gpt-oss 120B — H200 vs MI300X
Head-to-head AI inference benchmark comparison of H200 (NVIDIA Hopper) and MI300X (AMD CDNA 3) on gpt-oss 120B. 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.
At 92 tok/s/user interactivity on gpt-oss 120B, H200 delivers 3635 tok/s/GPU at $0.11 per million tokens; MI300X delivers 2051 tok/s/GPU at $0.15. H200 is 38% cheaper per token; H200 delivers 77% more tok/s/GPU at this point.
H200 posts 2018 tok/s/GPU for $0.20 per million tokens at 144 tok/s/user on gpt-oss 120B; MI300X posts 957 tok/s/GPU for $0.32. H200 is 64% cheaper per token; H200 delivers 111% more tok/s/GPU.
Throughput at 197 tok/s/user on gpt-oss 120B: H200 hits 1085 tok/s/GPU, MI300X hits 355. Per-million costs land at $0.36 and $0.87 respectively. H200 is 139% cheaper per token; H200 delivers 206% more tok/s/GPU. (Numbers reflect the default 1k/1k · fp4 selection for this URL — table and chart below update if you change sequence, precision, or model in the controls.)
| Metric | Interactivity (tok/s/user) | Interactivity (tok/s/user) | Interactivity (tok/s/user) |
|---|---|---|---|
| Throughput (tok/s/gpu) | H200:3634.9MI300X:2050.9 | H200:2018.4MI300X:956.8 | H200:1085.1MI300X:355.0 |
| Cost ($/M tok) | H200:$0.108MI300X:$0.148 | H200:$0.195MI300X:$0.320 | H200:$0.365MI300X:$0.872 |
| tok/s/MW | H200:2101076MI300X:1145772 | H200:1166719MI300X:534550 | H200:627235MI300X:198311 |
| Concurrency | H200:~64MI300X:~23 | H200:~62MI300X:~7 | H200:~24MI300X:~8 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.