MiniMax M2.5/M2.7 — B200 vs H100
Head-to-head AI inference benchmark comparison of B200 (NVIDIA Blackwell) and H100 (NVIDIA Hopper) on MiniMax M2.5/M2.7. 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 44 tok/s/user interactivity on MiniMax M2.5/M2.7, B200 delivers 9526 tok/s/GPU at $0.06 per million tokens; H100 delivers 1869 tok/s/GPU at $0.19. B200 is 238% cheaper per token; B200 delivers 410% more tok/s/GPU at this point.
B200 posts 4753 tok/s/GPU for $0.11 per million tokens at 66 tok/s/user on MiniMax M2.5/M2.7; H100 posts 1251 tok/s/GPU for $0.29. B200 is 155% cheaper per token; B200 delivers 280% more tok/s/GPU.
Throughput at 89 tok/s/user on MiniMax M2.5/M2.7: B200 hits 3180 tok/s/GPU, H100 hits 831. Per-million costs land at $0.17 and $0.44 respectively. B200 is 158% cheaper per token; B200 delivers 283% more tok/s/GPU. (Numbers reflect the default 8k/1k · fp8 selection for this URL — table and chart below update if you change sequence, precision, or model in the controls.)
| Metric | Interactivity (tok/s/user) | Interactivity (tok/s/user) | Interactivity (tok/s/user) |
|---|---|---|---|
| Throughput (tok/s/gpu) | B200:9525.9H100:1868.7 | B200:4752.7H100:1251.2 | B200:3179.8H100:830.9 |
| Cost ($/M tok) | B200:$0.057H100:$0.192 | B200:$0.114H100:$0.291 | B200:$0.170H100:$0.439 |
| tok/s/MW | B200:4389834H100:1080187 | B200:2190189H100:723258 | B200:1465336H100:480286 |
| Concurrency | B200:~512H100:~19 | B200:~21H100:~16 | B200:~20H100:~4 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.