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/chip at $0.05 per million tokens; H100 delivers 1891 tok/s/chip at $0.17. B200 is 240% cheaper per token; B200 delivers 404% more tok/s/chip at this point.
B200 posts 4753 tok/s/chip for $0.10 per million tokens at 66 tok/s/user on MiniMax M2.5/M2.7; H100 posts 1269 tok/s/chip for $0.26. B200 is 153% cheaper per token; B200 delivers 275% more tok/s/chip.
Throughput at 89 tok/s/user on MiniMax M2.5/M2.7: B200 hits 3180 tok/s/chip, H100 hits 806. Per-million costs land at $0.15 and $0.40 respectively. B200 is 166% cheaper per token; B200 delivers 295% more tok/s/chip. (Numbers reflect the default 8k/1k · fp8 selection for this URL — table and chart below update if you change sequence, precision, or model in the controls.)
| Metric | Interactivity (tok/s/user) | Interactivity (tok/s/user) | Interactivity (tok/s/user) |
|---|---|---|---|
| Throughput (tok/s/chip) | B200:9525.9H100:1891.3 | B200:4752.7H100:1268.8 | B200:3179.8H100:805.9 |
| Cost ($/M tok) | B200:$0.050H100:$0.172 | B200:$0.101H100:$0.256 | B200:$0.151H100:$0.402 |
| tok/s/MW | B200:5570725H100:1380510 | B200:2779362H100:926145 | B200:1859520H100:588262 |
| Concurrency | B200:~512H100:~39 | B200:~21H100:~18 | B200:~20H100:~9 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.