Comparison
agentdojo vs agentic-vbench
Verdict
Pick agentdojo if agentDojo serves as a benchmarking environment to evaluate security attacks, like prompt injection, and defenses for Large Language Model (LLM) agents; pick agentic-vbench if agenticVBench evaluates AI agents' real-world post-production capabilities with specific task prompts for activities like audio restoration.
Markdown twin · agentdojo alternatives · agentic-vbench alternatives
GraphCanon updated Sep 20, 2026
13views this month
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Trust & integrity
| Signal | agentdojo | agentic-vbench |
|---|---|---|
| Maintenance | Slowing (94d since push) As of Sep 5, 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 5, 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
- agentdojo
- A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents
- agentic-vbench
- A benchmark for evaluating AI agents in performing real-world post-production tasks like audio and video editing.
Stars
- agentdojo
- 802
- agentic-vbench
- 96
Forks
- agentdojo
- 205
- agentic-vbench
- 27
Open issues
- agentdojo
- 51
- agentic-vbench
- 37
Language
- agentdojo
- Python
- agentic-vbench
- Python
Adopt for
- agentdojo
- AgentDojo serves as a benchmarking environment to evaluate security attacks, like prompt injection, and defenses for Large Language Model (LLM) agents.
- agentic-vbench
- AgenticVBench evaluates AI agents' real-world post-production capabilities with specific task prompts for activities like audio restoration.
Persona
- agentdojo
- -
- agentic-vbench
- -
Runtime
- agentdojo
- -
- agentic-vbench
- -
License
- agentdojo
- MIT
- agentic-vbench
- Apache-2.0
Last pushed
- agentdojo
- Jun 2, 2026
- agentic-vbench
- Sep 2, 2026
Categories
- agentdojo
- AI Agents, Evaluation & Observability
- agentic-vbench
- AI Agents, Evaluation & Observability
Trust and health
Maintenance
- agentdojo
- Slowing (36%)
- agentic-vbench
- Very active (96%)
Days since push
- agentdojo
- 94d
- agentic-vbench
- 6d
Open issues (now)
- agentdojo
- 51
- agentic-vbench
- 37
Stars delta
- agentdojo
- +86 (30d)
- agentic-vbench
- +14 (30d)
Open issues delta
- agentdojo
- +10 (30d)
- agentic-vbench
- -20 (30d)
Full report
- agentdojo
- Trust report
- agentic-vbench
- Trust report
Shared compatibility
- Python · agentdojo: Python runtime · agentic-vbench: Python runtime
Choose agentdojo if…
- License: agentdojo is MIT, agentic-vbench is Apache-2.0.
- Pricing: Open-source under the MIT License. Some advanced features might require additional libraries or APIs..
- Requirements: Min 8 GB RAM.
- Tags unique to agentdojo: large-language-models, prompt-injection, security.
- AgentDojo serves as a benchmarking environment to evaluate security attacks, like prompt injection, and defenses for Large Language Model (LLM) agents.
When NOT to use agentdojo
- Last GitHub push was Jun 2, 2026 (slowing maintenance). Validate activity before betting a new project on agentdojo.
- AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism.
- Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers.
Choose agentic-vbench if…
- License: agentic-vbench is Apache-2.0, agentdojo is MIT.
- Requirements: Requires Docker; Install via scripts provided in the repository.; Python virtual environment setup for reproducibility..
- Tags unique to agentic-vbench: ai-agents, 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 (ethz-spylab/agentdojo) · observed Sep 20, 2026
- GitHub forks (ethz-spylab/agentdojo) · observed Sep 20, 2026
- Last push (ethz-spylab/agentdojo) · observed Jun 2, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 12, 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: agentdojo 802 · agentic-vbench 96 (synced Sep 20, 2026).
Common questions
- What is the difference between agentdojo and agentic-vbench?
- agentdojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents. 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 agentdojo over agentic-vbench?
- Choose agentdojo over agentic-vbench when License: agentdojo is MIT, agentic-vbench is Apache-2.0; Pricing: Open-source under the MIT License. Some advanced features might require additional libraries or APIs.; Requirements: Min 8 GB RAM; Tags unique to agentdojo: large-language-models, prompt-injection, security; AgentDojo serves as a benchmarking environment to evaluate security attacks, like prompt injection, and defenses for Large Language Model (LLM) agents.
- When should I choose agentic-vbench over agentdojo?
- Choose agentic-vbench over agentdojo when License: agentic-vbench is Apache-2.0, agentdojo is MIT; Requirements: Requires Docker; Install via scripts provided in the repository.; Python virtual environment setup for reproducibility.; Tags unique to agentic-vbench: ai-agents, 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 agentdojo?
- Last GitHub push was Jun 2, 2026 (slowing maintenance). Validate activity before betting a new project on agentdojo. AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Evaluation & Observability: Defer heavyweight eval infra only until you have real traffic - never skip it once users depend on answers.
- 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 agentdojo or agentic-vbench more popular on GitHub?
- agentdojo has more GitHub stars (802 vs 96). Stars measure visibility, not whether either tool fits your constraints.
- Are agentdojo and agentic-vbench open source?
- Yes - both are open-source projects on GitHub (agentdojo: MIT, agentic-vbench: Apache-2.0).
- Where can I find alternatives to agentdojo or agentic-vbench?
- GraphCanon lists graph-backed alternatives at agentdojo alternatives and agentic-vbench alternatives (agentdojo 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, agentdojo or agentic-vbench?
- agentdojo: Slowing. 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 agentdojo and agentic-vbench?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: agentdojo trust report; agentic-vbench trust report.