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Liquid AI released LFM2.5-8B-A1B, an edge MoE model trained on 38T tokens with a 128K context window, improved tool calling, and reasoning capabilities, available on Hugging Face.
Liquid AI released LFM2.5-8B-A1B, an edge model with a 128K context window, 38T tokens of pre-training, and large-scale reinforcement learning, capable of tool calling and complex tasks while fitting on an entry-level laptop.
Liquid AI releases LFM2.5-8B-A1B, an 8B MoE model with 1.5B active parameters and 128K context, optimized for edge devices.
LottoLabs announces LiquidAI's LFM2.5-8B-A1B-GGUF model, an 8B parameter model trained on a massive token count and optimized for fast inference on limited GPU hardware, with support for llama.cpp, Ollama, vLLM, and more.
LiquidAI releases a GGUF quantized version of their LFM2.5-8B-A1B model, with instructions for use across multiple inference engines.
A tweet argues the next AI boom will be compact intelligence on edge devices rather than larger data centers, with Liquid AI supporting the vision of running AI on phones, cars, and everyday devices.