Comparison
deep-research vs AutoGPT
Verdict
Pick deep-research if 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; pick AutoGPT if autoGPT is a Python-based tool for creating accessible autonomous AI agents that can leverage various LLM APIs including OpenAI's GPT and Anthropic's Claude.
Markdown twin · deep-research alternatives · AutoGPT alternatives
GraphCanon updated 2d
vs
Trust & integrity
| Signal | deep-research | AutoGPT |
|---|---|---|
| Maintenance | Slowing (129d since push) As of 2d · github_public_v1 | Very active (0d since push) As of 5d · github_public_v1 |
| Provenance | Not a fork · Personal account As of 2d · github_public_v1 | Not a fork · Organization account As of 5d · github_public_v1 |
| OSV dependency advisories | Published findings As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · 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
- deep-research
- An AI-powered research assistant that refines its topic focus over time using search engines, web scraping, and large language models.
- AutoGPT
- AutoGPT is the vision of accessible AI for everyone, to use and to build on.
Stars
- deep-research
- 20k
- AutoGPT
- 187k
Forks
- deep-research
- 2.0k
- AutoGPT
- 46k
Open issues
- deep-research
- 93
- AutoGPT
- 517
Language
- deep-research
- TypeScript
- AutoGPT
- Python
Adopt for
- 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.
- AutoGPT
- AutoGPT is a Python-based tool for creating accessible autonomous AI agents that can leverage various LLM APIs including OpenAI's GPT and Anthropic's Claude.
Persona
- deep-research
- -
- AutoGPT
- -
Runtime
- deep-research
- -
- AutoGPT
- -
License
- deep-research
- MIT
- AutoGPT
- Other
Last pushed
- deep-research
- Apr 11, 2026
- AutoGPT
- Aug 15, 2026
Categories
- deep-research
- AI Agents, Data & Retrieval
- AutoGPT
- AI Agents, LLM Frameworks
Trust and health
Maintenance
- deep-research
- Slowing (36%)
- AutoGPT
- Very active (96%)
Days since push
- deep-research
- 129d
- AutoGPT
- 0d
Open issues (now)
- deep-research
- 93
- AutoGPT
- 517
Stars delta
- deep-research
- +195 (30d)
- AutoGPT
- +1.0k (30d)
Open issues delta
- deep-research
- +3 (30d)
- AutoGPT
- +19 (30d)
Owner type
- deep-research
- User
- AutoGPT
- Organization
OSV dependency advisories
- deep-research
- Published findings
- AutoGPT
- No lockfile (source not queried)
Full report
- deep-research
- Trust report
- AutoGPT
- Trust report
Typed relationship
deep-research alternative AutoGPTBoth deep-research and AutoGPT use large language models to execute tasks, including iterative research and decision making; they are alternatives in the AI agent domain.
Choose deep-research if…
- deep-research is primarily TypeScript; AutoGPT is Python.
- License: deep-research is MIT, AutoGPT is Other.
- Requirements: Requires Docker.
- Both deep-research and AutoGPT use large language models to execute tasks, including iterative research and decision making; they are alternatives in the AI agent domain.
- Tags unique to deep-research: agent, o3-mini, research.
- Also covers Data & Retrieval.
- deep-research ships Docker support for self-hosted deployment.
- 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.
Choose AutoGPT if…
- AutoGPT is primarily Python; deep-research is TypeScript.
- License: AutoGPT is Other, deep-research is MIT.
- Both deep-research and AutoGPT use large language models to execute tasks, including iterative research and decision making; they are alternatives in the AI agent domain.
- Tags unique to AutoGPT: agentic-ai, agents, artificial-intelligence, autonomous-agents.
- Also covers LLM Frameworks.
- When you need to rapidly prototype or deploy an autonomous agent using existing language models without deep AI expertise.
When NOT to use AutoGPT
- Avoid if you require absolute control over the underlying AI infrastructure and APIs used by your autonomous agents, as AutoGPT imposes its own framework.
- If your project demands proprietary or specialized models that aren't supported by AutoGPT's API ecosystem (e.g., custom TensorFlow or PyTorch models), consider other tools.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (dzhng/deep-research) · observed Aug 19, 2026
- GitHub forks (dzhng/deep-research) · observed Aug 19, 2026
- Last push (dzhng/deep-research) · observed Apr 11, 2026
- License file (MIT) · observed Aug 19, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (Significant-Gravitas/AutoGPT) · observed Aug 16, 2026
- GitHub forks (Significant-Gravitas/AutoGPT) · observed Aug 16, 2026
- Last push (Significant-Gravitas/AutoGPT) · observed Aug 15, 2026
- License file (Other) · observed Aug 16, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: deep-research 20k · AutoGPT 187k (synced Aug 19, 2026).
Common questions
- What is the difference between deep-research and AutoGPT?
- deep-research: An AI-powered research assistant that refines its topic focus over time using search engines, web scraping, and large language models.. AutoGPT: AutoGPT is the vision of accessible AI for everyone, to use and to build on.. See the comparison table for live GitHub stats and shared categories.
- When should I choose deep-research over AutoGPT?
- Choose deep-research over AutoGPT when deep-research is primarily TypeScript; AutoGPT is Python; License: deep-research is MIT, AutoGPT is Other; Requirements: Requires Docker; Both deep-research and AutoGPT use large language models to execute tasks, including iterative research and decision making; they are alternatives in the AI agent domain; Tags unique to deep-research: agent, o3-mini, research; Also covers Data & Retrieval; deep-research ships Docker support for self-hosted deployment; When you need a tool that can refine its topic focus over time through repeated iterations.
- When should I choose AutoGPT over deep-research?
- Choose AutoGPT over deep-research when AutoGPT is primarily Python; deep-research is TypeScript; License: AutoGPT is Other, deep-research is MIT; Both deep-research and AutoGPT use large language models to execute tasks, including iterative research and decision making; they are alternatives in the AI agent domain; Tags unique to AutoGPT: agentic-ai, agents, artificial-intelligence, autonomous-agents; Also covers LLM Frameworks; When you need to rapidly prototype or deploy an autonomous agent using existing language models without deep AI expertise.
- 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.
- When should I avoid AutoGPT?
- Avoid if you require absolute control over the underlying AI infrastructure and APIs used by your autonomous agents, as AutoGPT imposes its own framework. If your project demands proprietary or specialized models that aren't supported by AutoGPT's API ecosystem (e.g., custom TensorFlow or PyTorch models), consider other tools.
- Is deep-research or AutoGPT more popular on GitHub?
- AutoGPT has more GitHub stars (186,623 vs 19,571). Stars measure visibility, not whether either tool fits your constraints.
- Are deep-research and AutoGPT open source?
- Yes - both are open-source projects on GitHub (deep-research: MIT, AutoGPT: Other).
- Where can I find alternatives to deep-research or AutoGPT?
- GraphCanon lists graph-backed alternatives at deep-research alternatives and AutoGPT alternatives (deep-research markdown twin, AutoGPT 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, deep-research or AutoGPT?
- deep-research: Slowing. AutoGPT: 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 deep-research and AutoGPT?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: deep-research trust report; AutoGPT trust report.