--- title: "agent-opt vs aideml" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/future-agi-agent-opt-vs-wecoai-aideml" tools: ["future-agi-agent-opt", "wecoai-aideml"] --- # agent-opt vs aideml *GraphCanon updated Aug 4, 2026* ## Verdict Pick agent-opt if agent-opt is tailored for teams that require automated optimization of AI workflows and support for continuous integration/continuous delivery (CI/CD), relying on Python and specific library dependencies; pick aideml if aIDE is an autonomous machine learning engineering agent designed to automate AI research and development tasks, enhancing code optimization through intelligent automation. [agent-opt](https://app.futureagi.com) reports 71 GitHub stars, 7 forks, and 0 open issues, last pushed Jun 30, 2026. [aideml](https://weco.ai) has 1.5k stars, 212 forks, and 2 open issues, last pushed Jul 15, 2026. Figures are from public GitHub metadata via [agent-opt's repository](https://github.com/future-agi/agent-opt) and [aideml's repository](https://github.com/WecoAI/aideml). | | [agent-opt](/tools/future-agi-agent-opt.md) | [aideml](/tools/wecoai-aideml.md) | | --- | --- | --- | | Tagline | Open Source Library for Automated Optimization of AI Agent Workflows | AI-Driven Exploration in the Space of Code | | Stars | 71 | 1,460 | | Forks | 7 | 212 | | Open issues | 0 | 2 | | Language | Python | Python | | Adopt for | Agent-opt is tailored for teams that require automated optimization of AI workflows and support for continuous integration/continuous delivery (CI/CD), relying on Python and specific library dependencies. | AIDE is an autonomous machine learning engineering agent designed to automate AI research and development tasks, enhancing code optimization through intelligent automation. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | MIT | | Categories | AI Agents, Evaluation & Observability | AI Agents, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agent-opt](/tools/future-agi-agent-opt.md) | [aideml](/tools/wecoai-aideml.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Active (82%) | | Days since push | 35d | 18d | | Open issues (now) | 0 | 2 | | Full report | [trust report](/tools/future-agi-agent-opt/trust.md) | [trust report](/tools/wecoai-aideml/trust.md) | ## Shared compatibility - **Python**: [agent-opt](/tools/future-agi-agent-opt.md) - Python runtime; [aideml](/tools/wecoai-aideml.md) - Python runtime ## Decision facts: agent-opt - **Adopt for:** Agent-opt is tailored for teams that require automated optimization of AI workflows and support for continuous integration/continuous delivery (CI/CD), relying on Python and specific library dependencies. ## Decision facts: aideml - **Pricing:** freemium - The tool is available for free under the MIT license. However, external services like the OpenAI API might incur costs based on their usage policies. - **Requirements:** Min 4 GB RAM; Requires Docker; OpenAI API key is necessary for operation.; The tool supports setup through Docker or direct installation using pip for development use. - **Adopt for:** AIDE is an autonomous machine learning engineering agent designed to automate AI research and development tasks, enhancing code optimization through intelligent automation. ## Choose when ### Choose agent-opt if… - License: agent-opt is Apache-2.0, aideml is MIT. - Tags unique to agent-opt: agent, aioptimization, automation, cicd. - Also covers Evaluation & Observability. - - When your project needs seamless CI/CD integration alongside automated optimization ### Choose aideml if… - License: aideml is MIT, agent-opt is Apache-2.0. - Pricing: The tool is available for free under the MIT license. However, external services like the OpenAI API might incur costs based on their usage policies.. - Requirements: Min 4 GB RAM; Requires Docker; OpenAI API key is necessary for operation.; The tool supports setup through Docker or direct installation using pip for development use.. - Tags unique to aideml: automated-machine-learning, autonomous-agents, autoresearch, code-optimization. - Also covers Model Training. - aideml ships Docker support for self-hosted deployment. - When you need sophisticated automation in the R&D phase of your AI projects, leveraging AI-driven exploration to refine code effectively. ## When NOT to use agent-opt - - If your project does not require Python or if it cannot meet the specific requirement of having Python ≥ 3.10 - - In scenarios where CI/CD integration is not a priority for your AI workflow optimization ## When NOT to use aideml - If you seek a tool that is extensively documented or has community support, as the repository might lack detailed instructions and user forums. - For projects that require manual oversight at every stage of R&D; AIDE's strength lies in automating these processes, which may reduce human intervention more than desired. ## Common questions ### What is the difference between agent-opt and aideml? agent-opt: Open Source Library for Automated Optimization of AI Agent Workflows. aideml: AI-Driven Exploration in the Space of Code. See the comparison table for live GitHub stats and shared categories. ### When should I choose agent-opt over aideml? Choose agent-opt over aideml when License: agent-opt is Apache-2.0, aideml is MIT; Tags unique to agent-opt: agent, aioptimization, automation, cicd; Also covers Evaluation & Observability; - When your project needs seamless CI/CD integration alongside automated optimization. ### When should I choose aideml over agent-opt? Choose aideml over agent-opt when License: aideml is MIT, agent-opt is Apache-2.0; Pricing: The tool is available for free under the MIT license. However, external services like the OpenAI API might incur costs based on their usage policies.; Requirements: Min 4 GB RAM; Requires Docker; OpenAI API key is necessary for operation.; The tool supports setup through Docker or direct installation using pip for development use.; Tags unique to aideml: automated-machine-learning, autonomous-agents, autoresearch, code-optimization; Also covers Model Training; aideml ships Docker support for self-hosted deployment; When you need sophisticated automation in the R&D phase of your AI projects, leveraging AI-driven exploration to refine code effectively. ### When should I avoid agent-opt? - If your project does not require Python or if it cannot meet the specific requirement of having Python ≥ 3.10 - In scenarios where CI/CD integration is not a priority for your AI workflow optimization ### When should I avoid aideml? If you seek a tool that is extensively documented or has community support, as the repository might lack detailed instructions and user forums. For projects that require manual oversight at every stage of R&D; AIDE's strength lies in automating these processes, which may reduce human intervention more than desired. ### Is agent-opt or aideml more popular on GitHub? aideml has more GitHub stars (1,460 vs 71). Stars measure visibility, not whether either tool fits your constraints. ### Are agent-opt and aideml open source? Yes - both are open-source projects on GitHub (agent-opt: Apache-2.0, aideml: MIT). ### Where can I find alternatives to agent-opt or aideml? GraphCanon lists graph-backed alternatives at [agent-opt alternatives](/tools/future-agi-agent-opt/alternatives) and [aideml alternatives](/tools/wecoai-aideml/alternatives) ([agent-opt markdown twin](/tools/future-agi-agent-opt/alternatives.md), [aideml markdown twin](/tools/wecoai-aideml/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/future-agi-agent-opt-vs-wecoai-aideml.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agent-opt or aideml? agent-opt: Steady. aideml: 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 agent-opt and aideml? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agent-opt trust report](/tools/future-agi-agent-opt/trust); [aideml trust report](/tools/wecoai-aideml/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=future-agi-agent-opt`](/api/graphcanon/graph?tool=future-agi-agent-opt) - 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/_