--- title: "agent-opt vs agent-lightning" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/future-agi-agent-opt-vs-microsoft-agent-lightning" tools: ["future-agi-agent-opt", "microsoft-agent-lightning"] --- # agent-opt vs agent-lightning *GraphCanon updated Aug 19, 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 agent-lightning if detailed examination of agent-lightning reveals its strong points in model training, specifically its support for reinforcement learning and MLOps. [agent-opt](https://app.futureagi.com) reports 71 GitHub stars, 7 forks, and 0 open issues, last pushed Jun 30, 2026. [agent-lightning](https://microsoft.github.io/agent-lightning/) has 18k stars, 1.5k forks, and 156 open issues, last pushed Aug 19, 2026. Figures are from public GitHub metadata via [agent-opt's repository](https://github.com/future-agi/agent-opt) and [agent-lightning's repository](https://github.com/microsoft/agent-lightning). | | [agent-opt](/tools/future-agi-agent-opt.md) | [agent-lightning](/tools/microsoft-agent-lightning.md) | | --- | --- | --- | | Tagline | Open Source Library for Automated Optimization of AI Agent Workflows | The absolute trainer to light up AI agents | | Stars | 71 | 17,500 | | Forks | 7 | 1,541 | | Open issues | 0 | 156 | | 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. | Detailed examination of agent-lightning reveals its strong points in model training, specifically its support for reinforcement learning and MLOps. | | 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) | [agent-lightning](/tools/microsoft-agent-lightning.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Very active (96%) | | Days since push | 35d | 0d | | Open issues (now) | 0 | 156 | | Stars delta | Unknown | +104 (30d) | | Open issues delta | Unknown | +3 (30d) | | Full report | [trust report](/tools/future-agi-agent-opt/trust.md) | [trust report](/tools/microsoft-agent-lightning/trust.md) | ## 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: agent-lightning - **Adopt for:** Detailed examination of agent-lightning reveals its strong points in model training, specifically its support for reinforcement learning and MLOps. ## Choose when ### Choose agent-opt if… - License: agent-opt is Apache-2.0, agent-lightning is MIT. - Tags unique to agent-opt: ai-agents, aioptimization, automation, cicd. - Also covers Evaluation & Observability. - - When your project needs seamless CI/CD integration alongside automated optimization ### Choose agent-lightning if… - License: agent-lightning is MIT, agent-opt is Apache-2.0. - Tags unique to agent-lightning: agentic-ai, llm, mlops, reinforcement-learning. - Also covers Model Training. - When you're dealing with projects that require continuous integration and deployment workflows (CI/CD), as agent-lightning supports MLOps practices which facilitate this. ## 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 agent-lightning - Avoid using agent-lightning if you're working in a language other than Python, given that it's only available as a Python package. - It might not be the best fit for projects where stability over cutting-edge features is prioritized. Its development focus leans towards experimental functionalities, with frequent updates to the Test ## Common questions ### What is the difference between agent-opt and agent-lightning? agent-opt: Open Source Library for Automated Optimization of AI Agent Workflows. agent-lightning: The absolute trainer to light up AI agents. See the comparison table for live GitHub stats and shared categories. ### When should I choose agent-opt over agent-lightning? Choose agent-opt over agent-lightning when License: agent-opt is Apache-2.0, agent-lightning is MIT; Tags unique to agent-opt: ai-agents, aioptimization, automation, cicd; Also covers Evaluation & Observability; - When your project needs seamless CI/CD integration alongside automated optimization. ### When should I choose agent-lightning over agent-opt? Choose agent-lightning over agent-opt when License: agent-lightning is MIT, agent-opt is Apache-2.0; Tags unique to agent-lightning: agentic-ai, llm, mlops, reinforcement-learning; Also covers Model Training; When you're dealing with projects that require continuous integration and deployment workflows (CI/CD), as agent-lightning supports MLOps practices which facilitate this. ### 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 agent-lightning? Avoid using agent-lightning if you're working in a language other than Python, given that it's only available as a Python package. It might not be the best fit for projects where stability over cutting-edge features is prioritized. Its development focus leans towards experimental functionalities, with frequent updates to the Test ### Is agent-opt or agent-lightning more popular on GitHub? agent-lightning has more GitHub stars (17,500 vs 71). Stars measure visibility, not whether either tool fits your constraints. ### Are agent-opt and agent-lightning open source? Yes - both are open-source projects on GitHub (agent-opt: Apache-2.0, agent-lightning: MIT). ### Where can I find alternatives to agent-opt or agent-lightning? GraphCanon lists graph-backed alternatives at [agent-opt alternatives](/tools/future-agi-agent-opt/alternatives) and [agent-lightning alternatives](/tools/microsoft-agent-lightning/alternatives) ([agent-opt markdown twin](/tools/future-agi-agent-opt/alternatives.md), [agent-lightning markdown twin](/tools/microsoft-agent-lightning/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-microsoft-agent-lightning.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agent-opt or agent-lightning? agent-opt: Steady. agent-lightning: 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 agent-opt and agent-lightning? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agent-opt trust report](/tools/future-agi-agent-opt/trust); [agent-lightning trust report](/tools/microsoft-agent-lightning/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/_