Unverified50% confidenceFactExact time
The six LFM3 models use open weights, share the same backbone network, and cover text, vision, audio, omni-modal and decision models.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/28/2026
First Seen
Valid until: 1/26/2027
Sources
Liquid AI Releases LFM3: Six 2B-Class Models Covering Full Edge Multimodality
producthuntProductHunt Daily10/28/2026
Related Entities
Related Claims
UnverifiedThe design goal of LFM3 is to handle multiple data types uniformly within a single model system, rather than maintaining a separate model for each modality.75% similarUnverifiedA multimodal model refers to a model capable of simultaneously processing multiple input forms such as text, images, and audio.67% similarUnverifiedThe LFM series consists of small-parameter models designed for edge and on-device use, and the 1.2B size means it can only be optimized through extreme compression of the inference path.65% similarUnverifiedLLaMA-Factory is one of the most mainstream open-source large model fine-tuning frameworks, supporting supervised fine-tuning (SFT) and reinforcement learning from human feedback (RLHF) and other fine-tuning methods for dozens of mainstream open-source models including LLaMA, Qwen, and ChatGLM.64% similarUnverifiedIn a multi-model composite architecture, different stages can be routed to different models (for example, calling a VLM for visual understanding and a general language model for long-text reasoning) to strike a balance among latency, cost and accuracy.64% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1107439API
curl https://kongchang.com/api/v1/knowledge/claims/1107439MCP
get_claim(id=1107439)