OpenAI
platform.openai.com › docs › guides › deep-research
Deep research | OpenAI API
To use deep research, use the Responses API with the model set to o3-deep-research or o4-mini-deep-research. You must include at least one data source: web search, remote MCP servers, or file search with vector stores.
OpenAI Cookbook
cookbook.openai.com › examples › deep_research_api › introduction_to_deep_research_api
Introduction to deep research in the OpenAI API | OpenAI Cookbook
The Deep Research API enables you to automate complex research workflows that require reasoning, planning, and synthesis across real-world information.
Deep Research API Timeline
The deep research blog post is insane. Can we expect this model via an API-based offering anytime soon? chat.completions.create(model=“deep-research-02-15-2025”) has a nice ring to it. Thanks! More on community.openai.com
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December 28, 2024Plans for Deep Research tools and the API
Might as well be the first… Any hints/roadmaps in regards to tools like Deep Research for the API…I see this: In the future, you’ll be able to connect to more specialized data sources—expanding its access to subscription-based or internal resources—to make its output even more robust ... More on community.openai.com
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February 3, 2025I built a deep research agent with Perplexity API that works as well if not better than OpenAI's Deep Research
What is that one bench mark OpenAI used to showcase deep research? I believe they got around 30% which was much higher than whatever the previous top model was. If that benchmark is available, running yours on that would be a good way to see how yours stacks up. Ive tried perplexity api to help me choose which jobs to apply for. Basically, i have a list that gets updated daily. All i wanted it to do was take each job (containing title and company) that is newer than the previous maxDate and search for that specific job’s salary. Anything greater than $45 an hour gets compiled into a list for me. I found it would work for the first few jobs, then just completely stop processing and i would have to close the program. You experience anything like that while developing this? I was thinking it might be a rate limit, but the amount of jobs its processing is < 20 More on reddit.com
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October 16, 2024Does OpenAI API support the Deep Research model?
I’m now looking to build a similar capability into an automated workflow using the OpenAI API. Does the OpenAI API provide access to the same underlying model or capabilities used in the “Deep Research” feature in ChatGPT? If not, what are the limitations or reasons? More on community.openai.com
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May 23, 2025Videos
04:38
OpenAI Deep Research in 4 mins - YouTube
09:05
OpenAI Deep Research API - Financial App Integration - YouTube
19:43
How to Build Custom Deep Research Agents (Better than OpenAI) - ...
00:28
OpenAI New Deep Research API - YouTube
17:02
OpenAI’s Responses API: The Easiest Way to Build a RAG System?
13:29
Deep Research.....but Open Source - YouTube
OpenAI
openai.com › index › introducing-deep-research
Introducing deep research | OpenAI
API Platform(opens in a new window) OpenAI · February 2, 2025Release · Try on ChatGPT(opens in a new window) Loading… · Share · July 17, 2025 update: Deep research can now go even deeper and broader with access to a visual browser as part of ChatGPT agent.
OpenAI
platform.openai.com › docs › models › o3-deep-research
o3-deep-research Model | OpenAI API
Explore developer resources, tutorials, API docs, and dynamic examples to get the most out of OpenAI's platform.
Medium
cobusgreyling.medium.com › openai-api-deep-research-17ceca9a9a51
OpenAI API Deep Research. With the introduction of the OpenAI API… | by Cobus Greyling | Medium
July 11, 2025 - The architecture of the API is very much modelled on ChatGPT, but there is the omission of the disambiguation query which developers then are free to omit or customise. This setup gives developers full control over how research tasks are framed, but also places greater responsibility on the quality of the input prompt. ... ChatGPT is the friendly face of OpenAI’s tech — a web or app interface where you type a question and get an instant response.
Simon Willison
til.simonwillison.net › llms › o4-mini-deep-research
Exploring OpenAI's deep research API model o4-mini-deep-research | Simon Willison’s TILs
October 18, 2025 - o4-mini-deep-research is significantly cheaper than o3-deep-research - $2/$8 per million for input/output compared to $10/$40 - so I tried that one. These models are only available via the Responses API and recommend running using their "background" mode. My LLM tooling doesn't support that yet so I used curl instead. ... curl https://api.openai.com/v1/responses \ -H "Authorization: Bearer $(llm keys get openai)" \ -H "Content-Type: application/json" \ -d '{ "model": "o4-mini-deep-research-2025-06-26", "input": "Find locations of every surviving orchestrion in the world.
Apidog
apidog.com › blog › openai-deep-research-api
A Developer's Guide to the OpenAI Deep Research API
3 weeks ago - What if you could automate this entire workflow? OpenAI's Deep Research API is a significant step in that direction, offering a powerful tool to transform high-level questions into structured, citation-rich reports.
OpenAI Cookbook
cookbook.openai.com › examples › deep_research_api › introduction_to_deep_research_api_agents
Deep Research API with the Agents SDK | OpenAI Cookbook
June 25, 2025 - This cookbook demonstrates how to build Agentic research workflows using the OpenAI Deep Research API and the OpenAI Agents SDK. It is a...
OpenAI Developer Community
community.openai.com › api
Deep Research API Timeline - API - OpenAI Developer Community
The deep research blog post is insane. Can we expect this model via an API-based offering anytime soon? chat.completions.create(model=“deep-research-02-15-2025”) has a nice ring to it. Thanks!
