DeepSeek V4.1 Flash 552B · Performance per Dollar

DeepSeek V4.1 Flash 552B — B300 vs GB300 NVL72 Performance per Dollar

Cost per million tokens of B300 (NVIDIA Blackwell) versus GB300 NVL72 (NVIDIA Blackwell) on DeepSeek V4.1 Flash 552B. Large-hyperscaler-volume ownership TCO normalized by total 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.

AgentX replays real coding-agent sessions rather than fixed-length prompts, so context grows turn over turn and most of each request is served from cache instead of being recomputed. That turns the comparison into a systems question: KV transfer between nodes, prefix-aware routing, and cache capacity all move the curve alongside raw chip throughput. Fixed-sequence workloads stay the clean baseline for kernel and silicon performance, so the two scenarios answer different questions about the same hardware. Learn more about AgentX

B300 edges GB300 NVL72 at 89 tok/s/user on DeepSeek V4.1 Flash 552B — $0.01 per million tokens versus $0.06, a 532% cost-per-token gap.

Push DeepSeek V4.1 Flash 552B to 175 tok/s/user and B300 lands at $0.02 per million tokens against GB300 NVL72's $0.06 — B300 pulls ahead by 166%.

B300: $0.04 per million tokens. GB300 NVL72: $0.06. Both at 261 tok/s/user on DeepSeek V4.1 Flash 552B, with B300 36% cheaper. (Numbers reflect the default agentic-traces · fp4 selection for this URL — table and chart below update if you change sequence, precision, or model in the controls.)

Chip pricing (owning hyperscaler): B300 $2.26/chip/hr · GB300 NVL72 $2.31/chip/hr. Source: SemiAnalysis Market July 2026 Pricing Surveys & AI Cloud TCO Model.

View full latency + throughput comparison →

DeepSeek V4.1 Flash 552B: 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:$0.009GB300 NVL72:$0.060
B300:$0.022GB300 NVL72:$0.060
B300:$0.044GB300 NVL72:$0.060
Concurrency
B300:~39GB300 NVL72:~16
B300:~16GB300 NVL72:~16
B300:~7GB300 NVL72:~16

Inference Performance

Agentic inference metrics from the AgentX scenario and fixed-sequence inference metrics across models, hardware configurations, and serving parameters.

Benchmark Config

No data available

No measurements to plot for this selection. Review the benchmark controls above or adjust quick filters.