How do you get a cache hit on gpt-5-nano?

To get a cache hit on gpt-5-nano, send requests with identical prompt prefixes. The cache is keyed by the beginning of your prompt; as long as the prefix matches a previous request, subsequent calls benefit from the lower cached rate. Keep system messages and initial context consistent across calls for best results.

Can you call GPT-5-Nano with the OpenAI SDK you already use?

Yes. GPT-5-Nano is served through an OpenAI-compatible endpoint. You can continue using your existing OpenAI SDK by changing the base URL and model ID.

What should you evaluate before moving production traffic to GPT-5-Nano?

Test your developer tools and real-time applications. Confirm that the accuracy meets your requirements given the model’s focus on speed and cost over deep reasoning.

How much does prompt caching save on gpt-5-nano?

gpt-5-nano supports prompt caching, which can significantly reduce costs for repeated prompts with shared prefixes. The cache read price is substantially lower than the standard input price. Check the current pricing page for the exact cache hit discount ratio for gpt-5-nano.

How should you set the output budget for gpt-5-nano?

For gpt-5-nano, set the max_tokens or max_completion_tokens parameter to control spending per call. Start with a budget aligned to your typical response length and increase only when longer outputs are genuinely needed. Monitor token usage in the API response headers to tune your budget over time.

What is the rate limit for gpt-5-nano?

gpt-5-nano rate limits vary by your MixRoute subscription plan. Check your plan details in the console for requests per minute (RPM) and tokens per minute (TPM) limits. Run a small load test before production to confirm your effective quota.

Model detail

GPT-5 nano

Provided by OpenAI

Pay-as-you-go

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

Model ID: gpt-5-nano

Context length: 400K
Max output: 128K
I/O modalities
Released: 2025-08

API endpoints

One MixRoute gateway, OpenAI-compatible

OpenAI-compatible /v1/chat/completions POST

Pricing

Flat rate, unit: /1M Tokens

Input

$0.0500 /1M Tokens

Completion

$0.4000 /1M Tokens

Cache read

$0.0050 /1M Tokens

Selection summary

Quickly judge whether it fits your workload

What is this model good for?

Nano model for fast efficient tasks

GPT-5 nano: GPT-5 Nano is our fastest, cheapest version of GPT-5. It's great for summarization and classification tasks. For most new speed- and cost-sensitive workloads, we recommend starting. 400,000-token context.

What should you check before using it?

400,000 context, 128,000 output

OpenAI model. Supports tool calling, structured outputs, function calling. Knowledge cutoff: 2024-05-31.

Why use it through MixRoute?

Drop-in via OpenAI-compatible endpoint on MixRoute

Set the model parameter to "gpt-5-nano" and use your MixRoute API key.

Capabilities & compatibility

Unconfirmed capabilities stay "Unknown," no guesses

Tool calling

GPT-5 nano supports function and tool calls.

EX Send a tools definition; the response returns tool_calls to execute and feed results back.

Structured output

GPT-5 nano can produce JSON-formatted output on demand.

EX response_format: { type: "json_schema" } forces valid JSON output.

Streaming

GPT-5 nano supports streamed responses.

EX stream: true streams tokens incrementally, so chat UIs render as they arrive.

Prompt caching

GPT-5 nano supports prompt caching under supported routing conditions.

EX Keep the system prompt and tool definitions at the start of the request; repeated prefixes are automatically billed at the cache-read rate.

Vision input

GPT-5 nano can process image inputs alongside text.

EX Pass a base64-encoded image in a image_url content part alongside text messages.

OpenAI SDK

Call GPT-5 nano through MixRoute's OpenAI-compatible endpoint.

EX Change base_url to https://api.mixroute.ai/v1; everything else follows the OpenAI style.

Token cost estimator

Live estimate from this page's pricing, not an actual bill

Input tokens Max per request 400K

Output tokens Max per request 128K

Requests / month

Cache hit rate 0%

Share of the same prefix read repeatedly, up to 100%

FAQ

gpt-5-nano supports up to 128000 output tokens per request. Plan your prompts to stay within this limit, and use the max_tokens or max_completion_tokens parameter to control output length.

Get started

01

Create an API key

Generate a key in the Console; one key calls every model.
02

Set the base URL

Fully OpenAI SDK-compatible; just swap the URL to connect.

https://api.mixroute.ai/v1
03

Specify the model ID

In the request's model field, enter:

gpt-5-nano

Create an API key

New users get $5 in free credits

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.

Create an API key View integration docs