How to use from
llama.cpp
Install from brew
brew install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf ASTAROTH0405/LFM2-8B-A1B-GGUF:
# Run inference directly in the terminal:
llama-cli -hf ASTAROTH0405/LFM2-8B-A1B-GGUF:
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama-server -hf ASTAROTH0405/LFM2-8B-A1B-GGUF:
# Run inference directly in the terminal:
llama-cli -hf ASTAROTH0405/LFM2-8B-A1B-GGUF:
Use pre-built binary
# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf ASTAROTH0405/LFM2-8B-A1B-GGUF:
# Run inference directly in the terminal:
./llama-cli -hf ASTAROTH0405/LFM2-8B-A1B-GGUF:
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf ASTAROTH0405/LFM2-8B-A1B-GGUF:
# Run inference directly in the terminal:
./build/bin/llama-cli -hf ASTAROTH0405/LFM2-8B-A1B-GGUF:
Use Docker
docker model run hf.co/ASTAROTH0405/LFM2-8B-A1B-GGUF:
Quick Links
Liquid AI

LFM2-8B-A1B-GGUF

LFM2 is a new generation of hybrid models developed by Liquid AI, specifically designed for edge AI and on-device deployment. It sets a new standard in terms of quality, speed, and memory efficiency.

We're releasing the weights of our first MoE based on LFM2, with 8.3B total parameters and 1.5B active parameters.

  • LFM2-8B-A1B is the best on-device MoE in terms of both quality (comparable to 3-4B dense models) and speed (faster than Qwen3-1.7B).
  • Code and knowledge capabilities are significantly improved compared to LFM2-2.6B.
  • Quantized variants fit comfortably on high-end phones, tablets, and laptops.

Find more information about LFM2-8B-A1B in our blog post.

🏃 How to run LFM2

Example usage with llama.cpp:

llama-cli -hf LiquidAI/LFM2-8B-A1B-GGUF
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GGUF
Model size
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Architecture
lfm2moe
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