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llama-cli -hf liodon-ai/Qwen2.5-Coder-14B-Instruct-imatrix-GGUF:Q4_K_Mollama run hf.co/liodon-ai/Qwen2.5-Coder-14B-Instruct-imatrix-GGUF:Q4_K_Mliodon-ai/Qwen2.5-Coder-14B-Instruct-imatrix-GGUF and pick your quant.| Quant | Size | VRAM est. | Notes |
|---|---|---|---|
IQ2_M | 5.36 GB | ~6 GB | 2-bit, iMatrix — smallest usable |
IQ3_M | 6.92 GB | ~8 GB | 3-bit, iMatrix — great quality/size tradeoff |
IQ4_XS | 8.12 GB | ~9 GB | 4-bit extra-small, iMatrix |
Q4_K_M | 8.99 GB | ~10 GB | 4-bit, iMatrix-calibrated (recommended) |
Q5_K_M | 10.51 GB | ~12 GB | 5-bit, iMatrix-calibrated |
Q6_K | 12.12 GB | ~14 GB | 6-bit, iMatrix-calibrated, near-lossless |
Q8_0 | 15.70 GB | ~18 GB | 8-bit, essentially lossless |
Also see plain (non-iMatrix) quants:liodon-ai/Qwen2.5-Coder-14B-Instruct-GGUF