--- title: "DeepResearch vs deep-research" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/alibaba-nlp-deepresearch-vs-dzhng-deep-research" tools: ["alibaba-nlp-deepresearch", "dzhng-deep-research"] --- # DeepResearch vs deep-research Neutral, constraint-first comparison with live GitHub stats. | | [DeepResearch](/tools/alibaba-nlp-deepresearch.md) | [deep-research](/tools/dzhng-deep-research.md) | | --- | --- | --- | | Tagline | Tongyi Deep Research, the Leading Open-source Deep Research Agent | An AI-powered research assistant that performs iterative, deep research on any topic | | Stars | 19,621 | 19,312 | | Forks | 1,500 | 1,973 | | Open issues | 91 | 90 | | Language | Python | TypeScript | | 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 | Deep Research is an AI-powered research assistant that efficiently dives into any topic by leveraging search engines, web scraping, and large language models. It iteratively refines its research direction over time to go | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | LLM Frameworks, AI Agents | Data & Retrieval, AI Agents | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [DeepResearch](/tools/alibaba-nlp-deepresearch.md) | [deep-research](/tools/dzhng-deep-research.md) | | --- | --- | --- | | Maintenance | Slowing (36%) | Steady (60%) | | Days since push | 130d | 87d | | Open issues (now) | 91 | 90 | | Owner type | Organization | User | | Security scan | 104 low (104 low) | 39 low (39 low) | | Full report | [trust report](/tools/alibaba-nlp-deepresearch/trust.md) | [trust report](/tools/dzhng-deep-research/trust.md) | **Typed relationship:** DeepResearch _(alternative)_ deep-research Both are AI-powered research assistants that perform deep research on topics, differing in implementation and specific features. ## 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: deep-research - **Requirements:** Min 2 GB RAM; Requires Docker; Requires Node.js environment setup.; Needs specific API keys for third-party web search (Firecrawl) and language model services (OpenAI). - **Adopt for:** Deep Research is an AI-powered research assistant that efficiently dives into any topic by leveraging search engines, web scraping, and large language models. It iteratively refines its research direction over time to go ## Choose when ### Choose DeepResearch if… - DeepResearch is primarily Python; deep-research is TypeScript. - License: DeepResearch is Apache-2.0, deep-research is MIT. - 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 are AI-powered research assistants that perform deep research on topics, differing in implementation and specific features. - 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 deep-research if… - deep-research is primarily TypeScript; DeepResearch is Python. - License: deep-research is MIT, DeepResearch is Apache-2.0. - Requirements: Min 2 GB RAM; Requires Docker; Requires Node.js environment setup.; Needs specific API keys for third-party web search (Firecrawl) and language model services (OpenAI).. - Both are AI-powered research assistants that perform deep research on topics, differing in implementation and specific features. - Tags unique to deep-research: research, ai, o3-mini, gpt. - Also covers Data & Retrieval. - deep-research ships Docker support for self-hosted deployment. - You require a detailed and comprehensive report on a specific topic where traditional manual or less refined automated tools are too basic. ## 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 deep-research - If your project requires proprietary or classified data analysis because Deep Research relies on public web scraping and search engines, which limits access to non-public content. - You are looking for a tool that operates solely offline; since the tool needs internet access to perform its tasks through API calls to services like Firecrawl and OpenAI. ## Common questions ### What is the difference between DeepResearch and deep-research? DeepResearch: Tongyi Deep Research, the Leading Open-source Deep Research Agent. deep-research: An AI-powered research assistant that performs iterative, deep research on any topic. See the comparison table for live GitHub stats and shared categories. ### When should I choose DeepResearch over deep-research? Choose DeepResearch over deep-research when DeepResearch is primarily Python; deep-research is TypeScript; License: DeepResearch is Apache-2.0, deep-research is MIT; 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 are AI-powered research assistants that perform deep research on topics, differing in implementation and specific features; 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 deep-research over DeepResearch? Choose deep-research over DeepResearch when deep-research is primarily TypeScript; DeepResearch is Python; License: deep-research is MIT, DeepResearch is Apache-2.0; Requirements: Min 2 GB RAM; Requires Docker; Requires Node.js environment setup.; Needs specific API keys for third-party web search (Firecrawl) and language model services (OpenAI).; Both are AI-powered research assistants that perform deep research on topics, differing in implementation and specific features; Tags unique to deep-research: research, ai, o3-mini, gpt; Also covers Data & Retrieval; deep-research ships Docker support for self-hosted deployment; You require a detailed and comprehensive report on a specific topic where traditional manual or less refined automated tools are too basic. ### 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 deep-research? If your project requires proprietary or classified data analysis because Deep Research relies on public web scraping and search engines, which limits access to non-public content. You are looking for a tool that operates solely offline; since the tool needs internet access to perform its tasks through API calls to services like Firecrawl and OpenAI. ### Is DeepResearch or deep-research more popular on GitHub? DeepResearch has more GitHub stars (19,621 vs 19,312). Stars measure visibility, not whether either tool fits your constraints. ### Are DeepResearch and deep-research open source? Yes - both are open-source projects on GitHub (DeepResearch: Apache-2.0, deep-research: MIT). ### Where can I find alternatives to DeepResearch or deep-research? GraphCanon lists graph-backed alternatives at /tools/alibaba-nlp-deepresearch/alternatives and /tools/dzhng-deep-research/alternatives (/tools/alibaba-nlp-deepresearch/alternatives.md, /tools/dzhng-deep-research/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-dzhng-deep-research.md mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, DeepResearch or deep-research? DeepResearch: Slowing. deep-research: 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 DeepResearch and deep-research? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: DeepResearch: /tools/alibaba-nlp-deepresearch/trust; deep-research: /tools/dzhng-deep-research/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/_