MiniMax M2.5/M2.7 · GPU comparison

MiniMax M2.5/M2.7 — GB200 NVL72 vs H100

Head-to-head AI inference benchmark comparison of GB200 NVL72 (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 59 tok/s/user interactivity on MiniMax M2.5/M2.7, GB200 NVL72 delivers 3310 tok/s/GPU at $0.18 per million tokens; H100 delivers 614 tok/s/GPU at $0.58. GB200 NVL72 is 215% cheaper per token; GB200 NVL72 delivers 439% more tok/s/GPU at this point.

GB200 NVL72 posts 1320 tok/s/GPU for $0.48 per million tokens at 78 tok/s/user on MiniMax M2.5/M2.7; H100 posts 378 tok/s/GPU for $0.94. GB200 NVL72 is 95% cheaper per token; GB200 NVL72 delivers 249% more tok/s/GPU.

Throughput at 98 tok/s/user on MiniMax M2.5/M2.7: GB200 NVL72 hits 761 tok/s/GPU, H100 hits 199. Per-million costs land at $0.82 and $1.82 respectively. GB200 NVL72 is 121% cheaper per token; GB200 NVL72 delivers 282% 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.)

View performance-per-dollar view →

Interpolated from real benchmark data. Edit target interactivity values below to compare at different operating points.
Metric
Interactivity (tok/s/user)
Interactivity (tok/s/user)
Interactivity (tok/s/user)
Throughput (tok/s/gpu)
GB200 NVL72:3310.2H100:614.1
GB200 NVL72:1319.9H100:378.2
GB200 NVL72:760.8H100:199.2
Cost ($/M tok)
GB200 NVL72:$0.184H100:$0.580
GB200 NVL72:$0.480H100:$0.937
GB200 NVL72:$0.825H100:$1.824
tok/s/MW
GB200 NVL72:1770167H100:448245
GB200 NVL72:705818H100:276080
GB200 NVL72:406865H100:145425
Concurrency
GB200 NVL72:~340H100:~42
GB200 NVL72:~64H100:~12
GB200 NVL72:~32H100:~8

Inference Performance

Inference performance metrics across different models, hardware configurations, and serving parameters.

Vendor:
Aggregation:
Spec Decoding: