LFM3-1.7B-GGUF is now on ModelScope: 256K context, around 1 GB at 4-bit, and edge-first speed in a 1.73B model built for local agents.
🤖 https://modelscope.ai/models/atomic.chat/LFM3-1.7B-GGUF
⚡ Fast at the edge: In Liquid AI’s reported 32K-context evaluation, LFM3-1.7B delivered at least 2.5× faster prefilling and 1.8× faster decoding than every compared model across three tested devices.
📚 256K context in 1.73B parameters: Built for long prompts, local agents, tool calling, structured output, and domain-specific applications.
💾 Fits lightweight hardware: At 4-bit precision, the original model uses about 1 GB of memory, making local use practical on phones and laptops.
📦 Quantization trade-offs are documented: This GGUF release ranges from 1.85 GB for Q8_0 to 0.92 GB for IQ3_S. In the publisher’s evaluation, Q8_0 retains 96.3% top-1 agreement with a 0.004 mean KLD versus the reference model.
🛠️ Local-first deployment: Run it with an LFM3-compatible llama.cpp build, Ollama, or LM Studio. The original checkpoint also supports single-GPU fine-tuning for domain-specific workflows.
📜 LFM Open License v1.0. This is a GGUF conversion by Atomic Chat; the original model is from Liquid AI.