Kimi K3.1 Pro — B200 vs MI355X Performance per Dollar
Cost per million tokens of B200 (NVIDIA Blackwell) versus MI355X (AMD CDNA 4) on Kimi K3.1 Pro. 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 →
On Kimi K3.1 Pro at 41 tok/s/user, the per-million math comes out to $0.18 for B200 and $0.03 for MI355X; MI355X delivers 555% more total tokens per dollar.
At 55 tok/s/user on Kimi K3.1 Pro, B200 costs $0.26 per million tokens; MI355X costs $0.04. MI355X is 610% more cost-efficient at this operating point.
MI355X edges B200 at 69 tok/s/user on Kimi K3.1 Pro — $0.05 per million tokens versus $0.31, a 497% cost-per-token gap. (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): B200 $1.73/chip/hr · MI355X $1.50/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:$0.179MI355X:$0.027 | B200:$0.261MI355X:$0.037 | B200:$0.311MI355X:$0.052 |
| Concurrency | B200:~12MI355X:~29 | B200:~7MI355X:~20 | B200:~5MI355X:~13 |