DeepSeek V4 Pro 1.6T — B300 vs MI355X Performance per Dollar
Cost per million tokens of B300 (NVIDIA Blackwell) versus MI355X (AMD CDNA 4) on DeepSeek V4 Pro 1.6T. Owning-hyperscaler TCO normalized by output tokens — performance per dollar across LLM workloads. Pick the more cost-efficient SKU at every target interactivity level. Use the chart controls below to switch sequences, precisions, and metrics — same interactions as the main inference chart.
Push DeepSeek V4 Pro 1.6T to 35 tok/s/user and B300 lands at $0.07 per million tokens against MI355X's $0.10 — B300 pulls ahead by 43%.
B300: $0.09 per million tokens. MI355X: $0.23. Both at 67 tok/s/user on DeepSeek V4 Pro 1.6T, with B300 145% cheaper.
Toward the upper edge of the 4–130 tok/s/user interactivity band — at 99 tok/s/user — B300 runs $0.26 per million tokens on DeepSeek V4 Pro 1.6T while MI355X runs $0.48. B300 is the cheaper choice by 84%. (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.)
GPU pricing (owning hyperscaler): B300 $2.34/GPU/hr · MI355X $1.48/GPU/hr. Source: SemiAnalysis Market August 2025 Pricing Surveys & AI Cloud TCO Model.
| Metric | Interactivity (tok/s/user) | Interactivity (tok/s/user) | Interactivity (tok/s/user) |
|---|---|---|---|
| Dollar per Million Tokens | B300:$0.067MI355X:$0.096 | B300:$0.094MI355X:$0.230 | B300:$0.262MI355X:$0.482 |
| Concurrency | B300:~3071MI355X:~512 | B300:~427MI355X:~34 | B300:~231MI355X:~8 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.