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GPT-5 Nano API pricing & cost
Current token rates, context limits, workload examples and unit-economics shortcuts for GPT-5 Nano.
Input / 1M tokens$0.05
Output / 1M tokens$0.4
Cached input / 1M$0.005
Context window400K tokens
Pricing page fallback verified September 3, 2026; client checks TokenCOGS live registry on load.
Quick cost examples
Change the token assumptions →
What the token rates mean in dollars
Example workload: 2,000 input tokens + 500 output tokens per request, standard text-token pricing.
| Volume | Estimated API cost | Approx. / request |
|---|---|---|
| 1,000 requests | $0.3 | $0.0003 |
| 100,000 requests | $30.00 | $0.0003 |
| 1,000,000 requests | $300.00 | $0.0003 |
Positioning
Where GPT-5 Nano sits on price
GPT-5 Nano sits toward the lowest input-token rate in the current TokenCOGS registry for this provider. Price alone is not a quality ranking, but this position is useful when you are screening models for unit-economics fit before benchmarking latency and quality.
Cost comparison is not a quality, latency or reliability ranking. Benchmark the task you actually need to run.
Compare all OpenAI models →Cost considerations
What can move the invoice
- Cached input is tracked at $0.005 per 1M tokens, which can materially change repeated-system-prompt or repeated-context workloads.
Current deals & credits
Ways this provider may reduce spend
Use your workload
Turn pricing into unit economics
FAQ
GPT-5 Nano pricing questions
How much does GPT-5 Nano cost per 1M tokens?
The current TokenCOGS snapshot lists GPT-5 Nano at $0.05 per 1M input tokens and $0.4 per 1M output tokens. Live registry data can update these values when the provider changes pricing.
What would 1,000 GPT-5 Nano requests cost?
At 2,000 input tokens and 500 output tokens per request, 1,000 requests are approximately $0.3 before provider-specific extras. Change the workload in the linked calculator for your own usage pattern.
Is GPT-5 Nano the cheapest OpenAI model?
GPT-5 Nano sits toward the lowest input-token rate in the current TokenCOGS registry for this provider. Price alone is not a quality ranking, but this position is useful when you are screening models for unit-economics fit before benchmarking latency and quality.