MiniMax M2.5/M2.7 — GB300 NVL72 vs H200
Head-to-head AI inference benchmark comparison of GB300 NVL72 (NVIDIA Blackwell) and H200 (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.
Throughput at 49 tok/s/user on MiniMax M2.5/M2.7: GB300 NVL72 hits 4954 tok/s/GPU, H200 hits 1240. Per-million costs land at $0.15 and $0.32 respectively. GB300 NVL72 is 119% cheaper per token; GB300 NVL72 delivers 300% more tok/s/GPU.
GB300 NVL72 / H200 on MiniMax M2.5/M2.7 at 74 tok/s/user: 2117 / 516 tok/s/GPU, $0.35 / $0.77 per million tokens. GB300 NVL72 is 117% cheaper per token; GB300 NVL72 delivers 310% more tok/s/GPU.
Toward the upper edge of the 25–122 tok/s/user interactivity band, at 98 tok/s/user on MiniMax M2.5/M2.7: GB300 NVL72 runs 901 tok/s/GPU at $0.84/M tokens, H200 runs 375 at $1.05/M. GB300 NVL72 is 24% cheaper per token; GB300 NVL72 delivers 140% more tok/s/GPU. (Numbers reflect the default 1k/1k · fp8 selection for this URL — table and chart below update if you change sequence, precision, or model in the controls.)
| Metric | Interactivity (tok/s/user) | Interactivity (tok/s/user) | Interactivity (tok/s/user) |
|---|---|---|---|
| Throughput (tok/s/gpu) | GB300 NVL72:4954.2H200:1239.7 | GB300 NVL72:2116.8H200:515.8 | GB300 NVL72:901.3H200:375.3 |
| Cost ($/M tok) | GB300 NVL72:$0.149H200:$0.325 | GB300 NVL72:$0.354H200:$0.767 | GB300 NVL72:$0.845H200:$1.045 |
| tok/s/MW | GB300 NVL72:2336885H200:904887 | GB300 NVL72:998497H200:376510 | GB300 NVL72:425139H200:273955 |
| Concurrency | GB300 NVL72:~512H200:~64 | GB300 NVL72:~128H200:~27 | GB300 NVL72:~32H200:~8 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.