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使用推理合成大量在线信息并为您完成多步骤研究任务的代理。今天适用于Pro用户，接下来是Plus和Team。
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Today we’re launching deep research in ChatGPT, a new agentic capability that conducts multi-step research on the internet for complex tasks. It accomplishes in tens of minutes what would take a human many hours.
今天，我们将在ChatGPT进行深入研究，这是一种新的代理能力，可以在互联网上对复杂任务进行多步骤研究。它在几十分钟内完成了人类需要数小时才能完成的任务。
Deep research is OpenAI's next agent that can do work for you independently—you give it a prompt, and ChatGPT will find, analyze, and synthesize hundreds of online sources to create a comprehensive report at the level of a research analyst. Powered by a version of the upcoming OpenAI o3 model that’s optimized for web browsing and data analysis, it leverages reasoning to search, interpret, and analyze massive amounts of text, images, and PDFs on the internet, pivoting as needed in reaction to information it encounters.
深度研究是OpenAI下一个可以独立为你工作的代理——你给它一个提示，ChatGPT将找到、分析和综合数百个在线资源，以创建一份研究分析师级别的综合报告。它由即将推出的OpenAI o3模型的一个版本提供支持，该模型针对网页浏览和数据分析进行了优化，利用推理来搜索、解释和分析互联网上的大量文本、图像和PDF，根据需要根据遇到的信息进行旋转。
The ability to synthesize knowledge is a prerequisite for creating new knowledge. For this reason, deep research marks a significant step toward our broader goal of developing AGI, which we have long envisioned as capable of producing novel scientific research.
综合知识的能力是创造新知识的先决条件。因此，深入研究标志着我们朝着发展AGI的更广泛目标迈出了重要的一步，我们长期以来一直认为AGI能够产生新的科学研究。
Why we built deep research 为什么我们建立了深入的研究
Deep research is built for people who do intensive knowledge work in areas like finance, science, policy, and engineering and need thorough, precise, and reliable research. It can be equally useful for discerning shoppers looking for hyper-personalized recommendations on purchases that typically require careful research, like cars, appliances, and furniture. Every output is fully documented, with clear citations and a summary of its thinking, making it easy to reference and verify the information. It is particularly effective at finding niche, non-intuitive information that would require browsing numerous websites. Deep research frees up valuable time by allowing you to offload and expedite complex, time-intensive web research with just one query.
深度研究是为那些在金融、科学、政策和工程等领域进行深入知识工作并需要彻底、精确和可靠研究的人而建立的。它同样适用于寻找超个性化购买建议的挑剔购物者，这些建议通常需要仔细研究，如汽车、家电和家具。每个输出都有完整的记录，有清晰的引用和思考摘要，使其易于参考和验证信息。它特别有效地找到需要浏览多个网站的利基、非直观信息。深度研究通过允许您仅通过一个查询卸载和加速复杂、耗时的网络研究，释放了宝贵的时间。
Deep research independently discovers, reasons about, and consolidates insights from across the web. To accomplish this, it was trained on real-world tasks requiring browser and Python tool use, using the same reinforcement learning methods behind OpenAI o1, our first reasoning model. While o1 demonstrates impressive capabilities in coding, math, and other technical domains, many real-world challenges demand extensive context and information gathering from diverse online sources. Deep research builds on these reasoning capabilities to bridge that gap, allowing it to take on the types of problems people face in work and everyday life.
深度研究独立地发现、推理和整合来自网络的见解。为了实现这一目标，它接受了需要浏览器和Python工具使用的现实任务的训练，使用了我们第一个推理模型OpenAI o1背后的强化学习方法。虽然o1在编码、数学和其他技术领域展示了令人印象深刻的能力，但许多现实世界的挑战需要从不同的在线来源收集广泛的背景和信息。深度研究建立在这些推理能力的基础上，以弥合这一差距，使其能够处理人们在工作和日常生活中面临的问题类型。
How to use deep research 如何使用深度研究
In ChatGPT, select ‘deep research’ in the message composer and enter your query. Tell ChatGPT what you need—whether it’s a competitive analysis on streaming platforms or a personalized report on the best commuter bike. You can attach files or spreadsheets to add context to your question. Once it starts running, a sidebar appears with a summary of the steps taken and sources used.
在ChatGPT中，在消息编辑器中选择“深度研究”，然后输入您的查询。告诉ChatGPT您需要什么——无论是流媒体平台上的竞争分析，还是关于最佳通勤自行车的个性化报告。您可以附加文件或电子表格来为您的问题添加上下文。一旦开始运行，就会出现一个侧边栏，其中总结了所采取的步骤和使用的来源。
Deep research may take anywhere from 5 to 30 minutes to complete its work, taking the time needed to dive deep into the web. In the meantime, you can step away or work on other tasks—you’ll get a notification once the research is complete. The final output arrives as a report within the chat – in the next few weeks, we will also be adding embedded images, data visualizations, and other analytic outputs in these reports for additional clarity and context.
深度研究可能需要5到30分钟才能完成工作，这需要深入研究网络所需的时间。与此同时，您可以离开或处理其他任务-一旦研究完成，您将收到通知。最终输出将以报告的形式出现在聊天中-在接下来的几周内，我们还将在这些报告中添加嵌入式图像、数据可视化和其他分析输出，以增加清晰度和上下文。
Compared to deep research, GPT-4o is ideal for real-time, multimodal conversations. For multi-faceted, domain-specific inquiries where depth and detail are critical, deep research’s ability to conduct extensive exploration and cite each claim is the difference between a quick summary and a well-documented, verified answer that can be usable as a work product.
与深度研究相比，GPT-4o非常适合实时、多模态对话。对于深度和细节至关重要的多方面、特定领域的查询，深度研究进行广泛探索和引用每个声明的能力是快速摘要和可作为工作产品使用的有据可查的答案之间的区别。
How it works 它是如何工作的
Deep research was trained using end-to-end reinforcement learning on hard browsing and reasoning tasks across a range of domains. Through that training, it learned to plan and execute a multi-step trajectory to find the data it needs, backtracking and reacting to real-time information where necessary. The model is also able to browse over user uploaded files, plot and iterate on graphs using the python tool, embed both generated graphs and images from websites in its responses, and cite specific sentences or passages from its sources. As a result of this training, it reaches new highs on a number of public evaluations focused on real-world problems.
深度研究是通过端到端强化学习在一系列领域的硬浏览和推理任务上进行训练的。通过这种训练，它学会了规划和执行多步轨迹，以找到所需的数据，在必要时回溯并对实时信息做出反应。该模型还能够浏览用户上传的文件，使用python工具绘制和迭代图形，在其响应中嵌入从网站生成的图形和图像，并引用其来源的特定句子或段落。由于这种训练，它在许多关注现实世界问题的公共评估中达到了新高。
Humanity's Last Exam 人类的最后一次考试
On Humanity’s Last Exam(opens in a new window), a recently released evaluation that tests AI across a broad range of subjects on expert-level questions, the model powering deep research scores a new high at 26.6% accuracy. This test consists of over 3,000 multiple choice and short answer questions across more than 100 subjects from linguistics to rocket science, classics to ecology. Compared to OpenAI o1, the largest gains appeared in chemistry, humanities and social sciences, and mathematics. The model powering deep research showcased a human-like approach by effectively seeking out specialized information when necessary.
在最近发布的人类最后一次考试（在新窗口中打开）评估中，该模型在专家级别的问题上测试了广泛学科的AI，并以26.6%的准确率获得了新的高度。该测试包括超过3,000个选择题和简短答案问题，涵盖了从语言学到火箭科学，从经典到生态学的100多个学科。与OpenAI o1相比，最大的收益出现在化学，人文社会科学和数学方面。该模型通过在必要时有效地寻找专业信息，展示了一种类似人类的方法。
点击图片可查看完整电子表格
*Model is not multi-modal, evaluated on text-only subset.
**with browsing + python tools
GAIA
On GAIA(opens in a new window)(1), a public benchmark that evaluates AI on real-world questions, the model powering deep research reaches a new state of the art (SOTA), topping the external leaderboard(opens in a new window). Encompassing questions across three levels of difficulty, successful completion of these tasks requires abilities including reasoning, multi-modal fluency, web browsing, and tool-use proficiency.
在GAIA（在新窗口中打开）（1）上，这是一个评估现实世界问题AI的公共基准，推动深入研究的模型达到了新的最先进水平（SOTA），位居外部排行榜榜首（在新窗口中打开）。包含三个难度级别的问题，成功完成这些任务需要包括推理、多模态流畅性、网页浏览和工具使用熟练度在内的能力。
点击图片可查看完整电子表格
Expert-Level Tasks 专家级任务
In an internal evaluation of expert-level tasks across a range of areas, deep research was rated by domain experts to have automated multiple hours of difficult, manual investigation.
