gpt-oss 120B — B200 vs H100
Head-to-head AI inference benchmark comparison of B200 (NVIDIA Blackwell) and H100 (NVIDIA Hopper) 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.
Throughput at 117 tok/s/user on gpt-oss 120B: B200 hits 16602 tok/s/chip, H100 hits 2622. Per-million costs land at $0.03 and $0.13 respectively. B200 is 335% cheaper per token; B200 delivers 533% more tok/s/chip.
B200 / H100 on gpt-oss 120B at 166 tok/s/user: 9191 / 1379 tok/s/chip, $0.05 / $0.24 per million tokens. B200 is 354% cheaper per token; B200 delivers 566% more tok/s/chip.
Toward the upper edge of the 67–266 tok/s/user interactivity band, at 216 tok/s/user on gpt-oss 120B: B200 runs 5730 tok/s/chip at $0.08/M tokens, H100 runs 740 at $0.44/M. B200 is 419% cheaper per token; B200 delivers 675% more tok/s/chip. (Numbers reflect the default 1k/1k · fp4 selection for this URL — table and chart below update if you change sequence, precision, or model in the controls.)
| Metric | Interactivity (tok/s/user) | Interactivity (tok/s/user) | Interactivity (tok/s/user) |
|---|---|---|---|
| Throughput (tok/s/chip) | B200:16601.5H100:2621.5 | B200:9191.4H100:1379.3 | B200:5730.2H100:739.7 |
| Cost ($/M tok) | B200:$0.029H100:$0.125 | B200:$0.052H100:$0.236 | B200:$0.084H100:$0.438 |
| tok/s/MW | B200:9708491H100:1913517 | B200:5375074H100:1006814 | B200:3350967H100:539935 |
| Concurrency | B200:~154H100:~64 | B200:~64H100:~17 | B200:~61H100:~8 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.