OpenAI o3OpenAI's advanced reasoning model for complex, multi-step problem solving

4.0 (4)

Reviewed by Daniel Nikulshyn·Updated July 2026

Overview

OpenAI o3 is a frontier reasoning model designed to tackle problems that require careful, step-by-step thinking. It builds on the o-series approach of spending more compute at inference time to plan, verify, and refine answers, making it well-suited for tasks in mathematics, coding, science, and logical analysis. Compared to general-purpose chat models, o3 emphasizes depth over speed. It can break down ambiguous prompts, evaluate multiple approaches, and produce more reliable outputs on benchmarks that stress reasoning and tool use. Developers can access it through the OpenAI API and ChatGPT, where it integrates with tools like web browsing, Python, and file analysis. The model is aimed at researchers, engineers, and power users who need stronger accuracy on hard problems and are willing to trade some latency and cost for higher-quality results.

Key features

Extended chain-of-thought reasoning
Tool use including code, web, and file inputs
Large context window for long documents
API and ChatGPT availability
Improved accuracy on STEM benchmarks
Supports complex agentic workflows

Pricing

Model: Free
Category: LLM
Rating: 4.0 / 5 (4)

Use cases

Developing Robust Evaluations

Build evaluations to assess previously identified capabilities or potential new ones with significant security or safety implications. These evaluations should highlight threat models that identify specific capabilities, behaviors, and propensities that may pose concrete risks.

Creating Potential High-Risk Capabilities Demonstrations

Develop controlled demonstrations showcasing how reasoning models’ advanced capabilities could cause significant harm to individuals or public security absent further mitigation. Examples of scenarios that should be focused on include those not possible with currently widely adopted models or tools.

Pros & Cons

Pros

Strong performance on math, coding, and science benchmarks
Handles multi-step and ambiguous problems well
Integrates with tools like code execution and browsing
Useful for research, analysis, and technical workflows

Cons

Slower responses than standard chat models
Higher cost per token for heavy reasoning use
Overkill for simple, everyday queries
Can still hallucinate on edge cases

Battle record

Across 2 battles in the Pantheon.

1st

2nd

3rd

Last 2 battles

Reviews

4.0

Average from 4 ratings.

Grace Okafor

Jan 6, 2026

Years in this space

I've evaluated a lot of these over the years. What stands out here is supports complex agentic workflows — handled better than most — and handles multi-step and ambiguous problems well. Higher cost per token for heavy reasoning use is my one real gripe. Worth the time if this is your use case.

Kwame Mensah

Nov 1, 2025

Years in this space

I've evaluated a lot of these over the years. What stands out here is aPI and ChatGPT availability — handled better than most — and handles multi-step and ambiguous problems well. Higher cost per token for heavy reasoning use is my one real gripe. Worth the time if this is your use case.

Daniel Schmidt

Oct 3, 2025

Use it every day

Honestly didn't expect to like it this much. API and ChatGPT availability is exactly what I needed, and strong performance on math, coding, and science benchmarks. I do wish overkill for simple, everyday queries, but I reach for it almost every day now and it just clicks.

Camille Laurent

Aug 30, 2025

Compared a few options

Evaluated this against two competitors. Where it wins: supports complex agentic workflows and strong performance on math, coding, and science benchmarks. Where it lags: can still hallucinate on edge cases. On balance the feature set — especially tool use including code, web, and file inputs — justifies the 4 stars for our use case.

Q&A

What are the main limitations I should be aware of?

o3 responds slower than typical chat models, costs more per token, can be overkill for simple queries, and may still hallucinate on edge cases.

Asked by Yara Mansour · Mar 30, 2026

What types of problems is o3 best suited for?

o3 excels at multi-step, ambiguous tasks in mathematics, coding, scientific analysis, and logical reasoning, making it ideal for researchers, engineers, and power users needing high accuracy.

Asked by Valentina Marino · Mar 28, 2026

What integrations are available for using o3 in my applications?

You can access o3 via the OpenAI API and within ChatGPT, and it supports tool use such as web browsing, Python code execution, and file analysis for richer workflows.

Asked by Farah Rahimi · Feb 5, 2026

How does the pricing of OpenAI o3 compare to standard ChatGPT models?

o3 uses more compute for deep reasoning, so it incurs a higher cost per token than standard chat models; exact pricing is available on OpenAI’s pricing page.

Asked by Nour Khalil · Jan 22, 2026