LFM2.5-24B-A2B-Uncensored-GGUF

GGUF quantizations of pottokao/LFM2.5-24B-A2B-Uncensored (LiquidAI LFM2.5-24B-A2B decensored with Heretic ARA, searched and tested with thinking enabled; see the main repo for results).

IQ quants are fastest fully on GPU; if you offload experts to CPU, prefer the K-quants.

• All files keep every attn_output tensor at Q8_0 (--tensor-type attn_output=q8_0): the decensoring edit lives in blk.22.attn_output and blk.26.attn_output, and the 10 attention outputs together are only ~40M parameters.
• imatrix computed on the decensored BF16 GGUF with bartowski's calibration_datav3.
• Converted and quantized with llama.cpp 0a1ef30.

KV cache is small (only 10 of 40 layers are attention, ~20 KB per token in F16), so most of the VRAM goes to weights.

llama-server -m LFM2.5-24B-A2B-Uncensored-IQ3_M.gguf -ngl 99 -c 32768 --jinja \
  --temp 0.1 --top-k 50 --repeat-penalty 1.05

The model always thinks before answering; allow a generous output budget. Liquid AI's official DSpark draft targets the original weights (acceptance on this model not yet measured).

⚠️ Notice

Refusal behavior has been substantially reduced. Intended for research, red-teaming and personal use; you are responsible for your use and for complying with laws and the base model license.

License & credits

Derivative of LiquidAI/LFM2.5-24B-A2B under the LFM Open License v1.0. Decensoring with Heretic (p-e-w, AGPL-3.0) / ARA. Quantized with llama.cpp.