Qwen 3.5 397B-A17B — MI300X vs MI355X Performance per Dollar
Cost per million tokens of MI300X (AMD CDNA 3) 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.
Push Qwen 3.5 397B-A17B to 43 tok/s/user and MI300X lands at $0.76 per million tokens against MI355X's $0.15 — MI355X pulls ahead by 410%.
MI300X: $1.38 per million tokens. MI355X: $0.17. Both at 53 tok/s/user on Qwen 3.5 397B-A17B, with MI355X 720% cheaper.
Toward the upper edge of the 34–71 tok/s/user interactivity band — at 62 tok/s/user — MI300X runs $2.13 per million tokens on Qwen 3.5 397B-A17B while MI355X runs $0.19. MI355X is the cheaper choice by 1026%. (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.)
Chip pricing (owning hyperscaler): MI300X $0.95/chip/hr · MI355X $1.50/chip/hr. Source: SemiAnalysis Market July 2026 Pricing Surveys & AI Cloud TCO Model.
| Metric | Interactivity (tok/s/user) | Interactivity (tok/s/user) | Interactivity (tok/s/user) |
|---|---|---|---|
| Dollar per Million Tokens | MI300X:$0.758MI355X:$0.148 | MI300X:$1.385MI355X:$0.169 | MI300X:$2.135MI355X:$0.190 |
| Concurrency | MI300X:~34MI355X:~132 | MI300X:~15MI355X:~90 | MI300X:~8MI355X:~71 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.