OpenAI o3: a full-scale reasoning model featuring reinforcement learning scaling, native tool use, and groundbreaking in-chain image reasoning.
Capabilities, design details, and architectural traits
o3 is OpenAI's full-scale o-series reasoning model, built around a documented finding: large-scale reinforcement learning exhibits the same "more compute = better performance" scaling trend observed in GPT-series pretraining. OpenAI pushed an additional order of magnitude in both training compute and inference-time reasoning for o3, and performance continued to improve.
| Trait | Detail |
|---|---|
| Images in the chain of thought | o3 integrates images directly into its reasoning process - it thinks with images, not just about them; it can process blurry, reversed, or low-quality images and manipulate them (rotate, zoom, transform) mid-reasoning |
| RL-trained tool use | Trained via reinforcement learning to reason about when and how to use tools, not just how - tool deployment is based on desired outcomes |
| Reasoning effort is configurable | The reasoning_effort parameter controls how many reasoning tokens are allocated per request |
| API availability | Available via both Chat Completions and Responses API; the Responses API additionally supports reasoning summaries and preserving reasoning tokens across function calls |
| Fine-tuning | Not supported |
OpenAI's official positioning is to use o3 for multi-step problems that involve analysis across text, code, and images. It excels at technical writing and instruction-following in addition to math, science, and coding - a broader documented scope than earlier o-series models.
Independent evaluations · Artificial Analysis
Evaluate specifications, pricing, and independent benchmark indices
| Model Details | |||
|---|---|---|---|
| General Info | |||
| Provider | OpenAI | Anthropic | Anthropic |
| Release Date | April 16, 2025 | July 24, 2026 | June 9, 2026 |
| Knowledge Cutoff | Jun 2024 | May 2026 | - |
| Context & Limits | |||
| Context Window | 200K | 1M Best Context Window | 1M Best Context Window |
| Pricing (per 1M tokens) | |||
| Input Pricing | $2 Best Input Pricing | $5 | $10 |
| Output Pricing | $8 Best Output Pricing | $25 | $50 |
| Modalities | |||
| Inputs | imagetextfile | textimage | textimagefile |
| Outputs | text | text | text |
| Benchmarks (0-100) | |||
| Intelligence Index | 31.1 | 63.1 Best Intelligence Index | 62.1 |
| Coding Index | - | 78.0 Best Coding Index | 76.5 |
| Agentic Index | - | 59.2 Best Agentic Index | 56.6 |
Graduate-level reasoning and expert Q&A evaluation.
Extremely difficult logical reasoning and knowledge.
Logical reasoning over long context windows.
Independent evaluation data provided by Artificial Analysis. To view the latest benchmarks and full details, visit their official site.
