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o4 Mini

by OpenAI · Released Apr 2025

Multimodal
57.0
avg score
Rank #83
Compare
Better than 64% of all models
Context
200K tokens (~100 books)
Input $/1M
$1.10
Output $/1M
$4.40
Type
multimodal
License
Proprietary
Benchmarks
26 tested
Data updated today
About

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...

Tested on 26 benchmarks with 53.2% average. Top scores: MATH level 5 (97.8%), HELM — IFEval (92.9%), HELM — WildBench (85.4%).

Looking for similar performance at lower cost?
Qwen2.5 7B Instruct scores 57.4 (101% as good) at $0.04/1M input · 96% cheaper
Capabilities
coding
47.0
#75 globally
reasoning
44.2
#59 globally
math
56.5
#57 globally
knowledge
54.3
#77 globally
language
92.9
#6 globally
Benchmark Scores
Compare All
Tested on 26 benchmarks · Ranked across 5 categories
Score Distribution (all 233 models)
0255075100
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Aider polyglot

Multi-language code editing from Aider. Tests editing ability across Python, JavaScript, TypeScript, Java, C++, Go, Rust, and more.

72.0
CadEval

Computer-aided design evaluation. Tests understanding of CAD concepts, 3D modeling, and engineering design principles.

62.0
WeirdML

Unusual and adversarial machine learning challenges. Tests robustness of reasoning about edge cases in ML systems.

52.6
HELM — WildBench

Stanford HELM WildBench evaluation. Tests reasoning on challenging real-world tasks.

85.4
ARC-AGI

Abstraction and Reasoning Corpus. Tests fluid intelligence through novel visual pattern recognition puzzles. Core measure of general intelligence.

58.7
SimpleBench

Deceptively simple questions that humans find easy but AI models often get wrong. Tests common sense and reasoning gaps.

26.4
MATH level 5

Competition-level math from AMC, AIME, and olympiad problems. Level 5 is the hardest tier, requiring creative problem-solving.

97.8
OTIS Mock AIME 2024-2025

Mock AIME (American Invitational Mathematics Exam) problems from OTIS. Tests mathematical competition performance.

81.7
HELM — Omni-MATH

Stanford HELM evaluation of mathematical reasoning across diverse problem types.

72.0
Excellent (85+) Good (70-85) Average (50-70) Below (<50)
Links
Documentation
Community
BenchGecko API
o4-mini
Specifications
  • Typemultimodal
  • Context200K tokens (~100 books)
  • ReleasedApr 2025
  • LicenseProprietary
  • StatusActive
  • Cost / Message~$0.007
Available On
OpenAI logoOpenAI$1.10
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o4 Mini is a proprietary multimodal AI model by OpenAI, released in April 2025. It has an average benchmark score of 57.0. Context window: 200K tokens.