Model detail
gpt-5-nano-2025-08-07
GPT-5-Nano is the smallest and fastest variant in the GPT-5 system, optimized for developer tools, rapid interactions, and ultra-low latency environments. While limited in reasoning depth compared to its larger counterparts, it retains key instruction-following and safety features. It is the successor to GPT-4.1-nano and offers a lightweight option for cost-sensitive or real-time applications.
Model specs
- Context length
- 400K
- Max output
- 128K
- I/O modalities
- Text / Image
- Released
- 2025-08
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API endpoints
One MixRoute gateway, OpenAI-compatible
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OpenAI-compatible
/v1/chat/completionsPOST
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Pricing
Flat rate, unit: /1M Tokens
Input
$0.0500 /1M Tokens
Completion
$0.4000 /1M Tokens
Cache read
$0.0050 /1M Tokens
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Selection summary
Quickly judge whether it fits your workload
What is this model good for?
Ultra-fast developer tools and real-time interactions
Use GPT-5-Nano for developer tools, rapid interactions, and ultra-low latency environments. It retains key instruction-following and safety features while being the most cost-effective option in the GPT-5 series.
What should you check before using it?
Confirm accuracy for your task class
GPT-5-Nano has limited reasoning depth compared to larger models. Test your developer tools and rapid interaction tasks to confirm the accuracy meets your requirements.
Why use it through MixRoute?
Use the OpenAI-compatible endpoint with stable model ID
Use the confirmed compatible endpoint with model ID gpt-5-nano through MixRoute, then run the same integration tests used for the current client.
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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-Nano is the smallest and fastest variant in the GPT-5 series, optimized for developer tools, rapid interactions, and ultra-low latency environments. It retains key instruction-following and safety features and is the successor to GPT-4.1-nano.
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.