Liquid AI opens LFM3 weights: 1.7B to 2B-class text, vision, audio and omni models that fine-tune on a single GPU
A family of small models on one shared backbone, pitched as the starting point for specialized models, with fine-tuning notebooks and a local agent guide.
// Key points
- The lineup is LFM3-1.7B (text), LFM3-VL-2B (images and video), LFM3-Audio-2B (speech in and out), LFM3-Omni-2B (all modalities), plus d1-2B and d1-omni-2B for calibrated answers, all open-weight on Hugging Face.
- LFM3-1.7B scores 38.42 on WebArena-Verified versus 3.02 for LFM2.5-2.6B, with 35% fewer parameters.
- LFM3-VL-2B raises the average across 62 vision benchmarks from 57.6 (LFM2.5-VL-3B) to 71.4, at 1.9B versus 3.1B parameters.
- Every model fine-tunes on a single GPU, with cookbook Colab notebooks for SFT, DPO, GRPO and continued pretraining; the post does not state a license.
Builder's takeA 2B-class model going from 3 to 38 on web-agent tasks says small on-device models are starting to do real work. For high-volume, low-difficulty jobs in AI Cloud Drive such as file classification and screenshot reading, I would fine-tune LFM3-VL-2B on our own data. Until the license is clear, keep it to internal evaluation, not production.
// Background · from #Open models
Full timeline →- Oct 27 Cloudflare discloses a GLM-5.3 cross-request leak: 155 responses carried other customers' data, caused by a KV pool smaller than the context window plus an SGLang bug
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