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Meta is back with Muse Glimmer: a 30B open-source multimodal model built for local, agentic use. HF is shipping day-0 support and I built a few demos to see what it can do. First: we gave Glimmer tools and asked it to quantize itself.

51,554 次观看 • 2 个月前 •via X (Twitter)

11 条评论

Ben Burtenshaw 的头像
Ben Burtenshaw2 个月前

Next: “Muse Glimmer, deploy yourself.” It deploys to a protected Hugging Face Inference Endpoint, verifies health and chat completion, then connects its claw to the endpoint. You can also just do this with:

Ben Burtenshaw 的头像
Ben Burtenshaw2 个月前

If you just want to try the model, I set up this research agent on the hub:

Ben Burtenshaw 的头像
Ben Burtenshaw2 个月前

Finally, I got it to optimize its own deployment for H100 architecture.

Noé Flandre 的头像
Noé Flandre2 个月前

Sounds like a solid release. Very exciting to see Meta coming back in the OSS game. Let’s see how it holds against 3.8

Ben Burtenshaw 的头像
Ben Burtenshaw2 个月前

Yes! So excited to see what people build with it.

Fajar M Reza 的头像
Fajar M Reza2 个月前

Open-weight multimodal models matter when local agents can inspect tools and images.

Shantanu Goel 的头像
Shantanu Goel2 个月前

is this in hermes?

Ben Burtenshaw 的头像
Ben Burtenshaw2 个月前

openclaw, but I've done similar stuff in Hermes and it works.

Marcus Supersonic 的头像
Marcus Supersonic2 个月前

Self-quantization is a neat demo. Whether agentic tool use holds up on consumer hardware is the actual question.

Ryan 的头像
Ryan2 个月前

@grok what pc specs do you recommend to run this smoothly all day.

Adel Bucetta 的头像
Adel Bucetta2 个月前

haven't seen anyone try to give an AI the task of optimizing its own architecture yet. that's a whole new level of self-awareness

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First impressions on Muse Glimmer! It's incredibly fast for a dense model, currently running an average of 208tps with a max of 274tps on a single 5090 with their DFLASH config. Comparatively, though, both using Open Code, Qwopus Coder (with thinking off) produced a much better shark survival game than the one I got from Glimmer. Meta's new dense model is currently just lacking some HTML canvas taste, but this is something that can be added via SFT as long as the model is stable and capable from a back-end programming perspective. And it seems to be, without a doubt. The big kicker here is that I ran this at extra high thinking, and it did not take long at all to run. Our current local leader, Qwen 27B 3.6, has a tendency to overthink, but with glimmer, that is not the case. Right now, my recommendation for general local programming (Apps, Games, Websites, Visual Tools) in this class is still Qwopus Coder with thinking disabled, or Qwopus Fusion with thinking enabled. Of course Shark Survival is a very basic domain-specific test, but I find that the result scales very well across many domains. If we're going to be shipping apps generated entirely locally, visual taste is somewhat of a bare minimum requirement, solely in my opinion, and Qwen's models in this class offer significantly more at the moment. That's actually why I initially started getting into finetuning with Qwen 3.5, they were the first base that was able to do really good front-end with some opus-trace fine-tuning. Qwen 3.6 has taste even in the base model, and we know Qwen 3.8 is going to blow us all away! Regardless, this looks like a very tempting new base model. As a first offering from Meta in this class for a long time, I am incredibly impressed and elated to have it. We now finally have a proper Single GPU frontier race, instead of us just begging Qwen for more releases. Single GPU open frontier model race is a VERY good thing. Please keep pushing Meta

Kyle Hessling

17,485 次观看 • 2 个月前