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 44–161 tok/s/user interactivity band — at 73 tok/s/user — GB300 NVL72 runs $0.09 per million tokens on Qwen 3.5 397B-A17B while MI355X runs $0.12. GB300 NVL72 is the cheaper choice by 41%.
On Qwen 3.5 397B-A17B at 103 tok/s/user, the per-million math comes out to $0.16 for GB300 NVL72 and $0.15 for MI355X; MI355X delivers 5% more output per dollar.
At 132 tok/s/user on Qwen 3.5 397B-A17B, GB300 NVL72 costs $0.24 per million tokens; MI355X costs $0.20. MI355X is 23% more cost-efficient at this operating point. (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): 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:$0.086MI355X:$0.121 | GB300 NVL72:$0.157MI355X:$0.150 | GB300 NVL72:$0.244MI355X:$0.198 |
| Concurrency | GB300 NVL72:~225MI355X:~14 | GB300 NVL72:~45MI355X:~6 | GB300 NVL72:~23MI355X:~4 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.