All model and GPU pairings
Kimi K3 2.8TNVIDIA Blackwell

Running Kimi K3 on B300

Quick answer

Kimi K3 sustains 6,083 tokens/s per GPU on B300 at 50 tokens/s per user, which works out to $0.10 per million tokens at hyperscaler pricing, served by vLLM. Fastest measured TTFT: 0.6 ms; fastest TPOT: 0.0 ms (each the best across all configs, not one run).

Benchmarked configs

15

Serving engines

vLLM

Precisions

fp4

Run dates

2026-08-112026-08-16

Throughput at every interactivity target

Serving is a trade-off: push more concurrent users through a GPU and each user's tokens arrive slower. The ladder below reads the measured frontier at each per-user speed target on the AgentX agentic coding workload, using the best engine and precision at that point.

Per-user targetTokens/s per GPU$ / 1M tokensEnginePrecision
30 tok/s7,855$0.080vLLMfp4
50 tok/s6,083$0.10vLLMfp4
75 tok/s4,650$0.14vLLMfp4
100 tok/s4,051$0.15vLLMfp4
150 tok/s2,075$0.30vLLMfp4
200 tok/s2,027$0.31vLLMfp4

What serving actually costs

Converting the 50 tokens/s per user operating point to $ per million total tokens across rental pricing tiers from the SemiAnalysis AI Cloud TCO model.

Pricing tier$ / GPU / hr$ / 1M tokens
Hyperscaler$2.26$0.10
Neocloud$2.52$0.12
Retail$3.00$0.14

Frequently asked questions

How fast is Kimi K3 on B300?
At an interactivity target of 50 tokens/s per user on the AgentX agentic coding workload, B300 sustains 6,083 tokens/s per GPU serving Kimi K3 with vLLM in FP4. Peak measured throughput across all configs is 12,566 tokens/s per GPU.
How much does it cost to serve Kimi K3 on B300?
$0.10 per million total tokens at hyperscaler $/GPU/hr pricing, at 50 tokens/s per user. Neocloud and retail rental tiers are tabulated above; slower interactivity targets lower the cost further.
Which serving engines run Kimi K3 on B300?
The runs behind this page used vLLM in FP4. Engines are rebuilt and re-benchmarked continuously, so the best config can change between visits.
How are these Kimi K3 numbers measured?
Every number is measured on real B300 hardware by the InferenceX fleet, sweeping concurrency on the AgentX agentic coding workload to trace the throughput-versus-interactivity frontier; the newest run landed on 2026-08-16. The same derivation powers the InferenceX overview leaderboard.

Explore the data