MiniMax M3 428B · Performance per Dollar

MiniMax M3 428B — B300 vs GB300 NVL72 Performance per Dollar

Cost per million tokens of B300 (NVIDIA Blackwell) versus GB300 NVL72 (NVIDIA Blackwell) on MiniMax M3 428B. 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.

B300: $0.09 per million tokens. GB300 NVL72: $0.22. Both at 63 tok/s/user on MiniMax M3 428B, with B300 143% cheaper.

Around the middle of the 22–190 tok/s/user interactivity band — at 106 tok/s/user — B300 runs $0.15 per million tokens on MiniMax M3 428B while GB300 NVL72 runs $0.37. B300 is the cheaper choice by 147%.

On MiniMax M3 428B at 148 tok/s/user, the per-million math comes out to $0.20 for B300 and $0.90 for GB300 NVL72; B300 delivers 348% more output per dollar. (Numbers reflect the default 8k/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): B300 $2.34/GPU/hr · GB300 NVL72 $2.65/GPU/hr. Source: SemiAnalysis Market August 2025 Pricing Surveys & AI Cloud TCO Model.

View full latency + throughput comparison →

MiniMax M3 428B: B300 versus GB300 NVL72 cost per million tokens at matched interactivity levels
B300 versus GB300 NVL72 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
B300:$0.092GB300 NVL72:$0.224
B300:$0.148GB300 NVL72:$0.365
B300:$0.202GB300 NVL72:$0.902
Concurrency
B300:~54GB300 NVL72:~128
B300:~21GB300 NVL72:~44
B300:~11GB300 NVL72:~14

Inference Performance

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

Vendor:
Aggregation:
Spec Decoding: