Qwen 3.5 397B-A17B — MI300X vs RTX PRO 6000 Performance per Dollar
Cost per million tokens of MI300X (AMD CDNA 3) versus RTX PRO 6000 (NVIDIA Blackwell) 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.
At 47 tok/s/user on Qwen 3.5 397B-A17B, RTX PRO 6000 comes in at $0.17 per million tokens. MI300X hasn't been benchmarked at this operating point.
Only RTX PRO 6000 has cost data at 82 tok/s/user on Qwen 3.5 397B-A17B — $0.23 per million tokens. MI300X is unmeasured at this target.
RTX PRO 6000 costs $0.38 per million tokens at 118 tok/s/user on Qwen 3.5 397B-A17B; we have no MI300X benchmark data at this exact target. (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.)
Chip pricing (owning hyperscaler): MI300X $0.95/chip/hr · RTX PRO 6000 $0.68/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:—RTX PRO 6000:$0.172 | MI300X:—RTX PRO 6000:$0.230 | MI300X:—RTX PRO 6000:$0.383 |
| Concurrency | MI300X:—RTX PRO 6000:~12 | MI300X:—RTX PRO 6000:~5 | MI300X:—RTX PRO 6000:~2 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.