by meatmanek
1 subcomments
- This model is pretty cool if you don't have a GPU - I was able to get I think 20 or 30 tokens per second on CPU (DDR4 ram) alone. (I don't remember if that was with q4 or q8.)
Otherwise, if you have a GPU with more than like 4GB of VRAM, there are better models. Gemma4 and Qwen3.6 (or Qwen3.5 if you need the smaller dense models that haven't yet been released for 3.6) are a good place to start.
- Liquid AI have made some awesome models (especially the smaller ones, they are lightning fast). I wish they made a fast small size coder. Did a finetune distill of 0.8B myself and it is in fact working properly, coding like a 30B model, so I know it is possible.
Anyway here you have the 24B parameters with 2B active: https://hugston.com/models/lfm2-24b-a2b-q4-k-m
- The blog post was published a couple months ago, and it looks like there hasn't been a follow-up release with the fully trained model. I'm not sure if there's much to take away from an early checkpoint besides the unique architectural choices they made in their model for faster inference.
- I just tried the Q4_K_M variant of this [] and this is one of the first models that run at ~20tps on my laptop. I also tried it with some "hard" maths questions and it clearly knows much. Can't wait to try some local coding agent harnesses with it (I recently discovered kon [1] and dirac [2] and wanted to try them out)
The only thing I'm not sure about is if this model supports thinking or not.
[1]: https://github.com/0xku/kon
[2]: https://github.com/dirac-run/dirac
by BoredomIsFun
1 subcomments
- LFM models I've tried all seemed to be suffering from serious coherence issues. I found Gemmas the best at tasks requiring rock solid coherent output; even Qwen's not comparable.
by alfiedotwtf
1 subcomments
- Tokens per second is nice but I would also like to see quality benchmarks especially against other models. I mean eventually someone’s gonna write a blog post comparing models, so why not just do it yourself… that way your marketing department at least get to control the narrative rather than a random blogger
by potatobanana
0 subcomment
- I liked LFM2-8B-A1B for its speed on cpu or integrated gpu. This one is slower. I used it recently while coding in offline stressful situation and it is good enough to propose an ok suggestion how to solve a simple to intermediate problem in a bit obscure language. But multi turn iteration was not working well. The code was working but it didn't exactly fulfill all expectations from next turns. Good enough to help though and take it further, so helpful.
- Comparison with Qwen3.6 35B A3B:
- GPQA Diamond: 47.4% vs 84.1% for Qwen
- HLE: 4.4% vs 20.2% for Qwen
- AA Omniscience Accuracy: 6.4% vs 18.9% for Qwen
- AA Hallucination Rate: 30.0% vs 50.3% for Qwen
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