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Most Reliable GPT-5.5 Pro Inference Providers

Ranks providers by the uptime OpenRouter measured during the latest 30-minute window.

OpenAI currently ranks first at 100.00% via openai.

Provider options:
2
Ranked:
2
Metric:
Uptime (last 30 min)

Highest uptime endpoint ranking

Most Reliable GPT-5.5 Pro Inference Providers
RankProvider / routeUptime (last 30 min)Speed measurementsEndpoint details
#1Provider / route
OpenAIopenai
Uptime (last 30 min)100.00%Speed measurements
500-token response
78.13 s
Response starts
25.50 s
Output speed
9.5 tok/s
Endpoint details
Input price
$30 / 1M tokens
Output price
$180 / 1M tokens
Uptime (30 min)
100.00%
Context
1.1M
#2Provider / route
OpenAIopenai/flex
Uptime (last 30 min)100.00%Speed measurements
500-token response
Insufficient recent data
Response starts
Insufficient recent data
Output speed
Insufficient recent data
Endpoint details
Input price
$15 / 1M tokens
Output price
$90 / 1M tokens
Uptime (30 min)
100.00%
Context
1.1M

Endpoint data fetched .

GPT-5.5 Pro endpoint guide

How to interpret the Most Reliable GPT-5.5 Pro Inference Providers

2 of 2 GPT-5.5 Pro endpoints currently have the published data required for this ranking. OpenAI leads at 100.00% via openai. The table keeps unranked routes visible so missing measurements do not look like missing provider availability.

How recent uptime is ranked

The reliability ranking uses the published 30-minute endpoint uptime measurement. This short operational window can reveal current instability, but it is not a service-level agreement or a substitute for longer-term availability monitoring.

Compare OpenAI with the next option

OpenAI currently ranks second at 100.00%. 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

GPT-5.5 Pro 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.