Qwen 3.5 397B-A17B — GB300 NVL72 vs MI355X Performance per Dollar
Cost per million tokens of GB300 NVL72 (NVIDIA Blackwell) versus MI355X (AMD CDNA 4) on Qwen 3.5 397B-A17B. 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.
Near the low end of the 32–206 tok/s/user interactivity band — at 75 tok/s/user — GB300 NVL72 runs $0.68 per million tokens on Qwen 3.5 397B-A17B while MI355X runs $0.23. MI355X is the cheaper choice by 192%.
On Qwen 3.5 397B-A17B at 119 tok/s/user, the per-million math comes out to $1.65 for GB300 NVL72 and $0.39 for MI355X; MI355X delivers 325% more output per dollar.
At 163 tok/s/user on Qwen 3.5 397B-A17B, GB300 NVL72 costs $3.46 per million tokens; MI355X costs $0.64. MI355X is 438% more cost-efficient at this operating point. (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.)
GPU pricing (owning hyperscaler): GB300 NVL72 $2.65/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 | GB300 NVL72:$0.677MI355X:$0.232 | GB300 NVL72:$1.648MI355X:$0.388 | GB300 NVL72:$3.463MI355X:$0.644 |
| Concurrency | GB300 NVL72:~63MI355X:~48 | GB300 NVL72:~16MI355X:~18 | GB300 NVL72:~5MI355X:~8 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.