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*self_attn*, *router*, lm_head, i.e., only MoE MLP linear layers are quantized.1python examples/torch/language_modeling/llm_ptq/quantize_quark.py \
2 --multi_gpu \
3 --model_dir openai/gpt-oss-20b \
4 --quant_scheme w_mxfp4_a_fp8 \
5 --kv_cache_dtype fp8 \
6 --exclude_layers "*self_attn*" "*router*" "lm_head" \
7 --dataset pileval \
8 --num_calib_data 128 \
9 --output_dir amd/gpt-oss-20b-MoE-Quant-W-MXFP4-A-FP8-KV-FP8 \
10 --model_export hf_format \
11 --skip_evaluation| Model name | Weight | Activation | KV cache | Exclude | gpqa_diamond_generative_n_shot (5) | gsm8k_platinum | ||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| TP1 | TP2 | TP4 | TP8 | TP1 | TP2 | TP4 | TP8 | |||||
| openai/gpt-oss-20b | MXFP4 | BF16 | BF16 | - | 0.5606 | 0.5303 | 0.5657 | 0.5606 | 0.9016 | 0.9024 | 0.9032 | 0.8966 |
| amd/gpt-oss-20b-WMXFP4-AFP8-KVFP8 (this one) | MXFP4 | FP8 | FP8 | *self_attn* *router* lm_head | 0.5303 | 0.5556 | 0.5152 | 0.5404 | 0.8999 | 0.8900 | 0.8958 | 0.9098 |
http://www.apache.org/licenses/LICENSE-2.0