Qwen 3.8 Flash Next 176B-A6B β B200 vs H100 Performance per Dollar
Cost per million tokens of B200 (NVIDIA Blackwell) versus H100 (NVIDIA Hopper) on Qwen 3.8 Flash Next 176B-A6B. Large-hyperscaler-volume ownership TCO normalized by total tokens β 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 β 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 β
At 46 tok/s/user on Qwen 3.8 Flash Next 176B-A6B, H100 comes in at $0.07 per million tokens. B200 hasn't been benchmarked at this operating point.
Only H100 has cost data at 77 tok/s/user on Qwen 3.8 Flash Next 176B-A6B β $0.07 per million tokens. B200 is unmeasured at this target.
H100 costs $0.07 per million tokens at 108 tok/s/user on Qwen 3.8 Flash Next 176B-A6B; we have no B200 benchmark data at this exact target. (Numbers reflect the default agentic-traces Β· fp8 selection for this URL β table and chart below update if you change sequence, precision, or model in the controls.)
Chip pricing (owning hyperscaler): B200 $1.73/chip/hr Β· H100 $1.17/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 | B200:βH100:$0.065 | B200:βH100:$0.066 | B200:βH100:$0.066 |
| Concurrency | B200:βH100:~11 | B200:βH100:~10 | B200:βH100:~9 |
Inference Performance
Agentic inference metrics from the AgentX scenario and fixed-sequence inference metrics across models, hardware configurations, and serving parameters.