Comparison
gpt-researcher vs deep-research
Verdict
Both gpt-researcher and deep-research are open-source AI development tools designed for conducting in-depth research using language models and other technologies. gpt-researcher, written in Python, supports a variety of language model providers and can be deployed as a Docker container or a Claude Skill. deep-research, on the other hand, operates in a TypeScript environment with Node.js and uses a.
Markdown twin · gpt-researcher alternatives · deep-research alternatives
GraphCanon updated Sep 20, 2026
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Trust & integrity
| Signal | gpt-researcher | deep-research |
|---|---|---|
| Maintenance | Active (11d since push) As of Sep 8, 2026 · github_public_v1 | Slowing (129d since push) As of Aug 19, 2026 · github_public_v1 |
| Provenance | Not a fork · Personal account As of Sep 8, 2026 · github_public_v1 | Not a fork · Personal account As of Aug 19, 2026 · github_public_v1 |
| OSV dependency advisories | Published findings As of Jul 11, 2026 · osv@v1 | Published findings As of Jul 11, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- gpt-researcher
- An autonomous agent that conducts deep research using LLM providers
- deep-research
- An AI-powered research assistant that refines its topic focus over time using search engines, web scraping, and large language models.
Stars
- gpt-researcher
- 29k
- deep-research
- 20k
Forks
- gpt-researcher
- 4.0k
- deep-research
- 2.0k
Open issues
- gpt-researcher
- 76
- deep-research
- 93
Language
- gpt-researcher
- Python
- deep-research
- TypeScript
Adopt for
- gpt-researcher
- gpt-researcher is an autonomous agent that uses Language Model Providers to conduct deep research automatically, supporting various installation methods including Docker and deployment as a Claude Skill.
- deep-research
- Deep-research is an AI-powered research assistant that leverages search engines, web scraping, and large language models to conduct iterative and in-depth exploration of topics.
Persona
- gpt-researcher
- -
- deep-research
- -
Runtime
- gpt-researcher
- -
- deep-research
- -
License
- gpt-researcher
- Apache-2.0
- deep-research
- MIT
Last pushed
- gpt-researcher
- Aug 27, 2026
- deep-research
- Apr 11, 2026
Categories
- gpt-researcher
- AI Agents, Data & Retrieval
- deep-research
- AI Agents, Data & Retrieval
Trust and health
Maintenance
- gpt-researcher
- Active (82%)
- deep-research
- Slowing (36%)
Days since push
- gpt-researcher
- 11d
- deep-research
- 129d
Open issues (now)
- gpt-researcher
- 76
- deep-research
- 93
Stars delta
- gpt-researcher
- +460 (30d)
- deep-research
- +195 (30d)
Open issues delta
- gpt-researcher
- -116 (30d)
- deep-research
- +3 (30d)
Full report
- gpt-researcher
- Trust report
- deep-research
- Trust report
Typed relationship
gpt-researcher alternative deep-researchBoth tools aim to conduct deep research using AI, with the primary difference being their implementation approaches.
Shared compatibility
- Node.js · gpt-researcher: Node.js runtime · deep-research: Node.js runtime
- OpenAI API · gpt-researcher: OpenAI API · deep-research: OpenAI API
Choose gpt-researcher if…
- gpt-researcher is primarily Python; deep-research is TypeScript.
- License: gpt-researcher is Apache-2.0, deep-research is MIT.
- Pricing: The core functionality of gpt-researcher under Apache-2.0 license is free to use, however, users need API keys from external Language Model Providers like OpenAI and Tavily, which are subject to their.
- Both tools aim to conduct deep research using AI, with the primary difference being their implementation approaches.
- Tags unique to gpt-researcher: automation, deepresearch, llms, python.
- - When you require automated in-depth research capabilities across diverse LLM providers like OpenAI and Tavily.
When NOT to use gpt-researcher
- - If your setup strictly adheres to a specific tool that does not support the extension of capabilities through skills like Claude Skills.
- - In scenarios with stringent network restrictions where running an autonomous agent on top of various LLM providers is prohibited or poses security risks.
