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Highest Output-Speed Gemini 2.5 Pro Inference Providers

Ranks providers by their recent typical output speed in tokens per second. Providers without enough recent data remain visible after ranked rows.

Google Vertex currently ranks first at 108.0 tok/s via google-vertex/us.

Provider options:
8
Ranked:
4
Metric:
Output speed

Highest output speed endpoint ranking

Highest Output-Speed Gemini 2.5 Pro Inference Providers
RankProvider / routeOutput speedSpeed measurementsEndpoint details
#1Provider / route
Google Vertexgoogle-vertex/us
Output speed108.0 tok/sSpeed measurements
500-token response
9.62 s
Response starts
4.99 s
Output speed
108.0 tok/s
Endpoint details
Input price
$1.25 / 1M
Output price
$10 / 1M
Uptime (30 min)
Insufficient recent data
Context
1M
#2Provider / route
Google Vertexgoogle-vertex/eu
Output speed99.0 tok/sSpeed measurements
500-token response
8.17 s
Response starts
3.12 s
Output speed
99.0 tok/s
Endpoint details
Input price
$1.25 / 1M
Output price
$10 / 1M
Uptime (30 min)
89.40%
Context
1M
#3Provider / route
Google AI Studiogoogle-ai-studio
Output speed98.0 tok/sSpeed measurements
500-token response
7.82 s
Response starts
2.71 s
Output speed
98.0 tok/s
Endpoint details
Input price
$1.25 / 1M
Output price
$10 / 1M
Uptime (30 min)
99.82%
Context
1M
#4Provider / route
Google Vertexgoogle-vertex/global
Output speed90.0 tok/sSpeed measurements
500-token response
7.80 s
Response starts
2.24 s
Output speed
90.0 tok/s
Endpoint details
Input price
$1.25 / 1M
Output price
$10 / 1M
Uptime (30 min)
98.89%
Context
1M
Provider / route
Google Vertexgoogle-vertex/global/flex
Output speedInsufficient recent dataSpeed measurements
500-token response
Insufficient recent data
Response starts
Insufficient recent data
Output speed
Insufficient recent data
Endpoint details
Input price
$0.625 / 1M
Output price
$5 / 1M
Uptime (30 min)
98.89%
Context
1M
Provider / route
Google Vertexgoogle-vertex/global/priority
Output speedInsufficient recent dataSpeed measurements
500-token response
Insufficient recent data
Response starts
Insufficient recent data
Output speed
Insufficient recent data
Endpoint details
Input price
$2.25 / 1M
Output price
$18 / 1M
Uptime (30 min)
98.89%
Context
1M
Provider / route
Google AI Studiogoogle-ai-studio/flex
Output speedInsufficient recent dataSpeed measurements
500-token response
Insufficient recent data
Response starts
Insufficient recent data
Output speed
Insufficient recent data
Endpoint details
Input price
$0.625 / 1M
Output price
$5 / 1M
Uptime (30 min)
99.82%
Context
1M
Provider / route
Google AI Studiogoogle-ai-studio/priority
Output speedInsufficient recent dataSpeed measurements
500-token response
Insufficient recent data
Response starts
Insufficient recent data
Output speed
Insufficient recent data
Endpoint details
Input price
$2.25 / 1M
Output price
$18 / 1M
Uptime (30 min)
99.82%
Context
1M

Endpoint data fetched .

Gemini 2.5 Pro endpoint guide

How to interpret the Highest Output-Speed Gemini 2.5 Pro Inference Providers

4 of 8 Gemini 2.5 Pro endpoints currently have the published data required for this ranking. Google Vertex leads at 108.0 tok/s via google-vertex/us. The table keeps unranked routes visible so missing measurements do not look like missing provider availability.

How generation throughput is ranked

The output-speed ranking compares recent median generated tokens per second. It favors routes that complete long generations quickly, while first-token latency remains a separate measure of how responsive the endpoint feels at the beginning.

Compare Google Vertex with the next option

Google Vertex currently ranks second at 99.0 tok/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

Gemini 2.5 Pro has 8 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.