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update auto_scheme_acc doc #2000

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update auto_scheme_acc doc
n1ck-guo Jul 6, 2026
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Merge branch 'main' of https://github.com/intel/auto-round into hengg…
n1ck-guo Jul 6, 2026
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96 changes: 96 additions & 0 deletions docs/auto_scheme_acc.md
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Expand Up @@ -30,6 +30,102 @@ evalscope eval --model qwen3-8b --api-url http://127.0.0.1:8001/v1 --api-key E
| qwen3.5-4b: Fake quantized model | 0.505 | 0.3172 | 0.5948 |


### GGUF Format results

@wenhuach21 wenhuach21 Jul 6, 2026

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similar title

**using lm_eval to eval**
```bash
lm_eval --model hf --model_args pretrained=test_gguf/,gguf_file=Qwen3-8B-Q4_K_M.gguf --device cuda:0 --tasks arc_challenge,arc_easy,boolq,hellaswag,lambada_openai,mmlu,openbookqa,piqa,truthfulqa_mc1,winogrande
```
| Qwen3-8B | Quant Type | Actual Bits | Avg Acc | arc_challenge | arc_easy | boolq | hellaswag | lambada_openai | openbookqa | piqa | truthfulqa_mc1 | winogrande | mmlu |

|--------|------------|-------------|---------|---------------|----------|-------|-----------|----------------|------------|------|----------------|------------|------|

| f16 | f16 | 16 | | | | | | | | | | | |

| unsloth | Q2_K | 3.20 | 0.6075 | 0.5145 | 0.8051 | 0.8526 | 0.5309 | 0.6255 | 0.3166 | 0.7530 | 0.3452 | 0.6590 | 0.6729 |

| unsloth | Q2_K_L | 3.34 | 0.6078 | 0.5128 | 0.8068 | 0.8529 | 0.5295 | 0.6276 | 0.3189 | 0.7546 | 0.3427 | 0.6567 | 0.6750 |

| bartowski | Q2_K | 3.20 | 0.6071 | 0.5128 | 0.8018 | 0.8511 | 0.5312 | 0.6257 | 0.3100 | 0.7568 | 0.3366 | 0.6677 | 0.6772 |

| bartowski | Q2_K_L | 3.79 | 0.5761 | 0.5162 | 0.8018 | 0.5306 | 0.5306 | 0.6266 | 0.3120 | 0.7606 | 0.3305 | 0.6717 | 0.6806 |

| auto_round | 2.5b mixed[q2,q3,q4] | 3.23 | 0.6153 | 0.5239 | 0.8102 | 0.8615 | 0.5242 | 0.6598 | 0.3140 | 0.7503 | 0.3390 | 0.6756 | 0.6943 |

| auto_round | 2.5b mixed[q2,q3,q4] lm_head Q6K | 3.25 | 0.6093 | 0.5060 | 0.8093 | 0.8538 | 0.5119 | 0.6598 | 0.3040 | 0.7459 | 0.3256 | 0.6835 | 0.6929 |

| auto_round | 2.5b mixed[q2,q3,q4,q6] | 3.24 | 0.6074 | 0.5034 | 0.8131 | 0.8508 | 0.5109 | 0.6571 | 0.3020 | 0.7470 | 0.3317 | 0.6685 | 0.6897 |

| auto_round | 2.5b mixed[q2,q3,q4,q6] iters 200 | 3.25 | 0.6046 | 0.5060 | 0.8136 | 0.8541 | 0.5234 | 0.6565 | 0.3040 | 0.7606 | 0.3403 | 0.6827 | 0.6919 |

| unsloth | Q3_K_M | 4.02 | 0.6260 | 0.5503 | 0.8270 | 0.8596 | 0.5589 | 0.6301 | 0.3120 | 0.7655 | 0.3770 | 0.6677 | 0.7115 |

| bartowski | Q3_K_M | 4.02 | 0.6246 | 0.5478 | 0.8304 | 0.8606 | 0.5554 | 0.6321 | 0.3200 | 0.7661 | 0.3647 | 0.6575 | 0.7118 |

