--- title: "AutoGPT vs py-gpt" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/significant-gravitas-autogpt-vs-szczyglis-dev-py-gpt" tools: ["significant-gravitas-autogpt", "szczyglis-dev-py-gpt"] --- # AutoGPT vs py-gpt *GraphCanon updated Jul 15, 2026* ## Verdict Pick AutoGPT when tags unique to AutoGPT: agentic-ai, agents, autonomous-agents, gpt; pick py-gpt when tags unique to py-gpt: ai-assistant, autonomous-agent, chatbot, deepseek. [AutoGPT](https://agpt.co) reports 185k GitHub stars, 46k forks, and 494 open issues, last pushed Jul 11, 2026. [py-gpt](https://pygpt.net) has 1.9k stars, 333 forks, and 61 open issues, last pushed Feb 6, 2026. Figures are from public GitHub metadata via [AutoGPT's repository](https://github.com/Significant-Gravitas/AutoGPT) and [py-gpt's repository](https://github.com/szczyglis-dev/py-gpt). | | [AutoGPT](/tools/significant-gravitas-autogpt.md) | [py-gpt](/tools/szczyglis-dev-py-gpt.md) | | --- | --- | --- | | Tagline | AutoGPT is the vision of accessible AI for everyone, to use and to build on. | Desktop AI Assistant powered by GPT-5, GPT-4, o1, o3, Gemini, Claude, Ollama, DeepSeek, Perplexity, Grok, Bielik, chat, vision, voice, RAG, image and video generation, agents, tools, MCP, plugins, spe | | Stars | 185,464 | 1,851 | | Forks | 46,111 | 333 | | Open issues | 494 | 61 | | Language | Python | Python | | Adopt for | 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 | - | - | | Runtime | - | - | | License | Other | Other | | Categories | AI Agents, LLM Frameworks | AI Agents, LLM Frameworks, Vector Databases | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [AutoGPT](/tools/significant-gravitas-autogpt.md) | [py-gpt](/tools/szczyglis-dev-py-gpt.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 0d | 159d | | Open issues (now) | 494 | 61 | | Owner type | Organization | User | | Full report | [trust report](/tools/significant-gravitas-autogpt/trust.md) | [trust report](/tools/szczyglis-dev-py-gpt/trust.md) | ## Decision facts: AutoGPT - **Adopt for:** 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. ## Choose when ### Choose AutoGPT if… - Tags unique to AutoGPT: agentic-ai, agents, autonomous-agents, gpt. - When you need to rapidly prototype or deploy an autonomous agent using existing language models without deep AI expertise. - More GitHub stars (185k vs 1.9k) - visibility, not fit. ### Choose py-gpt if… - Tags unique to py-gpt: ai-assistant, autonomous-agent, chatbot, deepseek. - Also covers Vector Databases. - Leaner open-issue backlog (61). ## 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. ## When NOT to use py-gpt - Last GitHub push was 159 days ago (slowing maintenance, Feb 6, 2026). Validate activity before betting a new project on py-gpt. - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. - Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ## Common questions ### What is the difference between AutoGPT and py-gpt? AutoGPT: AutoGPT is the vision of accessible AI for everyone, to use and to build on.. py-gpt: Desktop AI Assistant powered by GPT-5, GPT-4, o1, o3, Gemini, Claude, Ollama, DeepSeek, Perplexity, Grok, Bielik, chat, vision, voice, RAG, image and video generation, agents, tools, MCP, plugins, spe. See the comparison table for live GitHub stats and shared categories. ### When should I choose AutoGPT over py-gpt? Choose AutoGPT over py-gpt when Tags unique to AutoGPT: agentic-ai, agents, autonomous-agents, gpt; When you need to rapidly prototype or deploy an autonomous agent using existing language models without deep AI expertise; More GitHub stars (185k vs 1.9k) - visibility, not fit. ### When should I choose py-gpt over AutoGPT? Choose py-gpt over AutoGPT when Tags unique to py-gpt: ai-assistant, autonomous-agent, chatbot, deepseek; Also covers Vector Databases; Leaner open-issue backlog (61). ### 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. ### When should I avoid py-gpt? Last GitHub push was 159 days ago (slowing maintenance, Feb 6, 2026). Validate activity before betting a new project on py-gpt. AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ### Is AutoGPT or py-gpt more popular on GitHub? AutoGPT has more GitHub stars (185,464 vs 1,851). Stars measure visibility, not whether either tool fits your constraints. ### Are AutoGPT and py-gpt open source? Yes - both are open-source projects on GitHub (AutoGPT: Other, py-gpt: Other). ### Where can I find alternatives to AutoGPT or py-gpt? GraphCanon lists graph-backed alternatives at [AutoGPT alternatives](/tools/significant-gravitas-autogpt/alternatives) and [py-gpt alternatives](/tools/szczyglis-dev-py-gpt/alternatives) ([AutoGPT markdown twin](/tools/significant-gravitas-autogpt/alternatives.md), [py-gpt markdown twin](/tools/szczyglis-dev-py-gpt/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 [this comparison](/compare/significant-gravitas-autogpt-vs-szczyglis-dev-py-gpt.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, AutoGPT or py-gpt? AutoGPT: Very active. py-gpt: 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 AutoGPT and py-gpt? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [AutoGPT trust report](/tools/significant-gravitas-autogpt/trust); [py-gpt trust report](/tools/szczyglis-dev-py-gpt/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=significant-gravitas-autogpt`](/api/graphcanon/graph?tool=significant-gravitas-autogpt) - 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/_