o3-mini
o3-mini is a text generation model from OpenAI designed for reasoning-intensive tasks with a 200,000-token context window.
OpenAICompact reasoning model for STEM tasks
o3-mini is a reasoning-focused language model released by OpenAI in January 2025. It belongs to the o3 model family and is designed to handle tasks that benefit from structured, step-by-step reasoning, particularly in areas like mathematics, science, and programming. A notable feature is its configurable reasoning effort level, which lets users trade off between response speed and depth of reasoning. The model supports a 200,000-token context window and can produce responses up to 100,000 tokens in length.
o3-mini is well-suited for developers and researchers who need reliable performance on logic-heavy or technical tasks without deploying a larger model. Its adjustable reasoning effort setting makes it flexible for use cases ranging from quick lookups to complex multi-step problem solving. Because it is a text-only model, it does not process images or video. It is available as a first-party OpenAI model and can be accessed through MindStudio without managing API keys directly.
What o3-mini supports
Adjustable Reasoning Effort
Exposes a reasoning effort selector that lets users control how deeply the model reasons before responding, balancing speed against thoroughness.
Large Context Window
Accepts up to 200,000 tokens of input, enabling analysis of long documents, codebases, or extended conversation histories in a single request.
Extended Response Length
Can generate responses up to 100,000 tokens, supporting detailed explanations, long-form code output, or multi-step reasoning traces.
Math and Science Reasoning
Optimized for structured problem solving in mathematics and science, applying chain-of-thought style reasoning to reach accurate conclusions.
Code Generation
Generates, explains, and debugs code across common programming languages, leveraging its reasoning capabilities to handle algorithmic and logic-heavy problems.
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Get Started FreeBenchmark scores
Scores represent accuracy — the percentage of questions answered correctly on each test.
| Benchmark | What it tests | Score |
|---|---|---|
| MMLU-Pro | Expert knowledge across 14 academic disciplines | 79.1% |
| GPQA Diamond | PhD-level science questions (biology, physics, chemistry) | 74.8% |
| MATH-500 | Undergraduate and competition-level math problems | 97.3% |
| AIME 2024 | American math olympiad problems | 77.0% |
| LiveCodeBench | Real-world coding tasks from recent competitions | 71.7% |
| HLE | Questions that challenge frontier models across many domains | 8.7% |
| SciCode | Scientific research coding and numerical methods | 39.9% |
Common questions about o3-mini
What is the context window size for o3-mini?
o3-mini supports a context window of 200,000 tokens, meaning it can process up to that amount of combined input text in a single request.
What does the Reasoning Effort setting do?
The Reasoning Effort input lets you select how much internal reasoning the model applies before generating a response. Higher effort typically produces more thorough answers at the cost of additional latency.
Does o3-mini support image or video inputs?
No. Based on the available metadata, o3-mini is a text-only model and does not support image or video analysis.
What is the maximum response length o3-mini can produce?
o3-mini can generate responses up to 100,000 tokens in a single output, which is suitable for long-form content, detailed code, or extended reasoning traces.
When was o3-mini released?
o3-mini was released in January 2025 by OpenAI and became available on MindStudio on January 31, 2025.
What people think about o3-mini
The Reddit threads found do not directly discuss o3-mini in depth. One thread references o3-mini-medium as a benchmark comparison point when evaluating a third-party model, suggesting the community uses it as a known reference for reasoning performance.
The threads are primarily focused on other models rather than o3-mini itself, so direct community sentiment about o3-mini's strengths or limitations cannot be reliably summarized from this data.
Qwen 3 !!!
XBai o4 is live and claiming to beat OpenAI's o3-mini-medium in reasoning with parallel thinking, fast inference, and better web search.
Parameters & options
Used to give the model guidance on how many reasoning tokens it should generate before creating a response to the prompt. Low will favor speed and economical token usage, and high will favor more complete reasoning at the cost of more tokens generated and slower responses. The default value is medium, which is a balance between speed and reasoning accuracy.
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