Can you call o4-mini with the OpenAI SDK you already use?

Yes. o4-mini is served through a compatible endpoint. You can continue using your existing OpenAI SDK by changing the base URL and model ID.

How do you get a cache hit on o4-mini?

To get a cache hit on o4-mini, 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.

What is the max output length for o4-mini?

o4-mini supports up to 100000 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.

Does o4-mini support tool calling and structured output?

Yes. o4-mini supports tool use and structured output. Test with your specific tool definitions and JSON schemas to confirm compatibility with your workflows.

How much does prompt caching save on o4-mini?

o4-mini 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 o4-mini.

What is the rate limit for o4-mini?

o4-mini 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

o4-mini

Provided by OpenAI

Pay-as-you-go

OpenAI o4-mini is a compact reasoning model in the o-series, optimized for fast, cost-efficient performance while retaining strong multimodal and agentic capabilities. It supports tool use and demonstrates competitive reasoning and coding performance across benchmarks like AIME (99.5% with Python) and SWE-bench, outperforming its predecessor o3-mini and even approaching o3 in some domains. Despite its smaller size, o4-mini exhibits high accuracy in STEM tasks, visual problem solving (e.g., MathVista, MMMU), and code editing. It is especially well-suited for high-throughput scenarios where latency or cost is critical. Thanks to its efficient architecture and refined reinforcement learning training, o4-mini can chain tools, generate structured outputs, and solve multi-step tasks with minimal delay—often in under a minute.

Model specs

Model ID: o4-mini

Context length: 200K
Max output: 100K
I/O modalities
Released: 2025-04

API endpoints

One MixRoute gateway, OpenAI-compatible

OpenAI-compatible /v1/chat/completions POST

Pricing

Flat rate, unit: /1M Tokens

Input

$1.1000 /1M Tokens

Completion

$1.1000 /1M Tokens

Selection summary

Quickly judge whether it fits your workload

What is this model good for?

Fast, cost-efficient reasoning with tool use

Use o4-mini for high-throughput reasoning tasks where latency and cost are critical. It supports tool use, structured output, and multimodal inputs, making it suitable for agentic workflows at scale.

What should you check before using it?

Confirm tool use and structured output capabilities

Test your specific tool definitions, structured output schemas, and multimodal inputs. o4-mini is optimized for speed—verify it meets your accuracy requirements for your most demanding tasks. Knowledge cutoff: 2024-06-01.

Why use it through MixRoute?

Swap the base URL, keep the o4-mini client

MixRoute serves o4-mini on the OpenAI-compatible endpoint /v1/chat/completions; point your existing client at https://api.mixroute.ai/v1 with the model ID o4-mini and re-run your integration tests.

Capabilities & compatibility

Unconfirmed capabilities stay "Unknown," no guesses

Tool calling

o4-mini supports function and tool calls.

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

Structured output

o4-mini can produce JSON-formatted output on demand.

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

Streaming

o4-mini supports streamed responses.

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

Prompt caching

o4-mini 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

o4-mini can process image inputs alongside text.

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

OpenAI SDK

Call o4-mini 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 200K

Output tokens Max per request 100K

Requests / month

Cache hit rate –

This model has no cache-read price; caching is not counted

FAQ

Use the model ID o4-mini through the compatible chat completions endpoint. Check the current API documentation for the exact endpoint path and any required headers.

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:

o4-mini

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