Model detail
gpt-5.5
GPT-5.5 is OpenAI’s frontier model designed for complex professional workloads, building on GPT-5.4 with stronger reasoning, higher reliability, and improved token efficiency on hard tasks. It features a 1M+ token context window (922K input, 128K output) with support for text and image inputs, enabling large-scale reasoning, coding, and multimodal workflows within a single system.
Model specs
- Context length
- 1.05M
- Max output
- 128K
- I/O modalities
- Text / Image
- Released
- 2026-04
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API endpoints
One MixRoute gateway, OpenAI-compatible
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OpenAI-compatible
/v1/chat/completionsPOST
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Tiered pricing
Unit: /1M Tokens
| Tier | Input /1M Tokens | Output /1M Tokens | Cache read /1M Tokens |
|---|---|---|---|
| standard Length ≤ 272K | $5.0000 | $30.0000 | $0.5000 |
| long_context Length > 272K | $10.0000 | $45.0000 | $1.0000 |
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Selection summary
Quickly judge whether it fits your workload
What is this model good for?
Start with the documented use cases for gpt-5.5
GPT-5.5 is OpenAI’s frontier model designed for complex professional workloads, building on GPT-5.4 with stronger reasoning, higher reliability, and improved token efficiency on hard tasks. It features a 1M+ token context window (922K input, 128K output) with support for text and image inputs, enabling large-scale reasoning, coding, and multimodal workflows within a single system.
What should you check before using it?
Validate limits, pricing, and a representative workload
Review the current model limits and pricing record before production use.
How do you call it through MixRoute?
Use the documented endpoint and exact model ID
The model record lists OpenAI-compatible access via POST /v1/chat/completions with model ID gpt-5.5.
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Token cost estimator
Live estimate from this page's pricing, not an actual bill
Share of the same prefix read repeatedly, up to 100%
09
FAQ
GPT-5.5 is OpenAI’s frontier model designed for complex professional workloads, building on GPT-5.4 with stronger reasoning, higher reliability, and improved token efficiency on hard tasks. It features a 1M+ token context window (922K input, 128K output) with support for text and image inputs, enabling large-scale reasoning, coding, and multimodal workflows within a single system.
One endpoint, a testable decision
Test this model and alternate routes with the same request format
Start from a real workload, then let quality, total cost, and failure conditions decide whether to send production traffic.