OpenAI: o3 Mini

File input Text input Text output
Author's Description

OpenAI o3-mini is a cost-efficient language model optimized for STEM reasoning tasks, particularly excelling in science, mathematics, and coding. This model supports the `reasoning_effort` parameter, which can be set to "high", "medium", or "low" to control the thinking time of the model. The default is "medium". OpenRouter also offers the model slug `openai/o3-mini-high` to default the parameter to "high". The model features three adjustable reasoning effort levels and supports key developer capabilities including function calling, structured outputs, and streaming, though it does not include vision processing capabilities. The model demonstrates significant improvements over its predecessor, with expert testers preferring its responses 56% of the time and noting a 39% reduction in major errors on complex questions. With medium reasoning effort settings, o3-mini matches the performance of the larger o1 model on challenging reasoning evaluations like AIME and GPQA, while maintaining lower latency and cost.

Key Specifications
Cost
$$$$$
Context
200K
Parameters
200B
Released
Jan 31, 2025
Speed
Ability
Reliability
Supported Parameters

This model supports the following parameters:

Structured Outputs Response Format Seed Max Tokens Tool Choice Tools
Features

This model supports the following features:

Response Format Tools Structured Outputs
Performance Summary

OpenAI o3-mini, released on January 31, 2025, is a cost-efficient language model specifically optimized for STEM reasoning tasks. It demonstrates moderate speed performance, ranking in the 36th percentile, and is positioned at premium pricing levels, falling into the 18th percentile. Notably, the model exhibits exceptional reliability with a 100% success rate across all benchmarks, indicating consistent and usable responses. The o3-mini excels in specialized areas, achieving 95.0% accuracy in Mathematics (95th percentile) and 98.0% in Reasoning (93rd percentile), matching the performance of the larger o1 model on challenging evaluations like AIME and GPQA with medium reasoning effort. It also shows strong performance in Coding (93.0% accuracy, 85th percentile) and General Knowledge (99.5% accuracy, 76th percentile). While its Hallucinations accuracy is 96.0% (53rd percentile), its Instruction Following accuracy is 59.6% (63rd percentile), suggesting some room for improvement in complex multi-step directives. The model supports adjustable `reasoning_effort` levels, function calling, and structured outputs, making it a versatile tool for developers. Its primary strength lies in its STEM capabilities and high reliability, despite its premium pricing.

Model Pricing

Current Pricing

Feature Price (per 1M tokens)
Prompt $1.1
Completion $4.4
Input Cache Read $0.55

Price History

Available Endpoints
Provider Endpoint Name Context Length Pricing (Input) Pricing (Output)
OpenAI
OpenAI | openai/o3-mini-2025-01-31 200K $1.1 / 1M tokens $4.4 / 1M tokens
Benchmark Results
Benchmark Category Reasoning Strategy Free Executions Accuracy Cost Duration
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