LFM3-VL-2B
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Headlines · 3
- Private Mind adds offline LFM3 inference on iOS and Android
The developer of the open-source Private Mind app reports that it now runs LFM3 models fully offline on iOS and Android, including the LFM3-VL-2B vision model. They also published ExecuTorch exports for LFM3 and reported iPhone 16 Pro results of about 40 tokens per second for 4-bit LFM3-1.7B, versus about 20 tokens per second for LFM3-VL-2B after an approximately nine-second first-token delay. The exports use MLX for Apple GPUs and XNNPACK for mobile CPUs, with reported model sizes of 1.07 GB and 1.17 GB respectively.
r/LocalLLaMA · 🔥 2 - LFM3-VL-2B WebGPU demo offers local in-browser video captioning
A Hugging Face Space demonstrates real-time video captioning with LFM3-VL-2B running locally in a browser through WebGPU. The community post provides no benchmarks or independent verification of the demo’s real-time performance.
r/LocalLLaMA · 🔥 0 - Liquid AI Releases the Open-Weight LFM3 Multimodal Model Family
Liquid AI released LFM3, a family of six models in the roughly 2B-parameter range covering text, vision, audio, omni, and decision tasks on a shared hybrid backbone. The models were pretrained on 22T tokens, and the base and post-trained weights are available through Hugging Face, Liquid AI Playground, and the Liquid AI API. Liquid AI says LFM3-1.7B uses 35% fewer parameters than LFM2.5-2.6B, occupies about 1 GB at 4-bit precision, and supports a 256K-token context window.
Liquid AI Blog · 🔥 0
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