o3-deep-research vs o1
o1 comes out ahead, 61 to 49 on our weighted score, and it is the cheaper option too.
OpenAIo3-deep-research
49/100- ECI—
- Price—
- Context200K
- Our pickOpenAI
o1
61/100- ECI141.9
- Price$15.00 / $60.00
- Context200K
Add a model
Make it a three-way comparison.
o1 is our pick
o1 is the better all-round choice, scoring 61/100 against o3-deep-research (49). It leads on inputs & features. The score weighs inputs & features 60%, context window 40%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceo1o1 $26.25 per 1M tokens (3:1 blend) · o3-deep-research unpriced
- Longest contextAbout the sameo3-deep-research 200,000 · o1 200,000 tokens
- Widest inputso1o3-deep-research: Text, Images · o1: Text, Images, PDFs
- Self-hostingNo open weightsBoth are available only through APIs
| Measure | Weight | o3-deep-research | o1 |
|---|---|---|---|
| Inputs & features | 60% | 60 | 80 |
| Context window | 40% | 32 | 32 |
| Overall | 100% | 49/100 | 61/100 |
Left out because at least one model lacks the data: capability and price. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | o3-deep-researchOpenAI | o1OpenAI |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | 141.9 |
| ECI rank | — | #92 of 148 |
| GPQA DiamondGraduate-level science questions | — | 76.8% |
| FrontierMath Tiers 1–3Research-level mathematics | — | 14.7% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 73.3% |
| SimpleQA VerifiedShort factual questions | — | 41.1% |
| Price per million tokens | ||
| Input | — | $15.00 |
| Output | — | $60.00 |
| Cached input | — | $7.50 |
| Blended (3:1) | — | $26.25 |
| Long-context rate | — | Same rate |
| Price source | — | Official OpenAI API |
| Limits | ||
| Context window | 200,000 tokens | 200,000 tokens |
| Max output | 100,000 tokens | 100,000 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | Yes |
| PDFs | No | Yes |
| Audio | No | No |
| Video | No | No |
| Reasoning | Yes | Yeslow · medium · high |
| Tool calling | Yes | Yes |
| Structured output | No | Yes |
| Availability | ||
| Weights | Proprietary | Proprietary |
| API model ID | — | o1 |
| API providers | — | 9 |
| Released | Jun 26, 2024 | Dec 5, 2024 |
| Knowledge cutoff | May 2024 | Sep 2023 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- o3-deep-research—
- o1$270.00
Which should you choose?
Which is better: o3-deep-research or o1?
o1 is the better all-round choice, scoring 61/100 against o3-deep-research (49). It leads on inputs & features. The score weighs inputs & features 60%, context window 40%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, o3-deep-research or o1?
o1 is cheaper at $15.00 input / $60.00 output per million tokens (official OpenAI API price). . At a typical mix of three input tokens to one output token, that is $26.25 per million tokens for o1 versus . o3-deep-research has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. o3-deep-research has not been scored yet and o1 has an ECI of 141.9.
Which is better for coding?
There are no published SWE-bench Verified results for o3-deep-research and o1 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.
Which has the bigger context window?
o3-deep-research and o1 share the same 200,000-token context window. Maximum output per response: o3-deep-research up to 100,000, o1 up to 100,000 tokens.
Which can read images, PDFs, audio or video?
o3-deep-research accepts text and images; o1 accepts text, images and PDFs. o1 handles the widest range of inputs.
Are any of these open source?
No. o3-deep-research and o1 are proprietary and only available through APIs and apps.
Which is newer?
o1 is the newest, released Dec 5, 2024. o3-deep-research came out Jun 26, 2024. Knowledge cutoff: o3-deep-research May 2024, o1 Sep 2023.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.
