openai
OpenAI: o3 Pro
openai/o3-pro
Our take
AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.
According to OpenRouter's catalog, openai/o3-pro is an OpenAI o-series model positioned for complex reasoning: it accepts text, image, and file inputs, returns text, and always uses reasoning. The catalog says the o-series is trained with reinforcement learning to deliberate before answering and describes o3-pro as applying more compute to harder reasoning. It lists structured outputs, tool calling, seed, and reasoning controls. An independent model card was not available in this source pack, and no completed benchmark results were supplied, so performance remains unverified.[1]
Strengths
- Catalog-reported reasoning design: the o-series is described as reinforcement-learning-trained to think before answering, and o3-pro is described as allocating more compute to harder reasoning.[1]
- Broad inputs and long context: the catalog lists text, image and file inputs, text output, and a 200,000-token context window.[1]
- Integration controls: tools and tool choice, structured outputs and response format, seed, maximum token and reasoning parameters are listed.[1]
Limitations
- Only catalog evidence was supplied; no independent model card was available in this source pack, and the benchmark fields were empty or null. Measured quality remains unknown.[1]
- Reasoning is mandatory, and no effort levels or default effort are listed, so reasoning depth cannot be selected through those catalog controls.[1]
- Output is text only; the catalog lists a June 30, 2024 knowledge cutoff and a December 11, 2026 expiration date without explaining the latter.[1]
Where to use it
- Consider for difficult analytical, planning, coding, or multi-step tasks where mandatory deliberation may be useful; validate quality and latency on the target workload.[1]
- Potentially suitable for applications that accept user-supplied text, images and files but only need a text answer.[1]
- Worth evaluating for tool-using agents or structured-output workflows that need the listed API controls.[1]
Sources
- [1] OpenRouter catalog · OpenAI: o3 ProSources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
The o-series of models are trained with reinforcement learning to think before they answer and perform complex reasoning. The o3-pro model uses more compute to think harder and provide consistently...
Specifications
- Model ID
- openai/o3-pro
- Canonical ID
- openai/o3-pro-2025-06-10
- Creator
- openai
- Added to OpenRouter
- 10.06.2025
- Context length
- 200,000
- Modality
- text+image+file->text
- Input modalities
- text, file, image
- Output modalities
- text
- Token pricing
- USD per 1M tokens: in $20 / out $80
- Knowledge cutoff
- 30.06.2024
- Expiration date
- 11.12.2026
Tasks and capabilities
A grade appears only where the source supplies a matching measurement for that task, the model is active and the cohort holds at least 10 comparable models. The capability column lists facts the source declares — supported formats, reasoning and tool parameters — which are not measured quality.
| Task | Grade | Source-declared capability |
|---|---|---|
| General quality | No measurement | reasoning: mandatory · parameters: include_reasoning, reasoning |
| Coding | No measurement | — |
| Agents | No measurement | parameters: structured_outputs, tool_choice, tools |
| Writing | No measurement | output: text |
| Reasoning | No measurement | reasoning: mandatory · parameters: include_reasoning, reasoning |
| Document analysis | No measurement | input: file |
| Vision | No measurement | input: image |
| Image generation | No measurement | — |
| Audio | No measurement | — |
| Video | No measurement | — |
| Embeddings | No measurement | — |
Evaluations
No evaluations are supplied for this model.
How grades work
Each letter grade compares a model only against other models scored by the same source and metric in the current snapshot. S means the top 10%, A the next 20%, B the next 30%, C the rest. Models without a published measurement are shown as not rated — a supported format alone never implies measured quality.
- S — S — top 10% of the cohort
- A — A — next 20% of the cohort
- B — B — next 30% of the cohort
- C — C — below the B band
Providers
Optional live provider statistics from OpenRouter. Missing values are unknown, not zero.
| Provider | Context length | Price in /1M | Price out /1M | Latency p50 (30m, s) | Throughput p50 (30m, tok/s) | Uptime (30m) |
|---|---|---|---|---|---|---|
| OpenAI | 200,000 | $20 | $80 | — | — | — |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.