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Fastest Kimi K2 Thinking Inference Providers

Ranks providers by estimated time to return 500 tokens, combining the wait for the first token with output speed.

Google Vertex currently ranks first at 4.00 s via google-vertex.

Provider options:
2
Ranked:
2
Metric:
Estimated response time

Fastest response endpoint ranking

Fastest Kimi K2 Thinking Inference Providers
RankProvider / routeEstimated response timeSpeed measurementsEndpoint details
#1Provider / route
Google Vertexgoogle-vertex
Estimated response time4.00 sSpeed measurements
500-token response
4.00 s
Response starts
0.42 s
Output speed
139.5 tok/s
Endpoint details
Input price
$0.6 / 1M tokens
Output price
$2.5 / 1M tokens
Uptime (30 min)
99.68%
Context
262.1K
#2Provider / route
NovitaAInovita/bf16
Estimated response time15.70 sSpeed measurements
500-token response
15.70 s
Response starts
1.42 s
Output speed
35.0 tok/s
Endpoint details
Input price
$0.6 / 1M tokens
Output price
$2.5 / 1M tokens
Uptime (30 min)
93.63%
Context
262.1K

Endpoint data fetched .

Kimi K2 Thinking endpoint guide

How to interpret the Fastest Kimi K2 Thinking Inference Providers

2 of 2 Kimi K2 Thinking endpoints currently have the published data required for this ranking. Google Vertex leads at 4.00 s via google-vertex. The table keeps unranked routes visible so missing measurements do not look like missing provider availability.

How complete response time is ranked

The fastest ranking estimates a 500-token answer by adding the recent median first-token wait to 500 divided by median output throughput. It represents an example complete response, not a guarantee for every prompt or request size.

Compare Google Vertex with the next option

NovitaAI currently ranks second at 15.70 s. Compare that gap with input and output price, response-start time, output speed, 30-minute uptime, context length, and the exact route before deciding whether first place is meaningful for your workload.

Use the route, not only the provider name

Kimi K2 Thinking has 2 published provider options, and performance data is matched to each exact OpenRouter routing tag. Different quantization, context, regional deployment, or provider configuration can change price and behavior even when the underlying model name is identical.