GPT o3 & o4-mini
Last updated
Last updated
OpenAI o3 and o4-mini are the latest additions to the "o-series" of models, announced on April 16, 2025.
These models are the most capable released by OpenAI, excelling in reasoning and complex task processing.
Agentic tool use: They can autonomously access and combine all tools available within ChatGPT (web search, file/data analysis, visual reasoning, image generation).
Emphasis on enhanced problem-solving, intelligent tool selection, and deeper reasoning.
Both models can "think with images," integrating visual inputs directly into their reasoning process for multimodal understanding.
O3 is the powerhouse for maximum reasoning; O4-mini is optimized for efficiency and cost.
Most powerful reasoning model to date from OpenAI.
Excels in coding, mathematics, science, and visual perception.
Achievements:
Codeforces ELO: 2706 (with terminal access)
SWE-bench: 69.1%
MMMU benchmark: new records
Handles complex, multi-faceted queries requiring deep analysis.
Strong visual reasoning: can interpret and manipulate images (rotation, zoom, transformation), even with low quality.
20% fewer major errors than o1 in real-world tasks (notably in programming, consulting, creative ideation).
Large context window: 200,000 tokens; output up to 100,000 tokens.
Pricing: $10/million input tokens, $40/million output tokens (75% discount on cached input tokens).
Smaller, faster, and more cost-efficient model.
Strong performance in mathematics, coding, and visual tasks.
Top scores:
AIME 2024: 93.4%
AIME 2025: 92.7% (99.5% with Python interpreter)
Outperforms o3-mini in non-STEM and data science tasks.
Supports higher usage limits, ideal for high-volume applications (e.g., chatbots, real-time analytics).
SWE-bench: 68.1% (close to o3)
Pricing: $1.10/million input tokens, $4.40/million output tokens (75% input caching discount).
Same context window and output limit as o3.
Available to free users via the "think" button in ChatGPT.
Both models can autonomously use and combine all ChatGPT tools.
Capabilities include:
Web search for real-time info
File/data analysis with Python
Deep visual reasoning
Image generation
Models reason about which tools to use and chain multiple tool calls for complex tasks.
Example: For "How will summer energy usage in California compare to last year?", the model can search, analyze, generate graphs, and explain—all autonomously.
Supports custom tools via API function calling.
Models can "think with images," not just recognize them.
Integrate visual info into reasoning chains for multimodal problem-solving.
Handle various image types (whiteboards, diagrams, sketches), even if blurry or reversed.
Can manipulate images (rotate, zoom, transform) as part of reasoning.
Achieve best-in-class accuracy on visual perception tasks (e.g., MMMU, MathVista).
Example: O3 analyzed a research poster by zooming into elements to extract details for conclusions.
Reasoning Power
Highest
Strong
Speed
Slower, more thorough
Very fast
Cost (Input)
~$10/million tokens
~$1.10/million tokens
Cost (Output)
~$40/million tokens
~$4.40/million tokens
Use Cases
Deep analysis, research, ideation, complex coding
Customer support, dev tools, analytics, high-volume tasks
O3: For users needing the highest reasoning, willing to pay premium.
O4-mini: Balanced performance and cost, suitable for broader applications.
Both show significant improvements over predecessors (o1, o3-mini).
O3: 200,000 token context window (vs. GPT-4's 128,000); 100,000 output tokens (vs. GPT-4's 4,096).
O3: 96.7% on AIME 2024 (vs. GPT-4's 64.5% on MATH).
GPT-4.1: Even larger context window (1M tokens), improved coding/instruction following, lower cost/latency.
O4-mini outperforms Google's Gemini 2.5 Pro in mathematical reasoning (AIME 2024/2025).
O3 scores higher than Gemini 2.5 Pro on SWE-bench (coding).
Both models set new standards for reasoning, coding, and multimodal tasks.
This document summarizes the key features, differences, and competitive positioning of OpenAI's O3 and O4 Mini models, providing a clear, structured overview for easy reference.