OpenAI o3-mini
High-speed, cost-efficient reasoning model with adjustable reasoning effort levels.
Technical Specification Matrix
Architecture & Engineering Overview
Compact Autoregressive Transformer with Test-Time Compute
Engineered specifically for STEM disciplines and technical coding workflows, o3-mini offers controllable reasoning effort (low, medium, high) allowing developers to balance latency, cost, and analytical depth for production software environments.
Empirical Academic Benchmarks
OpenAI o3-mini Benchmark Performance
OpenAI o3-mini Announcement (Jan 2025). High reasoning effort configuration.
Challenging competition-level high school and undergraduate mathematics problems evaluating step-by-step analytical proof capability.
Google-proof PhD-level multiple-choice questions in biology, physics, and chemistry designed by domain experts.
Expanded reasoning benchmark with 12,000+ challenging multi-step questions across 14 academic and professional subjects.
Human-verified subset of real-world GitHub issues evaluating autonomous agent capability to debug and resolve real open-source bugs.
Standard benchmark testing zero-shot Python function generation against functional unit test suites.
Verified Core Competencies
Head-to-Head Comparisons
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