Qwen 3.5 397B-A17B — H100 vs MI300X
Head-to-head AI inference benchmark comparison of H100 (NVIDIA Hopper) and MI300X (AMD CDNA 3) on Qwen 3.5 397B-A17B. Latency, throughput, and cost across LLM workloads. Use the chart controls below to switch sequences, precisions, and metrics — same interactions as the main inference chart.
H100 posts 1033 tok/s/GPU for $0.35 per million tokens at 43 tok/s/user on Qwen 3.5 397B-A17B; MI300X posts 346 tok/s/GPU for $0.89. H100 is 154% cheaper per token; H100 delivers 199% more tok/s/GPU.
Throughput at 53 tok/s/user on Qwen 3.5 397B-A17B: H100 hits 776 tok/s/GPU, MI300X hits 190. Per-million costs land at $0.47 and $1.63 respectively. H100 is 249% cheaper per token; H100 delivers 309% more tok/s/GPU.
H100 / MI300X on Qwen 3.5 397B-A17B at 62 tok/s/user: 447 / 123 tok/s/GPU, $0.82 / $2.52 per million tokens. H100 is 207% cheaper per token; H100 delivers 264% more tok/s/GPU. (Numbers reflect the default 1k/1k · fp8 selection for this URL — table and chart below update if you change sequence, precision, or model in the controls.)
| Metric | Interactivity (tok/s/user) | Interactivity (tok/s/user) | Interactivity (tok/s/user) |
|---|---|---|---|
| Throughput (tok/s/gpu) | H100:1032.9MI300X:345.8 | H100:775.8MI300X:189.5 | H100:446.6MI300X:122.7 |
| Cost ($/M tok) | H100:$0.351MI300X:$0.893 | H100:$0.468MI300X:$1.633 | H100:$0.818MI300X:$2.517 |
| tok/s/MW | H100:597043MI300X:193162 | H100:448438MI300X:105886 | H100:258172MI300X:68573 |
| Concurrency | H100:~106MI300X:~34 | H100:~67MI300X:~15 | H100:~29MI300X:~8 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.