Liquid AI announces open-weight LFM3 models near 2B parameters
First merged summary.
Liquid AI has announced LFM3, open-weight models near 2B parameters, with LFM3-1.7B offering a 256K context.
Liquid AI announced LFM3, a family of Liquid Foundation Models around 2B parameters that share one backbone for text, vision, audio, omni, and decision models. Hacker News reports the first release is open-weight and available on Hugging Face, the Liquid AI Playground, and the Liquid AI API. LFM3-1.7B-Base was pre-trained on 22T tokens; a final 3.5T-token mid-training stage extends context to 256K. MarkTechPost’s headline says six open-weight 2B-class multimodal models, while Hacker News does not state that count. The Hugging Face blog and MarkTechPost page bodies do not add license, benchmark, or model-card details.
- LFM3-1.7B-Base was pre-trained on 22 trillion tokens.
- Context reaches 256K after a 3.5T-token mid-training stage.
- Architecture: 13 convolution, five sliding-window, six global-attention layers.
- Liquid AI says it is about 25% faster per parameter than LFM2-1.2B at 8K.
- Post-trained for Hermes Agent, Pi, and OpenClaw harnesses.
- Hardware search covered 14 device and backend combinations.
Timeline
dated events in the reporting · oldest first- Oct 27, 2026Liquid AI announces the LFM3 model family. · Hacker News
What each outlet adds
beyond the shared facts- Hacker NewsArchitecture, token counts, context, speed claim, and availability.
- MarkTechPostHeadline states six open-weight 2B-class multimodal models.
- Vendors
- Liquid AI
- Organizations
- AMDAmbarellaLiquidAIHugging Face
- AI models
- LFM3LFM3-1.7BLFM3-1.7B-Base
Coverage
oldest first · one row per article · UTCLiquid AI releases open-weight multimodal LFM3 models around 2B
LFM3-1.7B-Base was pre-trained on 22T tokens, with a 256K context after mid-training.
Hugging Face blog post covers building models with LFM3
No article body was available, so LFM3's capabilities, license, and availability are not stated.
Liquid AI releases LFM3, six open-weight 2B models
The available text is only the headline; licenses, benchmarks, and release details are not included.