--- title: "DeepResearch vs gpt-researcher" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/alibaba-nlp-deepresearch-vs-assafelovic-gpt-researcher" tools: ["alibaba-nlp-deepresearch", "assafelovic-gpt-researcher"] --- # DeepResearch vs gpt-researcher Neutral, constraint-first comparison with live GitHub stats. | | [DeepResearch](/tools/alibaba-nlp-deepresearch.md) | [gpt-researcher](/tools/assafelovic-gpt-researcher.md) | | --- | --- | --- | | Tagline | Tongyi Deep Research, the Leading Open-source Deep Research Agent | An autonomous agent that conducts deep research on any data using any LLM providers | | Stars | 19,621 | 28,146 | | Forks | 1,500 | 3,803 | | Open issues | 91 | 210 | | Language | Python | Python | | Adopt for | DeepResearch is an agentic large language model designed with a focus on long-horizon, deep information-seeking tasks, making it particularly suitable for users needing advanced search capabilities. It comes with 30.5B+3 | 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 | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | LLM Frameworks, AI Agents | AI Agents | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [DeepResearch](/tools/alibaba-nlp-deepresearch.md) | [gpt-researcher](/tools/assafelovic-gpt-researcher.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Very active (96%) | | Days since push | 130d | 2d | | Open issues (now) | 91 | 210 | | Owner type | Organization | User | | Security scan | 104 low (104 low) | 62 low (62 low) | | Full report | [trust report](/tools/alibaba-nlp-deepresearch/trust.md) | [trust report](/tools/assafelovic-gpt-researcher/trust.md) | **Typed relationship:** DeepResearch _(alternative)_ gpt-researcher Both tools conduct deep research using LLMs, but they may use different LLM providers or offer unique functionalities. ## Decision facts: DeepResearch - **Pricing:** unknown - No specific pricing info provided; deployment could vary depending on your cloud service provider or if you self-host on local servers. - **Requirements:** Min 16 GB RAM; Requires substantial computational resources due to its size and complexity.; Recommended for users with access to robust hardware infrastructure, either through cloud services like Aliyun's Bailian or local deployment. - **Adopt for:** DeepResearch is an agentic large language model designed with a focus on long-horizon, deep information-seeking tasks, making it particularly suitable for users needing advanced search capabilities. It comes with 30.5B+3 ## 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 ## Choose when ### Choose DeepResearch if… - Pricing: No specific pricing info provided; deployment could vary depending on your cloud service provider or if you self-host on local servers.. - Requirements: Min 16 GB RAM; Requires substantial computational resources due to its size and complexity.; Recommended for users with access to robust hardware infrastructure, either through cloud services like Aliyun's Bailian or local deployment.. - Both tools conduct deep research using LLMs, but they may use different LLM providers or offer unique functionalities. - Tags unique to DeepResearch: llm, artificial-intelligence, alibaba, deep-research. - Also covers LLM Frameworks. - When you need to perform sophisticated long-term horizon tasks that require in-depth information seeking. ### Choose gpt-researcher if… - 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.. - Both tools conduct deep research using LLMs, but they may use different LLM providers or offer unique functionalities. - Tags unique to gpt-researcher: llms, deepresearch, ai, python. - 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 NOT to use DeepResearch - Avoid using it for tasks requiring quick responses as it might suffer from slower response times due to its complex architecture designed for deep information-seeking. - Not suitable for less demanding or simpler tasks where smaller and more efficient models can perform adequately without the overhead of DeepResearch's extensive capability. ## 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. ## Common questions ### What is the difference between DeepResearch and gpt-researcher? DeepResearch: Tongyi Deep Research, the Leading Open-source Deep Research Agent. gpt-researcher: An autonomous agent that conducts deep research on any data using any LLM providers. See the comparison table for live GitHub stats and shared categories. ### When should I choose DeepResearch over gpt-researcher? Choose DeepResearch over gpt-researcher when Pricing: No specific pricing info provided; deployment could vary depending on your cloud service provider or if you self-host on local servers.; Requirements: Min 16 GB RAM; Requires substantial computational resources due to its size and complexity.; Recommended for users with access to robust hardware infrastructure, either through cloud services like Aliyun's Bailian or local deployment.; Both tools conduct deep research using LLMs, but they may use different LLM providers or offer unique functionalities; Tags unique to DeepResearch: llm, artificial-intelligence, alibaba, deep-research; Also covers LLM Frameworks; When you need to perform sophisticated long-term horizon tasks that require in-depth information seeking. ### When should I choose gpt-researcher over DeepResearch? Choose gpt-researcher over DeepResearch when 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.; Both tools conduct deep research using LLMs, but they may use different LLM providers or offer unique functionalities; Tags unique to gpt-researcher: llms, deepresearch, ai, python; 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 avoid DeepResearch? Avoid using it for tasks requiring quick responses as it might suffer from slower response times due to its complex architecture designed for deep information-seeking. Not suitable for less demanding or simpler tasks where smaller and more efficient models can perform adequately without the overhead of DeepResearch's extensive capability. ### 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. ### Is DeepResearch or gpt-researcher more popular on GitHub? gpt-researcher has more GitHub stars (28,146 vs 19,621). Stars measure visibility, not whether either tool fits your constraints. ### Are DeepResearch and gpt-researcher open source? Yes - both are open-source projects on GitHub (DeepResearch: Apache-2.0, gpt-researcher: Apache-2.0). ### Where can I find alternatives to DeepResearch or gpt-researcher? GraphCanon lists graph-backed alternatives at /tools/alibaba-nlp-deepresearch/alternatives and /tools/assafelovic-gpt-researcher/alternatives (/tools/alibaba-nlp-deepresearch/alternatives.md, /tools/assafelovic-gpt-researcher/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/alibaba-nlp-deepresearch-vs-assafelovic-gpt-researcher.md mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, DeepResearch or gpt-researcher? DeepResearch: Slowing. gpt-researcher: Very active. 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 DeepResearch and gpt-researcher? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: DeepResearch: /tools/alibaba-nlp-deepresearch/trust; gpt-researcher: /tools/assafelovic-gpt-researcher/trust. --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=alibaba-nlp-deepresearch`](/api/graphcanon/graph?tool=alibaba-nlp-deepresearch) - 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/_