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  4. GPT-o4 Mini
OpenAI
Released April 16, 2025Cutoff June 2024

GPT-o4 Mini

OpenAI o4-mini: fast, cost-efficient o-series reasoning model optimized for coding and visual tasks, fine-tuning support, higher rate limits than o3.

Visit OpenAIAnnouncement
Inputs
Image
Text
File
Outputs
Text

Model Overview

Capabilities, design details, and architectural traits

o4-mini - Fast o-Series Reasoning with Fine-Tuning Support

o4-mini is OpenAI's small o-series model built for fast, cost-efficient reasoning with a specific focus on coding and visual tasks. Its most structurally distinctive trait within the o-series is that it supports fine-tuning - something o3 and o3-pro do not. OpenAI also explicitly documents that o4-mini supports significantly higher usage limits than o3, positioning it as the o-series option for high-volume, high-throughput workloads.

TraitDetail
Fine-tuningSupported - unlike o3, which does not support fine-tuning
Usage limitsSignificantly higher rate limits than o3, documented for high-volume and high-throughput use
Visual reasoningIntegrates images directly into the chain of thought, not as isolated inputs
Reasoning effortConfigurable via reasoning_effort; the o4-mini-high variant in ChatGPT uses the high setting
Speed tierMedium (faster than o3, which is rated Slowest)
Reasoning summarySupports the detailed reasoning summary setting

Designed for Coding and Visual Tasks at Scale

o4-mini is optimized for exceptionally efficient performance in coding and visual tasks. Its combination of fine-tuning support, medium speed, and documented high-throughput positioning makes it the o-series choice when task-specific adaptation or volume are requirements that o3 cannot meet.

Benchmark Performance

Independent evaluations · Artificial Analysis

26.1%
Intelligence

Accuracy & Capability Details

GPQA - Graduate Science78.4%
Humanity's Last Exam16.5%
SciCode - Scientific Coding46.5%
Instruction Following68.7%
Long Context Reasoning60.0%
τ²-Bench - Agentic Tasks55.6%
TerminalBench - System Control15.2%
Specs
Context window
200Ktokens
Input pricing
$1.10per 1M tokens
Output pricing
$4.40per 1M tokens
Cached input
$0.28per 1M tokens

Prices in USD.

Compare Models Side-by-Side

Evaluate specifications, pricing, and independent benchmark indices

Model Details
General Info
ProviderOpenAIAnthropicAnthropic
Release DateApril 16, 2025July 24, 2026June 9, 2026
Knowledge CutoffJun 2024May 2026-
Context & Limits
Context Window200K
1M
Best Context Window
1M
Best Context Window
Pricing (per 1M tokens)
Input Pricing
$1.10
Best Input Pricing
$5$10
Output Pricing
$4.40
Best Output Pricing
$25$50
Modalities
Inputs
imagetextfile
textimage
textimagefile
Outputs
text
text
text
Benchmarks (0-100)
Intelligence Index26.1
63.1
Best Intelligence Index
62.1
Coding Index-
78.0
Best Coding Index
76.5
Agentic Index-
59.2
Best Agentic Index
56.6
GPT-o4 Mini
Claude Opus 5
Claude Fable 5

GPQA Benchmark

Graduate-level reasoning and expert Q&A evaluation.

78%
GPT-o4 Mini
GPQA Benchmark
Score: 78%
GPT-o4 Mini
93%
Claude Opus 5
GPQA Benchmark
Score: 93%
Claude Opus 5
93%
Claude Fable 5
GPQA Benchmark
Score: 93%
Claude Fable 5

Humanity's Last Exam

Extremely difficult logical reasoning and knowledge.

17%
GPT-o4 Mini
Humanity's Last Exam
Score: 17%
GPT-o4 Mini
55%
Claude Opus 5
Humanity's Last Exam
Score: 55%
Claude Opus 5
56%
Claude Fable 5
Humanity's Last Exam
Score: 56%
Claude Fable 5

Long Context Reasoning

Logical reasoning over long context windows.

60%
GPT-o4 Mini
Long Context Reasoning
Score: 60%
GPT-o4 Mini
76%
Claude Opus 5
Long Context Reasoning
Score: 76%
Claude Opus 5
77%
Claude Fable 5
Long Context Reasoning
Score: 77%
Claude Fable 5

Independent evaluation data provided by Artificial Analysis. To view the latest benchmarks and full details, visit their official site.

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