Comparison
agent-opt vs agent-lightning
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.
Markdown twin · agent-opt alternatives · agent-lightning alternatives
GraphCanon updated today
vs
Trust & integrity
| Signal | agent-opt | agent-lightning |
|---|---|---|
| Maintenance | Steady (35d since push) As of 2w · github_public_v1 | Very active (0d since push) As of today · github_public_v1 |
| Provenance | Not a fork · Organization account As of 2w · github_public_v1 | Not a fork · Organization account As of today · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1w · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- agent-opt
- Open Source Library for Automated Optimization of AI Agent Workflows
- agent-lightning
- The absolute trainer to light up AI agents
Stars
- agent-opt
- 71
- agent-lightning
- 18k
Forks
- agent-opt
- 7
- agent-lightning
- 1.5k
Open issues
- agent-opt
- 0
- agent-lightning
- 156
Language
- agent-opt
- Python
- agent-lightning
- Python
Adopt for
- agent-opt
- 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.
- agent-lightning
- Detailed examination of agent-lightning reveals its strong points in model training, specifically its support for reinforcement learning and MLOps.
Persona
- agent-opt
- -
- agent-lightning
- -
Runtime
- agent-opt
- -
- agent-lightning
- -
License
- agent-opt
- Apache-2.0
- agent-lightning
- MIT
Last pushed
- agent-opt
- Jun 30, 2026
- agent-lightning
- Aug 19, 2026
Categories
- agent-opt
- AI Agents, Evaluation & Observability
- agent-lightning
- AI Agents, Model Training
Trust and health
Maintenance
- agent-opt
- Steady (60%)
- agent-lightning
- Very active (96%)
Days since push
- agent-opt
- 35d
- agent-lightning
- 0d
Open issues (now)
- agent-opt
- 0
- agent-lightning
- 156
Stars delta
- agent-opt
- Unknown
- agent-lightning
- +104 (30d)
Open issues delta
- agent-opt
- Unknown
- agent-lightning
- +3 (30d)
Full report
- agent-opt
- Trust report
- agent-lightning
- Trust report
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
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
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-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
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (future-agi/agent-opt) · observed Aug 4, 2026
- GitHub forks (future-agi/agent-opt) · observed Aug 4, 2026
- Last push (future-agi/agent-opt) · observed Jun 30, 2026
- License file (Apache-2.0) · observed Aug 4, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (microsoft/agent-lightning) · observed Aug 19, 2026
- GitHub forks (microsoft/agent-lightning) · observed Aug 19, 2026
- Last push (microsoft/agent-lightning) · observed Aug 19, 2026
- License file (MIT) · observed Aug 19, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Aug 9, 2026
GitHub stars on cards: agent-opt 71 · agent-lightning 18k (synced Aug 4, 2026).
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 and agent-lightning alternatives (agent-opt markdown twin, agent-lightning markdown twin), 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 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; agent-lightning trust report.