Liquid AI 发布 LFM3 系列新一代基础模型，包含 6 个约 2B 规模的模型实例，覆盖文本、视觉、音频、omni 和决策任务，采用新的 tri-hybrid 架构。其中 LFM3-1.7B 文本模型支持 256k 上下文窗口，为 Hermes Agent 和 Pi 等智能体框架训练，在 Liquid 自己的 WebArena-Verified 评测中得 38.4 分，高于 Qwen3.5-9B 的 28.9；LFM3-VL-2B 号称可与更大的 Gemma 4 12B 和 Gemini 3.5 Flash Lite 竞争。全系模型可在单张 GPU 上微调，架构针对 GPU、CPU、NPU 共 14 类处理器优化，适合本地常驻智能体场景。
作者梳理了 LFM3 家族的模态覆盖、上下文长度和基准对比，读者可以据此评估小模型跑本地智能体的可行性。
You don't see releases like this every day.
Liquid AI just released LFM3, a family of ~2B open-weight models for text, vision, audio, omni, and decision tasks, all on one shared backbone.
LFM3-1.7B is trained to run in agent harnesses like Hermes Agent and Pi, with a 256K context.
On WebArena-Verified, it scores 38.4 vs. 28.9 for Qwen3.5-9B in Liquid's evaluation. Models can be fine-tuned on a single GPU.
This series of models has huge potential for always-on local agents.
Introducing 𝙻𝙵𝙼𝟹: our new generation of Liquid Foundation Models. With a new tri-hybrid architecture and new multimodal encoders, the LFM3 family is the ideal model suite for specialized intelligence. > 6 model instances, across text, audio, vision, and omni modalities, generative and decision models. > 𝙻𝙵𝙼𝟹-𝟷.𝟽𝙱: text, 256k context window. > 𝙻𝙵𝙼𝟹-𝚅𝙻-𝟸𝙱: vision-language model with video-input support for spatial understanding > 𝙻𝙵𝙼𝟹-𝙰𝚞𝚍𝚒𝚘-𝟸𝙱: tool calls, voice chat, reasoning in 18 languages. > 𝙻𝙵𝙼𝟹-𝙾𝚖𝚗𝚒-𝟸𝙱: an omni model combines vision, audio, and language. > 𝚍𝟷-𝟸𝙱 and 𝚍𝟷-𝙾𝚖𝚗𝚒-𝟸𝙱: decision models with typed outputs and calibrated probabilities in a single pass. Omni adds audio input. > fine-tune on 1 GPU. > a new tri-hybrid architecture > architecture optimized for 14 processor classes across GPUs, CPUs, and NPUs. > 𝙻𝙵𝙼𝟹-𝚅𝙻-𝟸𝙱 is a beast. It performs competitively with Gemma 4 12B (6x larger), and Gemini 3.5 Flash Lite, and GPT-5.6 Luna, with 1.9B parameters. > 𝙻𝙵𝙼𝟹-𝟷.𝟽𝙱 is #1 on the Pareto frontier of device intelligence 𝚙𝚒𝚙𝚎𝚝𝚝𝚎.𝚕𝚒𝚚𝚞𝚒𝚍.𝚊𝚒 Every modality for specialized intelligence. Pick the one that fits your use case, customize it, and run it on-device. 1/ 🧵在 X 查看被引用的帖子
来源：elvis · x.com