LFM2.5 2.6B model competitive with 4x larger models
huggingface.co - 86 poäng - 18 kommentarer - 576801 sekunder sedan
Kommentarer (7)
- lend000 - 19694 sekunder sedanI can't imagine who is using something like this for agentic coding, but I see exciting opportunities on the horizon when we can have hundreds of reasonably rational and conversational agents working on local machines to simulate emergent behavior (simulating crowds, markets, ecosystems, game NPCs, etc.)
- Gecko4072 - 21411 sekunder sedanThese LiquidAI models have never worked well for me in practice.
- lostmsu - 14057 sekunder sedanIt's not even competitive with 2x sized Qwen 4B.
Why is Qwen3.5 2B not in the table?
- 0xbadcafebee - 18965 sekunder sedanLFM's training/post-training is famously different than other models. They target reliable operation of tiny models in ways other model families don't (they aren't just scaling a larger model to a smaller size). If you're looking for good performance out of tiny models, LFM has the most advanced design.
Note how they're much smaller than all other models in the comparison yet match or exceed them. This is for 2.6B params, but they have models as small as 230M. Nobody else designs models that small.
- harshshah212003 - 16943 sekunder sedanWill this work in i3/i5 laptops?
- GaggiX - 10678 sekunder sedanThe model is cool but I would prefer if people do not editorialize the titles on their HN submissions.
- madhu_ghalame - 13575 sekunder sedan[dead]
Nördnytt! 🤓