter model that can fit in about 24 GB of VRAM in four-bit-class form sounds like a local-agent milestone. For practitioners, it is better treated as permission to test—not permission to deploy.</p> <h2> Start with the workflow, not the model card </…

  4. r/LocalLLaMA TIER_1 English(EN) · /u/WonderRico ·

    Local Benchmark : Muse Glimmer 30B vs Qwen 3.6 27B vs Gemma4 31B (and many other models and finetunes)

    <table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1vlsixl/local_benchmark_muse_glimmer_30b_vs_qwen_36_27b/"> <img alt="Local Benchmark : Muse Glimmer 30B vs Qwen 3.6 27B vs Gemma4 31B (and many other models and finetunes)" src="https://preview.redd.it/pyodj3c…

  5. r/LocalLLaMA TIER_1 English(EN) · /u/xenovatech ·

    Muse Glimmer 30B running locally in-browser with custom WebGPU kernels at ~25 tok/s on an M4 Max (same speed as llama.cpp)

    <table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1vlmnd4/muse_glimmer_30b_running_locally_inbrowser_with/"> <img alt="Muse Glimmer 30B running locally in-browser with custom WebGPU kernels at ~25 tok/s on an M4 Max (same speed as llama.cpp)" src="https://ext…

  6. r/LocalLLaMA TIER_1 Deutsch(DE) · /u/PathfinderTactician ·

    Tested in Coding: BF16 Muse Glimmer vs BF16 Qwen3.6 27B

    <!-- SC_OFF --><div class="md"><p>I'm guessing that many people have been waiting for this comparison. For clarity, both models are running at full FP16 KV-cache. Due to VRAM limitations, Muse Glimmer is running full 262,144 context, whilst Qwen3.6 27B can only run at 147,500 con…

  7. r/LocalLLaMA TIER_1 (ET) · /u/Thin_Pollution8843 ·

    Muse Glimmer on 1/2 AMD v620

    <!-- SC_OFF --><div class="md"><p>Hey. Just tried it on my old ass gpus 😄 Surprisingly Tensor Split is working on 2 gpus almost doubling PP (wonder how it will work with 4 gpus)</p> <h4>Q6 — 1 GPU</h4> <p><code> llama-server \ --model &lt;MODEL_DIR&gt;/Muse-Glimmer-30B-GGUF/Muse-…

  8. r/LocalLLaMA TIER_1 Deutsch(DE) · /u/NoFaithlessness951 ·

    Muse glimmer benchmark

    <table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1vkxpnd/muse_glimmer_benchmark/"> <img alt="Muse glimmer benchmark" src="https://preview.redd.it/h7tyoi3p6mih1.png?width=140&amp;height=140&amp;crop=1:1,smart&amp;auto=webp&amp;s=bfdb27ed7cc7552a299c8e1e33546a…

  9. r/LocalLLaMA TIER_1 English(EN) · /u/BarberIcy366 ·

    Please Share Your Experience About Muse Glimmer

    <!-- SC_OFF --><div class="md"><p>I have a classic test for local LLM's. I asked for 8 ball pool game with only one HTML file and Muse Glimmer spend 21k Token(I m using full context so 128k) and only created a 220 lines of HTML and said its done. With my experience its not even c…

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