在对多个领域的专家级任务进行内部评估时，领域专家认为深度研究具有自动化多小时的困难手动调查能力。
Limitations 限制
Deep research unlocks significant new capabilities, but it’s still early and has limitations. It can sometimes hallucinate facts in responses or make incorrect inferences, though at a notably lower rate than existing ChatGPT models, according to internal evaluations. It may struggle with distinguishing authoritative information from rumors, and currently shows weakness in confidence calibration, often failing to convey uncertainty accurately. At launch, there may be minor formatting errors in reports and citations, and tasks may take longer to kick off. We expect all these issues to quickly improve with more usage and time.
深度研究解锁了重要的新功能，但仍处于早期阶段，存在局限性。根据内部评估，它有时会在回答中产生幻觉或做出错误的推断，尽管速度明显低于现有的ChatGPT模型。它可能难以区分权威信息和谣言，目前在信心校准方面表现出弱点，通常无法准确传达不确定性。在发布时，报告和引用中可能存在轻微的格式错误，任务可能需要更长时间才能启动。我们预计所有这些问题将随着更多的使用和时间而迅速改善。
Access 访问
Deep research in ChatGPT is currently very compute intensive. The longer it takes to research a query, the more inference compute is required. We are starting with a version optimized for Pro users today, with up to 100 queries per month. Plus and Team users will get access next, followed by Enterprise. We are still working on bringing access to users in the United Kingdom, Switzerland, and the European Economic Area.
ChatGPT的深度研究目前非常需要计算。研究查询所需的时间越长，需要的推理计算就越多。我们从今天针对专业用户优化的版本开始，每月最多可访问100个查询。接下来是Plus和Team用户，其次是Enterprise。我们仍在努力为英国、瑞士和欧洲经济区的用户提供访问权限。
All paid users will soon get significantly higher rate limits when we release a faster, more cost-effective version of deep research powered by a smaller model that still provides high quality results.
当我们发布一个更快、更具成本效益的深度研究版本时，所有付费用户将很快获得更高的速率限制，该版本由一个更小的模型提供支持，该模型仍然提供高质量的结果。
In the coming weeks and months, we’ll be working on the technical infrastructure, closely monitoring the current release, and conducting even more rigorous testing. This aligns with our principle of iterative deployment. If all safety checks continue to meet our release standards, we anticipate releasing deep research to Plus users in about a month.
在接下来的几周和几个月里，我们将致力于技术基础设施，密切监控当前版本，并进行更严格的测试。这符合我们迭代部署的原则。如果所有安全检查继续符合我们的发布标准，我们预计将在大约一个月内向Plus用户发布深入研究。
What's next 下一步是什么
Deep research is available today on ChatGPT web, and will be rolled out to mobile and desktop apps within the month. Currently, deep research can access the open web and any uploaded files. 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 and personalized.
深度研究今天可以在ChatGPT网站上使用，并将在一个月内推广到移动和桌面应用程序。目前，深度研究可以访问开放的网络和任何上传的文件。将来，你将能够连接到更专业的数据源——扩大其对基于订阅或内部资源的访问——使其输出更加健壮和个性化。
Looking further ahead, we envision agentic experiences coming together in ChatGPT for asynchronous, real-world research and execution. The combination of deep research, which can perform asynchronous online investigation, and Operator, which can take real-world action, will enable ChatGPT to carry out increasingly sophisticated tasks for you.
展望未来，我们设想真实的体验将在ChatGPT中汇聚在一起，进行异步的现实世界研究和执行。可以执行异步在线调查的深度研究和可以采取现实世界行动的操作员的结合将使ChatGPT能够为您执行越来越复杂的任务。
Update on February 5, 2025: Deep research is now available to Pro users in the United Kingdom, Switzerland, and the European Economic Area.
2025年2月5日更新：英国、瑞士和欧洲经济区的专业用户现在可以进行深度研究。
Update on February 3, 2025: We conducted rigorous safety testing, preparedness evaluations, and governance reviews on the early version of o3 that powers deep research, identifying it as Medium(opens in a new window) risk. We also ran additional safety testing to better understand incremental risks associated with deep research's ability to browse the web, and we have added new mitigations. We will continue to thoroughly test and closely monitor the current limited release. We will share our safety insights and safeguards for deep research in a system card when we widen access to Plus users.
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