MiniMax M2.5/M2.7 · Performance per Dollar

MiniMax M2.5/M2.7 — GB300 NVL72 vs MI355X Performance per Dollar

Cost per million tokens of GB300 NVL72 (NVIDIA Blackwell) versus MI355X (AMD CDNA 4) on MiniMax M2.5/M2.7. 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 MiniMax M2.5/M2.7 to 47 tok/s/user and GB300 NVL72 lands at $0.14 per million tokens against MI355X's $0.12 — MI355X pulls ahead by 17%.

GB300 NVL72: $0.31 per million tokens. MI355X: $0.38. Both at 71 tok/s/user on MiniMax M2.5/M2.7, with GB300 NVL72 22% cheaper.

Toward the upper edge of the 24–119 tok/s/user interactivity band — at 95 tok/s/user — GB300 NVL72 runs $0.82 per million tokens on MiniMax M2.5/M2.7 while MI355X runs $0.73. MI355X is the cheaper choice by 13%. (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.

View full latency + throughput comparison →

MiniMax M2.5/M2.7: GB300 NVL72 versus MI355X cost per million tokens at matched interactivity levels
GB300 NVL72 versus MI355X cost per million tokens for this comparison's canonical default workload. Lower cost indicates better performance per dollar.
Interpolated from real benchmark data. Edit target interactivity values below to compare at different operating points.
Metric
Interactivity (tok/s/user)
Interactivity (tok/s/user)
Interactivity (tok/s/user)
Dollar per Million Tokens
GB300 NVL72:$0.136MI355X:$0.117
GB300 NVL72:$0.313MI355X:$0.383
GB300 NVL72:$0.823MI355X:$0.732
Concurrency
GB300 NVL72:~540MI355X:~256
GB300 NVL72:~128MI355X:~32
GB300 NVL72:~32MI355X:~6

Inference Performance

Inference performance metrics across different models, hardware configurations, and serving parameters.