DeepSeek V4 Pro 1.6T — B300 vs MI355X
Head-to-head AI inference benchmark comparison of B300 (NVIDIA Blackwell) and MI355X (AMD CDNA 4) on DeepSeek V4 Pro 1.6T. 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.
B300 posts 9689 tok/s/GPU for $0.07 per million tokens at 35 tok/s/user on DeepSeek V4 Pro 1.6T; MI355X posts 4286 tok/s/GPU for $0.10. B300 is 43% cheaper per token; B300 delivers 126% more tok/s/GPU.
Throughput at 67 tok/s/user on DeepSeek V4 Pro 1.6T: B300 hits 6939 tok/s/GPU, MI355X hits 1782. Per-million costs land at $0.09 and $0.23 respectively. B300 is 145% cheaper per token; B300 delivers 289% more tok/s/GPU.
B300 / MI355X on DeepSeek V4 Pro 1.6T at 99 tok/s/user: 2468 / 853 tok/s/GPU, $0.26 / $0.48 per million tokens. B300 is 84% cheaper per token; B300 delivers 189% more tok/s/GPU. (Numbers reflect the default 8k/1k · fp4 selection for this URL — table and chart below update if you change sequence, precision, or model in the controls.)
| Metric | Interactivity (tok/s/user) | Interactivity (tok/s/user) | Interactivity (tok/s/user) |
|---|---|---|---|
| Throughput (tok/s/gpu) | B300:9688.9MI355X:4286.3 | B300:6938.6MI355X:1781.8 | B300:2468.0MI355X:852.5 |
| Cost ($/M tok) | B300:$0.067MI355X:$0.096 | B300:$0.094MI355X:$0.230 | B300:$0.262MI355X:$0.482 |
| tok/s/MW | B300:5099429MI355X:2050877 | B300:3651906MI355X:852545 | B300:1298957MI355X:407903 |
| Concurrency | B300:~3071MI355X:~512 | B300:~427MI355X:~34 | B300:~231MI355X:~8 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.