Choose deep-research if…
- deep-research is primarily TypeScript; gpt-researcher is Python.
- License: deep-research is MIT, gpt-researcher is Apache-2.0.
- Requirements: Requires Docker.
- Both tools aim to conduct deep research using AI, with the primary difference being their implementation approaches.
- Tags unique to deep-research: gpt, o3-mini, research.
- When you need a tool that can refine its topic focus over time through repeated iterations.
When NOT to use deep-research
- When you prefer a language other than TypeScript, as deep-research specifically requires a Node.js environment.
- If your use case does not necessitate the use of both Firecrawl and OpenAI APIs, preferring instead solutions with more API flexibility or that do not require API keys.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (assafelovic/gpt-researcher) · observed Sep 20, 2026
- GitHub forks (assafelovic/gpt-researcher) · observed Sep 20, 2026
- Last push (assafelovic/gpt-researcher) · observed Aug 27, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (dzhng/deep-research) · observed Sep 20, 2026
- GitHub forks (dzhng/deep-research) · observed Sep 20, 2026
- Last push (dzhng/deep-research) · observed Apr 11, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: gpt-researcher 29k · deep-research 20k (synced Sep 20, 2026).
Common questions
- What are the key differences between gpt-researcher and deep-research?
- gpt-researcher is a Python-based tool that supports multiple language model providers and can be deployed as a Docker container or a Claude Skill. It is suitable for environments with Python 3.11+ and flexible API key configurations. deep-research, written in TypeScript and using Node.js, combines search engines, web scraping, and large language models, and requires specific API keys for Firecrawl
- When should I choose gpt-researcher over deep-research?
- Choose gpt-researcher if you need automated research capabilities across multiple language model providers and can work within a Python 3.11+ environment. It is also a good fit for those who prefer flexible API key configurations and support for various data sources or custom APIs.
- When should I choose deep-research over gpt-researcher?
- Choose deep-research if your research project requires integration with both Firecrawl and OpenAI APIs and operates within a TypeScript environment. It is also suitable for projects that benefit from Docker for ease of setup.
- Are there scenarios where neither tool would be suitable?
- Yes, neither tool would be suitable if your setup strictly adheres to a specific tool that does not support the extension of capabilities through skills like Claude Skills, or if your use case does not necessitate the use of both Firecrawl and OpenAI APIs. Additionally, if your preferred language is not Python or TypeScript, or if your environment has stringent network restrictions, neither tool
- What is the difference between gpt-researcher and deep-research?
- gpt-researcher: An autonomous agent that conducts deep research using LLM providers. deep-research: An AI-powered research assistant that refines its topic focus over time using search engines, web scraping, and large language models.. See the comparison table for live GitHub stats and shared categories.
- When should I avoid gpt-researcher?
- - If your setup strictly adheres to a specific tool that does not support the extension of capabilities through skills like Claude Skills. - In scenarios with stringent network restrictions where running an autonomous agent on top of various LLM providers is prohibited or poses security risks.
- When should I avoid deep-research?
- When you prefer a language other than TypeScript, as deep-research specifically requires a Node.js environment. If your use case does not necessitate the use of both Firecrawl and OpenAI APIs, preferring instead solutions with more API flexibility or that do not require API keys.
- Is gpt-researcher or deep-research more popular on GitHub?
- gpt-researcher has more GitHub stars (29,343 vs 19,571). Stars measure visibility, not whether either tool fits your constraints.
- Are gpt-researcher and deep-research open source?
- Yes - both are open-source projects on GitHub (gpt-researcher: Apache-2.0, deep-research: MIT).
- Where can I find alternatives to gpt-researcher or deep-research?
- GraphCanon lists graph-backed alternatives at gpt-researcher alternatives and deep-research alternatives (gpt-researcher markdown twin, deep-research markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, gpt-researcher or deep-research?
- gpt-researcher: Active. deep-research: Slowing. 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 deep-research?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: gpt-researcher trust report; deep-research trust report.