--- title: "every_eval_ever vs AutoGPT" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/evaleval-every-eval-ever-vs-significant-gravitas-autogpt" tools: ["evaleval-every-eval-ever", "significant-gravitas-autogpt"] --- # every_eval_ever vs AutoGPT *GraphCanon updated Jul 15, 2026* ## Verdict Pick every_eval_ever when license: every_eval_ever is MIT, AutoGPT is Other; pick AutoGPT when license: AutoGPT is Other, every_eval_ever is MIT. [every_eval_ever](https://evalevalai.com/projects/every-eval-ever/) reports 93 GitHub stars, 42 forks, and 48 open issues, last pushed Jul 4, 2026. [AutoGPT](https://agpt.co) has 185k stars, 46k forks, and 494 open issues, last pushed Jul 11, 2026. Figures are from public GitHub metadata via [every_eval_ever's repository](https://github.com/evaleval/every_eval_ever) and [AutoGPT's repository](https://github.com/Significant-Gravitas/AutoGPT). | | [every_eval_ever](/tools/evaleval-every-eval-ever.md) | [AutoGPT](/tools/significant-gravitas-autogpt.md) | | --- | --- | --- | | Tagline | Every Eval Ever is a shared schema and crowdsourced eval database. It defines a standardized metadata format for storing AI evaluation results, from leaderboard scrapes and research papers to local ev | AutoGPT is the vision of accessible AI for everyone, to use and to build on. | | Stars | 93 | 185,464 | | Forks | 42 | 46,111 | | Open issues | 48 | 494 | | 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 | MIT | Other | | Categories | AI Agents, Inference & Serving, LLM Frameworks | AI Agents, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [every_eval_ever](/tools/evaleval-every-eval-ever.md) | [AutoGPT](/tools/significant-gravitas-autogpt.md) | | --- | --- | --- | | Maintenance | Active (82%) | Very active (96%) | | Days since push | 10d | 0d | | Open issues (now) | 48 | 494 | | Full report | [trust report](/tools/evaleval-every-eval-ever/trust.md) | [trust report](/tools/significant-gravitas-autogpt/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 every_eval_ever if… - License: every_eval_ever is MIT, AutoGPT is Other. - Tags unique to every_eval_ever: agent-evaluation, ai-evaluation, evaluations, infra. - Also covers Inference & Serving. ### Choose AutoGPT if… - License: AutoGPT is Other, every_eval_ever is MIT. - Tags unique to AutoGPT: agentic-ai, agents, ai, artificial-intelligence. - When you need to rapidly prototype or deploy an autonomous agent using existing language models without deep AI expertise. ## When NOT to use every_eval_ever - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## 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. ## Common questions ### What is the difference between every_eval_ever and AutoGPT? every_eval_ever: Every Eval Ever is a shared schema and crowdsourced eval database. It defines a standardized metadata format for storing AI evaluation results, from leaderboard scrapes and research papers to local ev. 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 every_eval_ever over AutoGPT? Choose every_eval_ever over AutoGPT when License: every_eval_ever is MIT, AutoGPT is Other; Tags unique to every_eval_ever: agent-evaluation, ai-evaluation, evaluations, infra; Also covers Inference & Serving. ### When should I choose AutoGPT over every_eval_ever? Choose AutoGPT over every_eval_ever when License: AutoGPT is Other, every_eval_ever is MIT; Tags unique to AutoGPT: agentic-ai, agents, 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 avoid every_eval_ever? AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### 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 every_eval_ever or AutoGPT more popular on GitHub? AutoGPT has more GitHub stars (185,464 vs 93). Stars measure visibility, not whether either tool fits your constraints. ### Are every_eval_ever and AutoGPT open source? Yes - both are open-source projects on GitHub (every_eval_ever: MIT, AutoGPT: Other). ### Where can I find alternatives to every_eval_ever or AutoGPT? GraphCanon lists graph-backed alternatives at [every_eval_ever alternatives](/tools/evaleval-every-eval-ever/alternatives) and [AutoGPT alternatives](/tools/significant-gravitas-autogpt/alternatives) ([every_eval_ever markdown twin](/tools/evaleval-every-eval-ever/alternatives.md), [AutoGPT markdown twin](/tools/significant-gravitas-autogpt/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/evaleval-every-eval-ever-vs-significant-gravitas-autogpt.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, every_eval_ever or AutoGPT? every_eval_ever: Active. 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 every_eval_ever and AutoGPT? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [every_eval_ever trust report](/tools/evaleval-every-eval-ever/trust); [AutoGPT trust report](/tools/significant-gravitas-autogpt/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=evaleval-every-eval-ever`](/api/graphcanon/graph?tool=evaleval-every-eval-ever) - 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/_