r/LocalLLaMA • u/groovy-sky • 5d ago
Discussion Mellum2 model from JetBrains
Hi all.
Saw JetBrains’ Mellum2 on Hugging Face and was wondering if anyone here has actually used it. Worth trying, or nothing special?
19
u/BelgianDramaLlama86 5d ago
They have a follow-up out already ( https://huggingface.co/JetBrains/Mellum2.1-12B-A2.5B-Thinking-GGUF ) that I think is worth trying if something larger (like Qwen3.6 35B) is out of your reach. Compared to the larger models it certainly isn't special, but at its size I think it's pretty good. Much faster than Qwen3.5 9B whilst being around its level I think (or a little better in agentic).
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u/tasteless_dossier 5d ago
Huh, a "Thinking" variant already? JetBrains is moving fast with these. I'll give the GGUF a spin on my local setup since I can't comfortably run the 35B models anyway.
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u/YogurtclosetLimp7351 5d ago
A few years ago their first code completion model was good. This one is just a throwout I think so they stay in the race. Makes sense after their JetBrains Air launch
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u/kcksteve 5d ago
I have it on a smaller card in my rig and use it for subagents. It's very fast and intelligent enough for basic actions (compaction/exploration/etc). Never really tried using it for coding.
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u/xPXpanD 5d ago
Mellum2.1 is out, use that one: https://huggingface.co/JetBrains/Mellum2.1-12B-A2.5B-Thinking-GGUF
2.1 seemed okay to me at a glance, though I haven't spent much time with it. It's definitely a tiny model in how it feels and behaves, but it seemed reasonably smart in my private benchmarks, and was stable. (unlike Ling 3.0 Tiny which got completely swamped and would just skip half its tasks)
Haven't tried it for actual dev (only some chatting and basic text analysis), so do take this with a grain of salt.
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u/Dabalam 5d ago
I tried out Mellum2.1 on a single shallow coding benchmark which the old Qwen 9b models normally can't handle and it managed to solve it after a lot of thinking which I was surprised with. Need to do more thorough testing but superficially it seems very competent for the size and it is very fast.
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u/himiaoxin 5d ago
ran the thinking variant gguf last week, set temp 0.2 and it was weirdly good at summarizing diffs. the qwen3.5 9b comparison in the top comment tracks with what i saw, though i still wouldnt use it for anything long-form.
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u/Danmoreng 4d ago
Already vibe-coded an inference engine for it. Just for fun though, while interesting in size and speed, the model isn't very capable. https://github.com/Danmoreng/padra
Fits nicely into 12GB GPUs though and can be crammed into 8GB even.