Liquid AI releases six open-weight 2B-class models in the LFM3 series

Oct 28

1. 17:58

   Testing Catalog

   October 28 AI Daily Brief: Genie 4 and MAI-Image-2.7 Released

   Google DeepMind released the interactive world model Genie 4, which supports natural language control and native audio. It is first being opened to Trusted Testers, with later integration into Google AI Ultra and the Gemini API. Microsoft AI launched the image editing model MAI-Image-2.7-Preview, ranking 3rd on Arena Edit and 2nd on AA-Image-Editing. Liquid AI open-sourced the LFM3 series of six 2B-class text, vision, audio, and omni-modal models, using a triple-hybrid architecture.

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2. 14:07

   HaiderRelated discussion

   Haider joined this discussion ↗

   This post contributes to heat; it is not a formal report or confirmed fact.

3. 05:08

   MarkTechPost

   Liquid AI Releases the LFM3 Series of 6 Open-Source 2B-Class Multimodal Models

   Liquid AI has released the LFM3 series, in which 6 open-weight models share a single backbone and cover text, vision, audio, omni-modal, and decision-making tasks, all of which can be fine-tuned on a single GPU. LFM3-1.7B has 1.73B parameters and a 256K context, requires about 1 GB of memory at 4-bit, and scores an average of 49.37 across 29 benchmarks in official evaluations, higher than Qwen3.5-9B's 47.24. The weights are now available on Hugging Face, support formats such as GGUF, MLX, and ONNX, and the threshold for free commercial use is annual revenue of $10 million.

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4. 01:51

   Rohan Paul

   Liquid AI Releases the LFM3 Open-Source Model Family: 1.7B Text Model Surpasses Its 2.6B Predecessor

   Liquid AI has released the LFM3 open-weight model family, comprising 6 model instances and covering text, audio, vision, and omni modalities. Among them, the LFM3-1.7B text model outperforms its 2.6B predecessor in effectiveness, employing a 24-layer tri-hybrid architecture, with 13 layers using short convolutions, 5 layers using 256-token sliding-window attention, and 6 layers performing global attention. In Liquid's self-tested agent benchmarks, this model scores 41.29 on AutomationBench, compared with 15.10 for Qwen3.5-9B.

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5. 01:37

   Unite.AI

   Liquid AI Releases Six 2B-Class Open-Weight Models in the LFM3 Series

   On October 27, Liquid AI released the LFM3 series. All six 2B-parameter-class open-weight models branch from the same LFM3-1.7B-Base, covering text, vision, audio, omni-modal, and decision models. LFM3-1.7B has 1.73B parameters, a 256K token context, supports 16 languages, and adopts a Tri-Hybrid architecture with 13 layers of gated short convolutions, 5 layers of sliding-window attention, and 6 layers of global attention. It is available under the LFM Open License v1.0 on Hugging Face, the Liquid AI Playground, and via API. The company claims that LFM3-1.7B surpasses LFM2.5-2.6B with 35% fewer parameters and occupies about 1 GB of memory at 4-bit precision, but the model card states that it is not suitable for agentic coding or complex multi-step reasoning.

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6. 01:16

   Hugging FaceFirst-partySelected

   Liquid AI Releases the LFM3 Series of Models, Including 1.7B Text, Vision, Audio, and Omni Versions

   Liquid AI has released the LFM3 series of open-weight models, all branched from LFM3-1.7B-Base, covering text, vision, audio, Omni, and the d1 decision model. LFM3-1.7B-Base adopts a three-hybrid-layer architecture, is pretrained on 22T tokens, and in the mid-training stage over the final 3.5T tokens incorporates more agent trajectories and tool-calling data, with the context window extended to 256K tokens. The company says LFM3-1.7B is about 25% faster than LFM2-1.2B at an 8K context, and scores 38.42 versus 3.02 on WebArena-Verified; LFM3-VL-2B's average score across 62 vision benchmarks rises from 57.6 to 71.4. All models are available for download on Hugging Face, along with a single-GPU fine-tuning notebook.

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