MiniMax M3 428B — B200 vs B300
Head-to-head AI inference benchmark comparison of B200 (NVIDIA Blackwell) and B300 (NVIDIA Blackwell) on MiniMax M3 428B. 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 posts 2055 tok/s/GPU for $0.26 per million tokens at 111 tok/s/user on MiniMax M3 428B; B300 posts 2505 tok/s/GPU for $0.26. B300 is 2% cheaper per token; B300 delivers 22% more tok/s/GPU.
Throughput at 207 tok/s/user on MiniMax M3 428B: B200 hits 796 tok/s/GPU, B300 hits 1012. Per-million costs land at $0.68 and $0.64 respectively. B300 is 7% cheaper per token; B300 delivers 27% more tok/s/GPU.
B200 / B300 on MiniMax M3 428B at 304 tok/s/user: 285 / 532 tok/s/GPU, $1.90 / $1.22 per million tokens. B300 is 56% cheaper per token; B300 delivers 87% more tok/s/GPU. (Numbers reflect the default 1k/1k · fp4 selection for this URL — table and chart below update if you change sequence, precision, or model in the controls.)
| Metric | Interactivity (tok/s/user) | Interactivity (tok/s/user) | Interactivity (tok/s/user) |
|---|---|---|---|
| Throughput (tok/s/gpu) | B200:2055.4B300:2504.9 | B200:796.4B300:1012.2 | B200:284.9B300:532.4 |
| Cost ($/M tok) | B200:$0.264B300:$0.258 | B200:$0.681B300:$0.638 | B200:$1.901B300:$1.221 |
| tok/s/MW | B200:1201960B300:1318361 | B200:465726B300:532713 | B200:166637B300:280194 |
| Concurrency | B200:~58B300:~104 | B200:~8B300:~11 | B200:~1B300:~2 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.