Comparison
agent-opt vs agentic-vbench
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 agentic-vbench if agenticVBench evaluates AI agents' real-world post-production capabilities with specific task prompts for activities like audio restoration.
Markdown twin · agent-opt alternatives · agentic-vbench alternatives
GraphCanon updated Sep 20, 2026
12views this month
vs
Trust & integrity
| Signal | agent-opt | agentic-vbench |
|---|---|---|
| Maintenance | Steady (66d since push) As of Sep 4, 2026 · github_public_v1 | Very active (6d since push) As of Sep 9, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 4, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 9, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 15, 2026 · 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
- agentic-vbench
- A benchmark for evaluating AI agents in performing real-world post-production tasks like audio and video editing.
Stars
- agent-opt
- 74
- agentic-vbench
- 96
Forks
- agent-opt
- 8
- agentic-vbench
- 27
Open issues
- agent-opt
- 0
- agentic-vbench
- 37
Language
- agent-opt
- Python
- agentic-vbench
- 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.
- agentic-vbench
- AgenticVBench evaluates AI agents' real-world post-production capabilities with specific task prompts for activities like audio restoration.
Persona
- agent-opt
- -
- agentic-vbench
- -
Runtime
- agent-opt
- -
- agentic-vbench
- -
License
- agent-opt
- Apache-2.0
- agentic-vbench
- Apache-2.0
Last pushed
- agent-opt
- Jun 30, 2026
- agentic-vbench
- Sep 2, 2026
Categories
- agent-opt
- AI Agents, Evaluation & Observability
- agentic-vbench
- AI Agents, Evaluation & Observability
Trust and health
Maintenance
- agent-opt
- Steady (60%)
- agentic-vbench
- Very active (96%)
Days since push
- agent-opt
- 66d
- agentic-vbench
- 6d
Open issues (now)
- agent-opt
- 0
- agentic-vbench
- 37
Stars delta
- agent-opt
- +3 (30d)
- agentic-vbench
- +14 (30d)
Open issues delta
- agent-opt
- 0 (30d)
- agentic-vbench
- -20 (30d)
Full report
- agent-opt
- Trust report
- agentic-vbench
- Trust report
Shared compatibility
- Python · agent-opt: Python runtime · agentic-vbench: Python runtime
Choose agent-opt if…
- Tags unique to agent-opt: agent, aioptimization, automation, cicd.
- - When your project needs seamless CI/CD integration alongside automated optimization
- Leaner open-issue backlog (0).
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 agentic-vbench if…
- Requirements: Requires Docker; Install via scripts provided in the repository.; Python virtual environment setup for reproducibility..
- Tags unique to agentic-vbench: benchmark, harbor, llm-evaluation, video-editing.
- When you need to benchmark the performance of AI agents in handling specialized tasks such as audio and video editing that require precise restorative actions.
When NOT to use agentic-vbench
- When the focus is on generic performance evaluations rather than on real-world, task-specific benchmarks that assess handling complex post-production scenarios.
- If your budget or timeline cannot accommodate a per-task wall clock time of ~10 minutes and cost ranging from $0.10 to $2 based on agent token usage.
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 Sep 20, 2026
- GitHub forks (future-agi/agent-opt) · observed Sep 20, 2026
- Last push (future-agi/agent-opt) · observed Jun 30, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 17, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (PhiloLabs/agentic-vbench) · observed Sep 20, 2026
- GitHub forks (PhiloLabs/agentic-vbench) · observed Sep 20, 2026
- Last push (PhiloLabs/agentic-vbench) · observed Sep 2, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 16, 2026
- Trust scan (lockfile / OSV) · observed Jul 15, 2026
GitHub stars on cards: agent-opt 74 · agentic-vbench 96 (synced Sep 20, 2026).
Common questions
- What is the difference between agent-opt and agentic-vbench?
- agent-opt: Open Source Library for Automated Optimization of AI Agent Workflows. agentic-vbench: A benchmark for evaluating AI agents in performing real-world post-production tasks like audio and video editing.. See the comparison table for live GitHub stats and shared categories.
- When should I choose agent-opt over agentic-vbench?
- Choose agent-opt over agentic-vbench when Tags unique to agent-opt: agent, aioptimization, automation, cicd; - When your project needs seamless CI/CD integration alongside automated optimization; Leaner open-issue backlog (0).
- When should I choose agentic-vbench over agent-opt?
- Choose agentic-vbench over agent-opt when Requirements: Requires Docker; Install via scripts provided in the repository.; Python virtual environment setup for reproducibility.; Tags unique to agentic-vbench: benchmark, harbor, llm-evaluation, video-editing; When you need to benchmark the performance of AI agents in handling specialized tasks such as audio and video editing that require precise restorative actions.
- 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 agentic-vbench?
- When the focus is on generic performance evaluations rather than on real-world, task-specific benchmarks that assess handling complex post-production scenarios. If your budget or timeline cannot accommodate a per-task wall clock time of ~10 minutes and cost ranging from $0.10 to $2 based on agent token usage.
- Is agent-opt or agentic-vbench more popular on GitHub?
- agentic-vbench has more GitHub stars (96 vs 74). Stars measure visibility, not whether either tool fits your constraints.
- Are agent-opt and agentic-vbench open source?
- Yes - both are open-source projects on GitHub (agent-opt: Apache-2.0, agentic-vbench: Apache-2.0).
- Where can I find alternatives to agent-opt or agentic-vbench?
- GraphCanon lists graph-backed alternatives at agent-opt alternatives and agentic-vbench alternatives (agent-opt markdown twin, agentic-vbench 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 agentic-vbench?
- agent-opt: Steady. agentic-vbench: 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 agentic-vbench?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: agent-opt trust report; agentic-vbench trust report.