Views
No views yet
mm_proj, visual, etc.) were stripped from the original .safetensors prior to conversion. This makes these GGUF files significantly lighter, faster to load, and perfectly optimized for text-based inference and Roleplay.imatrix.dat) was calculated using a dedicated Roleplay dataset (calib_rp.txt). To ensure the absolute highest precision and retention of character reasoning and uncensored creativity, the calibration was run for an exhaustive ~8,000 chunks.Q4_K_L and Q5_K_L variants, created by forcing the most sensitive components (Embeddings and Output tensors) to 8-bit precision (q8_0), bridging the gap between medium quants and Q6_K.| File Name | Size (GB) | Notes |
|---|---|---|
| Qwen3.6-27B-uncensored-heretic-v2-Q6_K.gguf | 21.56 | Practically identical to FP16. Highest quality. |
| Qwen3.6-27B-uncensored-heretic-v2-Q5_K_L.gguf | 19.55 | Custom large variant (Q8_0 embeddings/output). |
| Qwen3.6-27B-uncensored-heretic-v2-Q5_K_M.gguf | 18.78 | Very high fidelity, recommended. |
| Qwen3.6-27B-uncensored-heretic-v2-IQ5_K_S.gguf | 18.24 | Imatrix optimized 5-bit. |
| Qwen3.6-27B-uncensored-heretic-v2-Q4_K_L.gguf | 17.08 | Custom large variant (Q8_0 embeddings/output). |
| Qwen3.6-27B-uncensored-heretic-v2-IQ4_K_M.gguf | 16.16 | Recommended. Best size/speed/quality ratio. |
| Qwen3.6-27B-uncensored-heretic-v2-Q4_K_S.gguf | 15.22 | Fast and reliable standard 4-bit. |
| Qwen3.6-27B-uncensored-heretic-v2-IQ4_XS.gguf | 14.73 | Highly optimized lower-end 4-bit. |
| Qwen3.6-27B-uncensored-heretic-v2-Q3_K_M.gguf | 12.99 | Great for systems with limited RAM/VRAM. |
| Qwen3.6-27B-uncensored-heretic-v2-Q3_K_S.gguf | 11.79 | Lower quality 3-bit. |
| Qwen3.6-27B-uncensored-heretic-v2-Q2_K.gguf | 10.46 | Heavy compression, noticeable perplexity loss. |
| Qwen3.6-27B-uncensored-heretic-v2-Q2_K_S.gguf | 10.01 | Maximum space saving, for the desperate. |
llama.cpp on Windows:safetensors library:1from safetensors.torch import load_file, save_file
2# Load each .safetensors file, find keys containing "vision", "visual", "mm_proj", etc., delete them, and save.convert_hf_to_gguf.py script provided in the llama.cpp repository:python llama.cpp/convert_hf_to_gguf.py ./base_model --outfile model_fp16.gguf --outtype f16calib_rp.txt for roleplay). Limit the GPU layers (-ngl) and CPU threads (-t) to prevent your system from crashing during this heavy process:llama-imatrix.exe -m model_fp16.gguf -f calib_rp.txt -o imatrix.dat -c 512 --gpu-layers 12 -t 81# Standard
2llama-quantize.exe --imatrix imatrix.dat model_fp16.gguf result_IQ4_K_M.gguf IQ4_K_M
3
4# Custom Large (Q8_0 embeddings)
5llama-quantize.exe --imatrix imatrix.dat --token-embedding-type q8_0 --output-tensor-type q8_0 model_fp16.gguf result_Q4_K_L.gguf Q4_K_M