--- title: "AutoGPT vs awesome-AutoML" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/significant-gravitas-autogpt-vs-windmaple-awesome-automl" tools: ["significant-gravitas-autogpt", "windmaple-awesome-automl"] --- # AutoGPT vs awesome-AutoML *GraphCanon updated Jul 11, 2026* ## Verdict Pick AutoGPT when license: AutoGPT is Other, awesome-AutoML is GPL-3.0; pick awesome-AutoML when license: awesome-AutoML is GPL-3.0, AutoGPT is Other. [AutoGPT](https://agpt.co) reports 185k GitHub stars, 46k forks, and 494 open issues, last pushed Jul 11, 2026. [awesome-AutoML](https://github.com/windmaple/awesome-AutoML) has 940 stars, 155 forks, and 1 open issues, last pushed Mar 24, 2026. Figures are from public GitHub metadata via [AutoGPT's repository](https://github.com/Significant-Gravitas/AutoGPT) and [awesome-AutoML's repository](https://github.com/windmaple/awesome-AutoML). | | [AutoGPT](/tools/significant-gravitas-autogpt.md) | [awesome-AutoML](/tools/windmaple-awesome-automl.md) | | --- | --- | --- | | Tagline | AutoGPT is the vision of accessible AI for everyone, to use and to build on. | Curating a list of AutoML-related research, tools, projects and other resources | | Stars | 185,464 | 940 | | Forks | 46,111 | 155 | | Open issues | 494 | 1 | | Language | 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 | GPL-3.0 | | Categories | LLM Frameworks, AI Agents | LLM Frameworks, Model Training, AI Agents | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [AutoGPT](/tools/significant-gravitas-autogpt.md) | [awesome-AutoML](/tools/windmaple-awesome-automl.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Slowing (36%) | | Days since push | 0d | 109d | | Open issues (now) | 494 | 1 | | Owner type | Organization | User | | Full report | [trust report](/tools/significant-gravitas-autogpt/trust.md) | [trust report](/tools/windmaple-awesome-automl/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… - License: AutoGPT is Other, awesome-AutoML is GPL-3.0. - Tags unique to AutoGPT: agents, llm, ai, artificial-intelligence. - When you need to rapidly prototype or deploy an autonomous agent using existing language models without deep AI expertise. ### Choose awesome-AutoML if… - License: awesome-AutoML is GPL-3.0, AutoGPT is Other. - Also covers Model Training. - Leaner open-issue backlog (1). ## 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 awesome-AutoML - Last GitHub push was 110 days ago (slowing maintenance, Mar 24, 2026). Validate activity before betting a new project on awesome-AutoML. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. - Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. ## Common questions ### What is the difference between AutoGPT and awesome-AutoML? AutoGPT: AutoGPT is the vision of accessible AI for everyone, to use and to build on.. awesome-AutoML: Curating a list of AutoML-related research, tools, projects and other resources. See the comparison table for live GitHub stats and shared categories. ### When should I choose AutoGPT over awesome-AutoML? Choose AutoGPT over awesome-AutoML when License: AutoGPT is Other, awesome-AutoML is GPL-3.0; Tags unique to AutoGPT: agents, llm, ai, artificial-intelligence; When you need to rapidly prototype or deploy an autonomous agent using existing language models without deep AI expertise. ### When should I choose awesome-AutoML over AutoGPT? Choose awesome-AutoML over AutoGPT when License: awesome-AutoML is GPL-3.0, AutoGPT is Other; Also covers Model Training; Leaner open-issue backlog (1). ### 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 awesome-AutoML? Last GitHub push was 110 days ago (slowing maintenance, Mar 24, 2026). Validate activity before betting a new project on awesome-AutoML. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. ### Is AutoGPT or awesome-AutoML more popular on GitHub? AutoGPT has more GitHub stars (185,464 vs 940). Stars measure visibility, not whether either tool fits your constraints. ### Are AutoGPT and awesome-AutoML open source? Yes - both are open-source projects on GitHub (AutoGPT: Other, awesome-AutoML: GPL-3.0). ### Where can I find alternatives to AutoGPT or awesome-AutoML? GraphCanon lists graph-backed alternatives at [AutoGPT alternatives](/tools/significant-gravitas-autogpt/alternatives) and [awesome-AutoML alternatives](/tools/windmaple-awesome-automl/alternatives) ([AutoGPT markdown twin](/tools/significant-gravitas-autogpt/alternatives.md), [awesome-AutoML markdown twin](/tools/windmaple-awesome-automl/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-windmaple-awesome-automl.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, AutoGPT or awesome-AutoML? AutoGPT: Very active. awesome-AutoML: 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 awesome-AutoML? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [AutoGPT trust report](/tools/significant-gravitas-autogpt/trust); [awesome-AutoML trust report](/tools/windmaple-awesome-automl/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/_