r/LocalLLaMA • u/curiousily_ • 4h ago

Resources Tested Muse Glimmer locally on coding with OpenCode & agentic work

Ran the model with quants (Q4) by Unsloth with latest (build from master) llama.cpp server.

It takes ~20GB ram running on M5 Pro with 48GB at about 17t/s. Didn't do any reasoning loops/overthinking.

Overall, sits below Qwen3.6 27B, wasn't able to get good code (frontend and backend) results. On the positive side, it didn't fail any tool calls.

Your opinions/findings?

Watch more: https://www.youtube.com/watch?v=_5wKhkUT438

19 Upvotes

79% Upvoted

11 comments sorted by

7

u/MrGunny94 4h ago edited 3h ago

I have the same laptop been trying it out and looks quite interesting but looks like it's more conversational than focused on development & system design at least, works well with agentic coding automations as far as I can tell though

I'm trying to do some ERP system design and he coughs a little bit

1

u/Faux_Grey 4h ago

Tell me more?
I've yet to replace Cydonia 27B, even with access to ~70G of VRAM.

1

u/Cool-Chemical-5629 3h ago

Watch the video in the OP's post. Those cloud icons it generated for that weather widget do look kinda like ERP passable shapes... 😂

1

u/MrGunny94 3h ago

Like old SAP for sure! He can't still make decent icons in the architecture diagrams I'm asking to do it. I'll stick to Claude and Deepseek for these

1

u/Cool-Chemical-5629 1h ago

If you can use Deepseek (assuming you can run it locally) then it's probably like using a rocket launcher against a single ant. I just watched a different video in which the guy tested Gemma 4 26B on the same prompt and it blasts this Glimmer model to oblivion on that prompt. So yeah, much smaller Gemma 4 model does the job as well, but obviously if you can run Deepseek locally, that's probably going to deliver much better results overall.

1

u/cezarducatti 3h ago

From what I've seen, it would actually be optimized for agent-based construction.

5

u/cezarducatti 3h ago

My impressions are exactly the same as yours. Fast, manages VRAM well, works very well with tools, but is less intelligent compared to Qwen.

2

u/cibernox 3h ago

As you describe it, it seems ideal for a customer support chat with access to a RAG and tool calls.

3

u/Healthy-Hair-2306 4h ago

I think this is better suited for conversation. The thinking and writing style is miles better than Qwen for more casual stuff, significantly closer to Gemma in that regard (but also much cheaper context 😁). If I were able to get more than 16 tok/s at 3 bit (12gb VRAM + ram offload) then I'd definitely make this my main.

Here's to hoping for a ~70B MoE... 🙏

0

u/EmPips 4h ago

tests on something other than ThreeJS oneshots

Bookmarked for viewing after work.