- OpenAI o3 is now available to ChatGPT Plus, Pro, and API users
- Pricing: $2/M input tokens, $8/M output tokens
- Scores 87.5% on ARC-AGI benchmark — significantly above o1
- Best use cases: complex reasoning, math, science, coding
What Is OpenAI o3?
OpenAI’s o3 model represents a major step forward in reasoning capability. Unlike standard LLMs that generate text token by token, o3 uses extended thinking — it reasons through problems before producing output, much like a human working through a complex problem on paper.
The result is dramatically better performance on tasks that require multi-step logic: mathematics, competitive coding, scientific analysis, and strategic planning. In testing, o3 scored 87.5% on the ARC-AGI benchmark, a test designed to be resistant to pattern-matching LLMs.
o3 vs o1 — What Actually Changed
| Feature | o1 | o3 |
|---|---|---|
| ARC-AGI Score | 32% | 87.5% |
| Coding (SWE-bench) | 48.9% | 71.7% |
| Math (AIME) | 83% | 96.7% |
| Input price | $15/M | $2/M |
| Speed | Slow | Faster |
Who Should Use o3?
o3 is built for power users who hit the ceiling of standard models. If you’re using ChatGPT for casual writing or summarization, o3 adds little value. But if your work involves:
- Complex debugging — o3 can trace multi-file codebases and reason through logic errors that Sonnet or GPT-4o miss
- Scientific research — literature synthesis, hypothesis generation, statistical reasoning
- Financial modeling — multi-step calculation chains with validation
- Competitive programming — it ranks in the 99th percentile on Codeforces problems
For everyday AI tasks — writing, summarizing, brainstorming — GPT-5, Claude Sonnet, or Gemini 2.5 Flash remain more cost-effective choices.
Pricing and Access
o3 is available now via the OpenAI API at $2 per million input tokens and $8 per million output tokens — a dramatic reduction from o1’s $15/$60 pricing. ChatGPT Plus and Pro subscribers get access through the model selector.
There’s also o3-mini at $1.10/$4.40 per million tokens, which retains most of the reasoning gains at lower cost — the best option for high-volume reasoning tasks.
What This Means for the AI Landscape
o3’s release changes the calculus for AI-assisted knowledge work. The gap between “good enough” LLMs and genuine reasoning systems is narrowing rapidly. Developers building on GPT-4o or Claude Haiku for analytical tasks should evaluate whether o3-mini’s cost-to-capability ratio makes it worth the switch.
The research and search AI space is also being reshaped — models that can reason deeply are increasingly competitive with specialized search tools for complex queries.
Frequently Asked Questions
Is o3 worth the extra cost over GPT-4o?
For reasoning-heavy tasks: yes. o3 and o3-mini dramatically outperform GPT-4o on math, coding, and logic. For writing or summarization: stick with GPT-4o or GPT-4o-mini.
Does o3 replace o1?
Effectively yes — o3 outperforms o1 on nearly every benchmark while costing 85% less. OpenAI is phasing o1 out of the main interface.
Can I use o3 via the API?
Yes. o3 and o3-mini are both available via the OpenAI API. Access requires a paid OpenAI account with API credits.
Bottom Line
o3 is the most significant reasoning model released to date. At $2/M input tokens it’s accessible to developers who previously couldn’t afford o1. If your workflows involve complex problem-solving, it’s worth testing immediately — the benchmark gains are real and the price drop makes it practical.
This article was produced with the assistance of AI tools and reviewed by the AIStackDigest editorial team.