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LFM2.5-1.2B-Instruct-GGUF

by LiquidAI · source Hugging Face · updated 2026-09-22

other697 MB~2 GB RAMsource aliveunlabeled

LFM2.5 is a new family of hybrid models designed for on-device deployment. It builds on the LFM2 architecture with extended pre-training and reinforcement learning.

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Numbers

Numbers as of 2026-10-02 21:00 UTC, from the source API.

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Files

filequantsize
LFM2.5-1.2B-Instruct-BF16.ggufBF162.2 GB
LFM2.5-1.2B-Instruct-F16.ggufF162.2 GB
LFM2.5-1.2B-Instruct-Q4_0.ggufQ4_0664 MB
LFM2.5-1.2B-Instruct-Q4_K_M.ggufQ4_K_M697 MB
LFM2.5-1.2B-Instruct-Q5_K_M.ggufQ5_K_M804 MB
LFM2.5-1.2B-Instruct-Q6_K.ggufQ6_K918 MB
LFM2.5-1.2B-Instruct-Q8_0.ggufQ8_01.2 GB
LFM2.5-1.2B-Instruct-QAD-Q4_0.ggufQ4_0664 MB
qad/model.safetensors4.4 GB

From the source README

Try LFM • Docs • LEAP • Discord

LFM2.5-1.2B-Instruct

LFM2.5 is a new family of hybrid models designed for on-device deployment. It builds on the LFM2 architecture with extended pre-training and reinforcement learning.

Find more details in the original model card: https://huggingface.co/LiquidAI/LFM2.5-1.2B-Instruct

🏃 How to run LFM2.5

Example usage with llama.cpp:

llama-cli -hf LiquidAI/LFM2.5-1.2B-Instruct-GGUF --conversation \
    --temp 0.1 --top-k 50 --repeat-penalty 1.05

QAD Q4_0 GGUF

The Quantization-Aware Distillation (QAD) checkpoint is available as
`LFM2.5-1.2B-Instruct-QAD-Q4_0.gguf`.

This is distinct from the post-training-quantized `LFM2.5-1.2B-Instruct-Q4_0.gguf`;
both use the GGUF Q4_0 format.

Example usage with llama.cpp:

llama-cli -hf LiquidAI/LFM2.5-1.2B-Instruct-GGUF \
  --hf-file LFM2.5-1.2B-Instruct-QAD-Q4_0.gguf \
  -p "What is C. elegans?"

Card id model:hf:LiquidAI/LFM2.5-1.2B-Instruct-GGUF · collected 2026-10-02 21:00 UTC · JSON