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Model detail

o4-mini-2025-04-16

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

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

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API endpoints

One MixRoute gateway, OpenAI-compatible

  • OpenAI-compatible /v1/chat/completions POST

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Pricing

Flat rate, unit: /1M Tokens

Input

$1.1000 /1M Tokens

Completion

$1.1000 /1M Tokens

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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.

Why use it through MixRoute?

Use the compatible endpoint with stable model ID

Use the confirmed compatible endpoint with model ID o4-mini 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

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

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FAQ

o4-mini is a compact reasoning model in OpenAI’s o-series, optimized for fast, cost-efficient performance. It retains strong multimodal and agentic capabilities, including tool use and structured output, and performs competitively on benchmarks like AIME and SWE-bench.

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.