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What changedMarkTechPost says LFM3’s free commercial use is limited by a $10 million annual revenue threshold. That is a significant qualification for businesses weighing the models: “open-weight” does not necessarily mean free commercial use at every scale.
The report says Liquid AI supports GGUF, MLX, ONNX, FP8 and NVFP4 checkpoints, with runtimes including llama cpp, MLX, vLLM, SGLang, Ollama and Transformers. It also says the models were tuned across 14 device and backend combinations, including a Raspberry Pi 5 and Qualcomm’s Hexagon NPU.
For local use, MarkTechPost says LFM3-1.7B has 1.73 billion parameters and a 256K context window; it reports that a full 128K context needs 1.6GB of KV cache. Those details make the deployment trade-offs more concrete, while the performance figures in the report remain claims attributed to Liquid AI rather than independent evaluations.
Sources and evidence- Liquid AI Releases LFM3: 6 Open-Weight 2B-Class Multimodal Models – MarkTechPost: MarkTechPost says Liquid AI’s LFM3 models support free commercial use only up to a $10 million annual revenue threshold and reports additional deployment formats, runtimes and model specifications.
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