o4 Mini High

openai/o4-mini-high-2025-04-16

OpenAI: o4 Mini High processes image, text, and file inputs to generate text outputs. It has a context length of 200,000 tokens and supports tools and reasoning. Input pricing is $1.1 per million tokens, while output pricing is $4.4 per million tokens.

  • tool use
  • structured outputs
  • reasoning

At a glance

provideropenai
releasedApr 16, 2025
context200K
input / M$1.10

Specifications

What the API gives you

Context window
200K tokens
Max output
100K tokens
Input price
$1.10 / 1M tokens
Output price
$4.40 / 1M tokens
Cache read
$0.28 / 1M tokens
Modalities
image, text, file → text
Knowledge cutoff
Jun 30, 2024
Released
Apr 16, 2025

Measured evidence

Public benchmark record

Aider Polyglot
72%2026-10-20

LMArena data licensed CC-BY-4.0. Aider (Apache-2.0) and SWE-bench (MIT) are open. Design Arena uses blind human preference.

Task evidence

How broad is the support?

Each status is exact to this model version and the selected task. Official release claims remain provisional.

  • Best Local LLM for CodingProvisional evidence

    38% of intended weighted task evidence across 1 independent source; broader independent confirmation is still missing from LiveBench Coding or LMArena WebDev. 4 of 4 configured evaluation feeds currently have results.

  • Best LLM for Debugging & Code ReviewProvisional evidence

    22% of intended weighted task evidence across 1 independent source; broader independent confirmation is still missing from LiveBench Coding or LMArena WebDev. 5 of 5 configured evaluation feeds currently have results.

  • Best LLM for Code CompletionProvisional evidence

    21% of intended weighted task evidence across 1 independent source; broader independent confirmation is still missing from LiveBench Coding or LMArena WebDev. 3 of 3 configured evaluation feeds currently have results.

  • Best LLM for CodingProvisional evidence

    11% of intended weighted task evidence across 1 independent source; broader independent confirmation is still missing from Design Arena Coding or LiveBench Coding. 7 of 7 configured evaluation feeds currently have results.

Recommendation coverage

Where this model appears

Not currently included in a published recommendation. The task evidence panel above says exactly what is confirmed and what is still missing.

Catalog data via OpenRouter and models.dev. Last checked within the past 6 hours.