Comparison
ROLL vs agent-opt
Verdict
Pick ROLL if efficient library for scaling reinforcement learning tasks with large language models; user-friendly setup and debugging tools provided; 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.
Markdown twin · ROLL alternatives · agent-opt alternatives
GraphCanon updated 2w
Trust & integrity
| Signal | ROLL | agent-opt |
|---|---|---|
| Maintenance | Very active (0d since push) As of 2w · github_public_v1 | Steady (35d since push) As of 2w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 2w · github_public_v1 | Not a fork · Organization account As of 2w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · 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
- ROLL
- Scaling Library for Reinforcement Learning with Large Language Models
- agent-opt
- Open Source Library for Automated Optimization of AI Agent Workflows
Stars
- ROLL
- 3.4k
- agent-opt
- 71
Forks
- ROLL
- 304
- agent-opt
- 7
Open issues
- ROLL
- 120
- agent-opt
- 0
Language
- ROLL
- Python
- agent-opt
- Python
Adopt for
- ROLL
- Efficient library for scaling reinforcement learning tasks with large language models; user-friendly setup and debugging tools provided.
- 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.
Persona
- ROLL
- -
- agent-opt
- -
Runtime
- ROLL
- -
- agent-opt
- -
License
- ROLL
- Apache-2.0
- agent-opt
- Apache-2.0
Last pushed
- ROLL
- Aug 7, 2026
- agent-opt
- Jun 30, 2026
Categories
- ROLL
- Evaluation & Observability, Model Training
- agent-opt
- AI Agents, Evaluation & Observability
Trust and health
Maintenance
- ROLL
- Very active (96%)
- agent-opt
- Steady (60%)
Days since push
- ROLL
- 0d
- agent-opt
- 35d
Open issues (now)
- ROLL
- 120
- agent-opt
- 0
Full report
- ROLL
- Trust report
- agent-opt
- Trust report
Choose ROLL if…
- Tags unique to ROLL: agentic, rlhf, rlvr.
- Also covers Model Training.
- When developing reinforcement learning applications requiring integration of large language models, offering efficient scalability solutions.
When NOT to use ROLL
- Avoid for tasks that prioritize minimalist setups over advanced feature integrations like Alibaba Cloud Function Compute DevPods.
- Not suitable if you prefer tools without built-in support for converting models between MCoreAdapter and Hugging Face formats.
Choose agent-opt if…
- Tags unique to agent-opt: agent, ai-agents, aioptimization, automation.
- Also covers AI Agents.
- - 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
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (alibaba/ROLL) · observed Aug 7, 2026
- GitHub forks (alibaba/ROLL) · observed Aug 7, 2026
- Last push (alibaba/ROLL) · observed Aug 7, 2026
- License file (Apache-2.0) · observed Aug 7, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- 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 on cards: ROLL 3.4k · agent-opt 71 (synced Aug 7, 2026).
Common questions
- What is the difference between ROLL and agent-opt?
- ROLL: Scaling Library for Reinforcement Learning with Large Language Models. agent-opt: Open Source Library for Automated Optimization of AI Agent Workflows. See the comparison table for live GitHub stats and shared categories.
- When should I choose ROLL over agent-opt?
- Choose ROLL over agent-opt when Tags unique to ROLL: agentic, rlhf, rlvr; Also covers Model Training; When developing reinforcement learning applications requiring integration of large language models, offering efficient scalability solutions.
- When should I choose agent-opt over ROLL?
- Choose agent-opt over ROLL when Tags unique to agent-opt: agent, ai-agents, aioptimization, automation; Also covers AI Agents; - When your project needs seamless CI/CD integration alongside automated optimization.
- When should I avoid ROLL?
- Avoid for tasks that prioritize minimalist setups over advanced feature integrations like Alibaba Cloud Function Compute DevPods. Not suitable if you prefer tools without built-in support for converting models between MCoreAdapter and Hugging Face formats.
- 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
- Is ROLL or agent-opt more popular on GitHub?
- ROLL has more GitHub stars (3,354 vs 71). Stars measure visibility, not whether either tool fits your constraints.
- Are ROLL and agent-opt open source?
- Yes - both are open-source projects on GitHub (ROLL: Apache-2.0, agent-opt: Apache-2.0).
- Where can I find alternatives to ROLL or agent-opt?
- GraphCanon lists graph-backed alternatives at ROLL alternatives and agent-opt alternatives (ROLL markdown twin, agent-opt 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, ROLL or agent-opt?
- ROLL: Very active. agent-opt: Steady. 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 ROLL and agent-opt?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: ROLL trust report; agent-opt trust report.