Analysis Summary
OpenAI's o3 Deep Research is designed for complex investigation and analysis. It combines strong general reasoning with particularly capable mathematical performance, coding results, vision, file input, and a 200K context window. Tool use and function calling support workflows that need external actions or structured orchestration.
For an agency, it fits long-document research, technical analysis, evidence-heavy content planning, and client tasks where accuracy matters more than throughput. Vision and file support also make it useful for reviewing source material beyond plain text. Its coding capability is strong, though not at the level of specialist coding leaders, and the high output price limits its role in bulk content generation.
Use o3 Deep Research for high-value research and reasoning tasks, especially where its context capacity and multimodal input reduce the need for separate processing steps.
Assessed August 9, 2026
Editorial notes
o3 Deep Research combines strong reasoning, mathematical performance, vision, file handling, and a 200K context window with tool and function calling. Its premium output pricing suits research-heavy work rather than routine volume.
Rankings consider pricing, capabilities, benchmarks, and real-world applicability and are refreshed as new models launch. Feedback?
DFO Verdict
o3 Deep Research combines strong reasoning, mathematical performance, vision, file handling, and a 200K context window with tool and function calling. Its premium output pricing suits research-heavy work rather than routine volume.
Benchmark scores
Magenta = intelligence · Ink = technical/agentic · Cyan = content & long-context · Grey = community benchmarks. Data: Artificial Analysis, Hugging Face.
38.3 Intelligence Index·38.4 Coding Index·88.3 Math Index
How OpenAI: o3 Deep Research compares
OpenAI: o3 Deep Research ranks #69 of 420 AI models we track for overall intelligence, #88 of 193 for coding. Its 200K-token context window is larger than 58% of the models we list. At $10.00 per million input tokens it is cheaper than 4% of comparable models.
Dark bar = input · light bar = output, scaled to the priciest peer.
1M tokens ≈ 8 full-length novels or ~2,500 pages of business documents in a single request.
Strongest on business fit. The pulled-in value corner is the trade-off, and if the shape matters more than the price, this is your model.
Compare shapes side-by-side →Pricing
| Token Type | Cost per 1M tokens | Cost per 1K tokens |
|---|---|---|
| Input | $10.00 | $0.010000 |
| Output | $40.00 | $0.040000 |
What would OpenAI: o3 Deep Research cost your business?
Pick the job that looks most like yours, then fine-tune with the sliders. Estimates update live.
A website chatbot handling around 100 customer conversations a day, a few short messages each.
Full calculator with 688 models → Price Calculator
These numbers get smaller with the right architecture.
We route routine calls to cheap models and save OpenAI: o3 Deep Research for the hard ones. Most clients cut their estimate by 60-80%.
Talk to our teamAbout OpenAI: o3 Deep Research
o3-deep-research is OpenAI's advanced model for deep research, designed to tackle complex, multi-step research tasks. Note: This model always uses the 'web_search' tool which adds additional cost.
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Frequently asked questions about OpenAI: o3 Deep Research
How much does OpenAI: o3 Deep Research cost?
OpenAI: o3 Deep Research costs $10.00 per million input tokens and $40.00 per million output tokens.
What is the context window of OpenAI: o3 Deep Research?
OpenAI: o3 Deep Research has a context window of 200,000 tokens (200K).
Is OpenAI: o3 Deep Research good for coding?
On our coding benchmark index, OpenAI: o3 Deep Research ranks #88 of 193 models, placing it in the broader range of the field for code generation and debugging.
What can OpenAI: o3 Deep Research do?
OpenAI: o3 Deep Research supports image/vision input, tool use, and function calling.
Who created OpenAI: o3 Deep Research?
OpenAI: o3 Deep Research is developed by OpenAI and was released on October 10, 2025.
Data sourced from the OpenRouter API, Artificial Analysis, the Hugging Face Open LLM Leaderboard and our own internal testing. Scores are editorially curated by our team.
Last updated: August 10, 2026 8:38 pm