gpt-oss 120B — GB200 NVL72 vs MI325X Performance per Dollar
Cost per million tokens of GB200 NVL72 (NVIDIA Blackwell) versus MI325X (AMD CDNA 3) on gpt-oss 120B. 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 51 tok/s/user on gpt-oss 120B, GB200 NVL72 costs $0.01 per million tokens; MI325X costs $0.11. GB200 NVL72 is 1003% more cost-efficient at this operating point.
GB200 NVL72 edges MI325X at 72 tok/s/user on gpt-oss 120B — $0.01 per million tokens versus $0.15, a 1258% cost-per-token gap.
Push gpt-oss 120B to 93 tok/s/user and GB200 NVL72 lands at $0.01 per million tokens against MI325X's $0.29 — GB200 NVL72 pulls ahead by 1915%. (Numbers reflect the default 1k/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): GB200 NVL72 $1.86/chip/hr · MI325X $1.10/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 | GB200 NVL72:$0.010MI325X:$0.113 | GB200 NVL72:$0.011MI325X:$0.154 | GB200 NVL72:$0.015MI325X:$0.292 |
| Concurrency | GB200 NVL72:~1559MI325X:~64 | GB200 NVL72:~1026MI325X:~60 | GB200 NVL72:~1225MI325X:~25 |
Inference Performance
Inference performance metrics across different models, hardware configurations, and serving parameters.