--- title: "gpt-researcher vs autogen" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/assafelovic-gpt-researcher-vs-microsoft-autogen" tools: ["assafelovic-gpt-researcher", "microsoft-autogen"] --- # gpt-researcher vs autogen Neutral, constraint-first comparison with live GitHub stats. | | [gpt-researcher](/tools/assafelovic-gpt-researcher.md) | [autogen](/tools/microsoft-autogen.md) | | --- | --- | --- | | Tagline | An autonomous agent that conducts deep research on any data using any LLM providers | A framework for creating multi-agent AI applications | | Stars | 28,146 | 59,573 | | Forks | 3,803 | 8,967 | | Open issues | 210 | 930 | | Language | Python | Python | | Adopt for | GPT Researcher is an open-source deep research agent that conducts thorough and unbiased web or local document analysis, producing comprehensive reports with inline images and detailed citations. It uses a 'planner' and | AutoGen is a framework for developing multi-agent AI applications that can act autonomously or alongside humans. It's currently in maintenance mode with no additional features planned and users are encouraged to migrate. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | CC-BY-4.0 | | Categories | AI Agents | AI Agents, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [gpt-researcher](/tools/assafelovic-gpt-researcher.md) | [autogen](/tools/microsoft-autogen.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Steady (60%) | | Days since push | 2d | 83d | | Open issues (now) | 210 | 930 | | Owner type | User | Organization | | Security scan | 62 low (62 low) | No lockfile | | Full report | [trust report](/tools/assafelovic-gpt-researcher/trust.md) | [trust report](/tools/microsoft-autogen/trust.md) | **Typed relationship:** gpt-researcher _(alternative)_ autogen autogen is a framework for creating multi-agent AI applications, comparable to GPT Researcher's function of conducting deep research using agents with LLM capabilities. ## Shared compatibility - **Node.js**: [gpt-researcher](/tools/assafelovic-gpt-researcher.md) - Node.js runtime; [autogen](/tools/microsoft-autogen.md) - Node.js runtime ## Decision facts: gpt-researcher - **Requirements:** Min 4 GB RAM; - A Python environment needs to be set up.; - Google Gemini (Nano Banana) integration for AI-generated images requires specific setup and keys. - **Adopt for:** GPT Researcher is an open-source deep research agent that conducts thorough and unbiased web or local document analysis, producing comprehensive reports with inline images and detailed citations. It uses a 'planner' and - **License detail:** Apache-2.0 ## Decision facts: autogen - **Requirements:** AutoGen requires Python 3.10 or later. - **Adopt for:** AutoGen is a framework for developing multi-agent AI applications that can act autonomously or alongside humans. It's currently in maintenance mode with no additional features planned and users are encouraged to migrate. ## Choose when ### Choose gpt-researcher if… - License: gpt-researcher is Apache-2.0, autogen is CC-BY-4.0. - Requirements: Min 4 GB RAM; - A Python environment needs to be set up.; - Google Gemini (Nano Banana) integration for AI-generated images requires specific setup and keys.. - autogen is a framework for creating multi-agent AI applications, comparable to GPT Researcher's function of conducting deep research using agents with LLM capabilities. - Tags unique to gpt-researcher: llms, deepresearch, python, automation. - gpt-researcher ships Docker support for self-hosted deployment. - - You need to generate objective and detailed research reports beyond 2,000 words using both web sources and local documents. ### Choose autogen if… - License: autogen is CC-BY-4.0, gpt-researcher is Apache-2.0. - Requirements: AutoGen requires Python 3.10 or later.. - autogen is a framework for creating multi-agent AI applications, comparable to GPT Researcher's function of conducting deep research using agents with LLM capabilities. - Tags unique to autogen: autogen, agents, agentic, framework. - Also covers LLM Frameworks. - You should use AutoGen if you have an existing project built on it and desire to maintain its current functionality without introducing advanced enterprise features or extensive new capabilities. ## When NOT to use gpt-researcher - - Your project requires real-time or interactive research with immediate feedback, as GPT Researcher focuses on in-depth analysis rather than quick responses. - - You are working within a restricted network environment where web scraping is not permitted, since the tool relies heavily on online sources for data gathering. ## When NOT to use autogen - Do not use AutoGen if you are planning to build a production-ready application that requires long-term support, enterprise-grade orchestration features, or multi-provider model support. - Avoid using this tool if your project needs future-proof development with new and continuous enhancements as the framework is in maintenance mode. ## Common questions ### What is the difference between gpt-researcher and autogen? gpt-researcher: An autonomous agent that conducts deep research on any data using any LLM providers. autogen: A framework for creating multi-agent AI applications. See the comparison table for live GitHub stats and shared categories. ### When should I choose gpt-researcher over autogen? Choose gpt-researcher over autogen when License: gpt-researcher is Apache-2.0, autogen is CC-BY-4.0; Requirements: Min 4 GB RAM; - A Python environment needs to be set up.; - Google Gemini (Nano Banana) integration for AI-generated images requires specific setup and keys.; autogen is a framework for creating multi-agent AI applications, comparable to GPT Researcher's function of conducting deep research using agents with LLM capabilities; Tags unique to gpt-researcher: llms, deepresearch, python, automation; gpt-researcher ships Docker support for self-hosted deployment; - You need to generate objective and detailed research reports beyond 2,000 words using both web sources and local documents. ### When should I choose autogen over gpt-researcher? Choose autogen over gpt-researcher when License: autogen is CC-BY-4.0, gpt-researcher is Apache-2.0; Requirements: AutoGen requires Python 3.10 or later.; autogen is a framework for creating multi-agent AI applications, comparable to GPT Researcher's function of conducting deep research using agents with LLM capabilities; Tags unique to autogen: autogen, agents, agentic, framework; Also covers LLM Frameworks; You should use AutoGen if you have an existing project built on it and desire to maintain its current functionality without introducing advanced enterprise features or extensive new capabilities. ### When should I avoid gpt-researcher? - Your project requires real-time or interactive research with immediate feedback, as GPT Researcher focuses on in-depth analysis rather than quick responses. - You are working within a restricted network environment where web scraping is not permitted, since the tool relies heavily on online sources for data gathering. ### When should I avoid autogen? Do not use AutoGen if you are planning to build a production-ready application that requires long-term support, enterprise-grade orchestration features, or multi-provider model support. Avoid using this tool if your project needs future-proof development with new and continuous enhancements as the framework is in maintenance mode. ### Is gpt-researcher or autogen more popular on GitHub? autogen has more GitHub stars (59,573 vs 28,146). Stars measure visibility, not whether either tool fits your constraints. ### Are gpt-researcher and autogen open source? Yes - both are open-source projects on GitHub (gpt-researcher: Apache-2.0, autogen: CC-BY-4.0). ### Where can I find alternatives to gpt-researcher or autogen? GraphCanon lists graph-backed alternatives at /tools/assafelovic-gpt-researcher/alternatives and /tools/microsoft-autogen/alternatives (/tools/assafelovic-gpt-researcher/alternatives.md, /tools/microsoft-autogen/alternatives.md), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at /compare/assafelovic-gpt-researcher-vs-microsoft-autogen.md mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, gpt-researcher or autogen? gpt-researcher: Very active. autogen: Steady. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for gpt-researcher and autogen? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: gpt-researcher: /tools/assafelovic-gpt-researcher/trust; autogen: /tools/microsoft-autogen/trust. --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=assafelovic-gpt-researcher`](/api/graphcanon/graph?tool=assafelovic-gpt-researcher) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_