gpt-oss 120B — B200 vs H200
Head-to-head AI inference benchmark comparison of B200 (NVIDIA Blackwell) and H200 (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.
B200 / H200 on gpt-oss 120B at 112 tok/s/user: 17454 / 2983 tok/s/chip, $0.03 / $0.11 per million tokens. B200 is 318% cheaper per token; B200 delivers 485% more tok/s/chip.
Around the middle of the 59–270 tok/s/user interactivity band, at 164 tok/s/user on gpt-oss 120B: B200 runs 9401 tok/s/chip at $0.05/M tokens, H200 runs 1607 at $0.21/M. B200 is 314% cheaper per token; B200 delivers 485% more tok/s/chip.
Setting 217 tok/s/user as the target on gpt-oss 120B, B200 produces 5671 tok/s/chip ($0.09 per million tokens) and H200 produces 797 ($0.43). B200 is 400% cheaper per token; B200 delivers 611% more tok/s/chip. (Numbers reflect the default 1k/1k · fp4 selection for this URL — table and chart below update if you change sequence, precision, or model in the controls.)
| Metric | Interactivity (tok/s/user) | Interactivity (tok/s/user) | Interactivity (tok/s/user) |
|---|---|---|---|
| Throughput (tok/s/chip) | B200:17453.5H200:2982.7 | B200:9400.5H200:1607.1 | B200:5670.6H200:797.4 |
| Cost ($/M tok) | B200:$0.027H200:$0.114 | B200:$0.051H200:$0.210 | B200:$0.085H200:$0.427 |
| tok/s/MW | B200:10206748H200:2177150 | B200:5497375H200:1173057 | B200:3316145H200:582040 |
| Concurrency | B200:~177H200:~64 | B200:~64H200:~45 | B200:~61H200:~7 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.