| auto_round | 3.5b mixed[q2,q3,q4] | 4.17 | 0.6284 | 0.5478 | 0.8300 | 0.8648 | 0.5651 | 0.6429 | 0.3100 | 0.7612 | 0.3574 | 0.6819 | 0.7225 |

| auto_round | 3.5b mixed[q2,q3,q4] lm_head Q6K | 4.19 | 0.6251 | 0.5384 | 0.8338 | 0.8609 | 0.5581 | 0.6354 | 0.3160 | 0.7612 | 0.3574 | 0.6725 | 0.7175 |

| auto_round | 3.5b mixed[q2,q3,q4,q6] | 4.19 | 0.6246 | 0.5401 | 0.8259 | 0.8624 | 0.5582 | 0.6387 | 0.3080 | 0.7628 | 0.3586 | 0.6725 | 0.7191 |

@wenhuach21 wenhuach21 Jul 6, 2026

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table format is incorrect


| auto_round | 3.5b mixed[q2,q3,q4,q6] iters 200 | 4.19 | 0.6318 | 0.5520 | 0.8346 | 0.8676 | 0.5624 | 0.6404 | 0.3160 | 0.7682 | 0.3696 | 0.6890 | 0.7183 |

| unsloth | Q4_K_M | 4.90 | 0.6308 | 0.5520 | 0.8329 | 0.8691 | 0.5685 | 0.6437 | 0.3180 | 0.7568 | 0.3623 | 0.6803 | 0.7248 |

| bartowski | Q4_K_M | 4.90 | 0.6301 | 0.5546 | 0.8359 | 0.8654 | 0.5655 | 0.6443 | 0.3120 | 0.7612 | 0.3599 | 0.6748 | 0.7269 |

**using llama-server and evalscope to eval**
```bash
llama-server \
--model test_gguf/Qwen3-8B-Q2_K_S.gguf \
--host 127.0.0.1 \
--port 8001 \
--alias qwen \
--ctx-size 65536 \
--gpu-layers all \
--parallel 16 \
--predict 2048 \
--reasoning off \
--no-webui \
```
```bash
evalscope eval \
--model qwen \
--api-url http://127.0.0.1:8001/v1 \
--api-key EMPTY \
--datasets math_500 \
--eval-batch-size 16
```

| Qwen3-8B | Quant Type | Actual Bits | gpqa_diamond | math_500 |

|--------|------------|-------------|--------------|----------|

| f16 | f16 | 16 | 0.4596 | 0.798 |

| unsloth | Q2_K | 3.20 | 0.3131 | 0.726 |

| unsloth | Q2_K_L | 3.34 | 0.3788 | 0.732 |

| auto_round | 2.5b mixed[q2,q3,q4] | 3.23 | 0.3636 | 0.706 |

| auto_round | 2.5b mixed[q2,q3,q4] lm_head Q6K | 3.25 | 0.3485 | 0.714 |

| auto_round | 2.5b mixed[q2,q3,q4,q6] | 3.24 | 0.3687 | 0.698 |

| auto_round | 2.5b mixed[q2,q3,q4,q6] iters 200 | 3.25 | 0.3990 | 0.700 |

| unsloth | Q3_K_M | 4.02 | 0.4192 | 0.778 |

| auto_round | 3.5b mixed[q2,q3,q4] | 4.17 | 0.4495 | 0.816 |

| auto_round | 3.5b mixed[q2,q3,q4] lm_head Q6K | 4.19 | 0.4495 | 0.788 |

| auto_round | 3.5b mixed[q2,q3,q4,q6] | 4.19 | 0.4444 | 0.814 |

| auto_round | 3.5b mixed[q2,q3,q4,q6] iters 200 | 4.19 | 0.5051 | 0.788 |

| unsloth | Q4_K_M | 4.90 | 0.4545 | 0.792 |

### Other results

We use **lm-eval** for evaluation. For LLaMA, we enabled `add_bos_token` and
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