Published December 28, 2024
OpenAI Developer Community
community.openai.com › api
Plans for Deep Research tools and the API - API - OpenAI Developer Community
February 3, 2025 - Might as well be the first… Any hints/roadmaps in regards to tools like Deep Research for the API…I see this: In the future, you’ll be able to connect to more specialized data sources—expanding its access to subscription-based or internal resources—to make its output even more robust ...
Datos.gob.es
datos.gob.es › en › blog › rag-retrieval-augmented-generation-key-unlocks-door-precision-language-models
RAG - Retrieval Augmented Generation: The key that unlocks the door to precision language models | datos.gob.es
OpenAI. OpenAI is the best known platform for LLM models and conversational interfaces. The creators of ChatGTP provide the developer community with a set of libraries to use the OpenAI API to create their own applications using the GPT-3.5 ...
Reddit
reddit.com › r/perplexity_ai › i built a deep research agent with perplexity api that works as well if not better than openai's deep research
r/perplexity_ai on Reddit: I built a deep research agent with Perplexity API that works as well if not better than OpenAI's Deep Research
October 16, 2024 -
So as we all know OpenAI's Deep Research is being talked about everywhere. The same goes with the company that I work for, everyone wanted to try it. They finally tried it the other day, and got a report of around 26 pages about a very specific subject and the quality was ok. But when I saw the structure it hit me: it was clearly a bunch of separate search queries stiched together and rewritten by their model. So why couldn't we just make it ourselves? So I built the agentic workflow that you see in the image in AI Workflow Automation plugin in WordPress which has integration with Perplexity api.
Basically this is how it works: a research query comes in, it gets sent to several different research nodes, each running Sonar Pro, and each one research the topic from a different angle, then each research node passes on the results to an AI node, for which I used Grok 2 because of the large output context window and good writing skills, and then all of them come together to create a unified research report.
I could generate a well cited and factual report of around 5000 to 6000 words in around 7 minutes, which in terms of quality was really on par with the OpenAI one. And the best thing about it: it cost less than 30 cents to run the whole thing!! You can see it in the second image.
And no, I didn't benchmark it against some standard benchmark, it was my own qualitative review of the result.
So yes, you can make your own agents, and I love Perplexity's Sonar Pro and Sonar Reasoning for this use case, especially that now you can limit the time window of the search and limit the search context. It's amazing.
You should be able to get similar results with a workflow built in a tool like N8N if you don't use AI Workflow Automation.
If you do use the plugin and you want the workflow, send me a dm and I'd be happy to share it with you!
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What is that one bench mark OpenAI used to showcase deep research? I believe they got around 30% which was much higher than whatever the previous top model was. If that benchmark is available, running yours on that would be a good way to see how yours stacks up. Ive tried perplexity api to help me choose which jobs to apply for. Basically, i have a list that gets updated daily. All i wanted it to do was take each job (containing title and company) that is newer than the previous maxDate and search for that specific job’s salary. Anything greater than $45 an hour gets compiled into a list for me. I found it would work for the first few jobs, then just completely stop processing and i would have to close the program. You experience anything like that while developing this? I was thinking it might be a rate limit, but the amount of jobs its processing is < 20
2 of 5
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if not n8n, which tool is it?
OpenAI Help Center
help.openai.com › en › articles › 10500283-deep-research-faq
Deep Research | OpenAI Help Center
To start a Deep Research task, select Deep research from the tools menu. Describe the task you want completed, and Deep Research will begin working. It may prompt you to confirm details before starting.
UPV
polipapers.upv.es › index.php › jclr › article › view › 20408
Self-supervision of Hallucinations in Large Language Models: LLteaM | Journal of Computer-Assisted Linguistic Research
December 12, 2023 - https://api.openai.com/v1
OpenAI Developer Community
community.openai.com › api
Does OpenAI API support the Deep Research model? - API - OpenAI Developer Community
May 23, 2025 - I’ve been using the “Deep Research” feature in ChatGPT and find it incredibly powerful for synthesizing complex information and extracting insights from long or technical documents. I’m now looking to build a similar capability into an automated workflow using the OpenAI API.
Microsoft Azure
azure.microsoft.com › blog home › ai + machine learning › introducing deep research in azure ai foundry agent service
Introducing Deep Research in Azure AI Foundry Agent Service | Microsoft Azure Blog
July 7, 2025 - Today we’re excited to announce the public preview of Deep Research in Azure AI Foundry—an API and software development kit (SDK)-based offering of OpenAI’s advanced agentic research capability, fully integrated with Azure’s enterprise-grade agentic platform.
TechCrunch
techcrunch.com › home › why openai isn’t bringing deep research to its api just yet
Why OpenAI isn't bringing deep research to its API just yet | TechCrunch
February 26, 2025 - OpenAI says that it won’t bring the AI model powering deep research, its in-depth research tool, to its developer API while it figures out how to better assess the risks of AI convincing people to act on or change their beliefs.
Reddit
reddit.com › r/llmdevs › openai deep research api
r/LLMDevs on Reddit: Openai Deep Research API
August 23, 2025 -
Has anyone been able to put the deep research via api to any good use. I am finding it extremely hard to steer this model, plus it keeps defaulting to it’s knowledge cutoff timeline to make all research plans, even if I have provided with all tools and information.
Another issue is that it keeps defaulting to web search when the mcp tools I have provided would provide much better data for certain tasks.
No amount of prompting helps. Anyone figured out how to make it follow a plan?