--- title: "agentdojo vs habitat-lab" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/ethz-spylab-agentdojo-vs-facebookresearch-habitat-lab" tools: ["ethz-spylab-agentdojo", "facebookresearch-habitat-lab"] --- # agentdojo vs habitat-lab *GraphCanon updated Aug 5, 2026* ## 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 habitat-lab if habitat-Lab is a Python library for training embodied AI agents in virtual environments through deep and reinforcement learning techniques. [agentdojo](https://agentdojo.spylab.ai/) reports 716 GitHub stars, 188 forks, and 41 open issues, last pushed Jun 2, 2026. [habitat-lab](https://aihabitat.org/) has 3.1k stars, 684 forks, and 388 open issues, last pushed May 7, 2026. Figures are from public GitHub metadata via [agentdojo's repository](https://github.com/ethz-spylab/agentdojo) and [habitat-lab's repository](https://github.com/facebookresearch/habitat-lab). | | [agentdojo](/tools/ethz-spylab-agentdojo.md) | [habitat-lab](/tools/facebookresearch-habitat-lab.md) | | --- | --- | --- | | Tagline | A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents | A modular high-level library to train embodied AI agents | | Stars | 716 | 3,082 | | Forks | 188 | 684 | | Open issues | 41 | 388 | | Language | Python | Python | | Adopt for | AgentDojo serves as a benchmarking environment to evaluate security attacks, like prompt injection, and defenses for Large Language Model (LLM) agents. | Habitat-Lab is a Python library for training embodied AI agents in virtual environments through deep and reinforcement learning techniques. | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | AI Agents, Evaluation & Observability | AI Agents, Computer Vision | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agentdojo](/tools/ethz-spylab-agentdojo.md) | [habitat-lab](/tools/facebookresearch-habitat-lab.md) | | --- | --- | --- | | Days since push | 63d | 84d | | Open issues (now) | 41 | 388 | | Full report | [trust report](/tools/ethz-spylab-agentdojo/trust.md) | [trust report](/tools/facebookresearch-habitat-lab/trust.md) | ## Shared compatibility - **Python**: [agentdojo](/tools/ethz-spylab-agentdojo.md) - Python runtime; [habitat-lab](/tools/facebookresearch-habitat-lab.md) - Python runtime ## Decision facts: agentdojo - **Pricing:** freemium - Open-source under the MIT License. Some advanced features might require additional libraries or APIs. - **Requirements:** Min 8 GB RAM - **Adopt for:** AgentDojo serves as a benchmarking environment to evaluate security attacks, like prompt injection, and defenses for Large Language Model (LLM) agents. ## Decision facts: habitat-lab - **Requirements:** Min 8 GB RAM; Requires Docker; Python >=3.9 is required along with cmake>=3.14 for installation; For users working on machines equipped with NVIDIA GPUs, nvidia-docker installation is necessary to run the provided Docker containers - **Adopt for:** Habitat-Lab is a Python library for training embodied AI agents in virtual environments through deep and reinforcement learning techniques. ## Choose when ### Choose agentdojo if… - 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: benchmark, large language models, prompt-injection, security. - Also covers Evaluation & Observability. - AgentDojo serves as a benchmarking environment to evaluate security attacks, like prompt injection, and defenses for Large Language Model (LLM) agents. ### Choose habitat-lab if… - Requirements: Min 8 GB RAM; Requires Docker; Python >=3.9 is required along with cmake>=3.14 for installation; For users working on machines equipped with NVIDIA GPUs, nvidia-docker installation is necessary to run the provided Docker containers. - Tags unique to habitat-lab: ai, computer-vision, deep-learning, reinforcement-learning. - Also covers Computer Vision. - habitat-lab ships Docker support for self-hosted deployment. - Use Habitat-Lab when your project requires the simulation of complex environments for embodied AI tasks, such as navigation and interaction with objects ## When NOT to use 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 NOT to use habitat-lab - Avoid Habitat-Lab if the computational resources required for running the simulations exceed what is available or feasible in terms of cost - Do not use Habitat-Lab when the project is solely focused on real-world data and does not necessitate virtual training environments, as setting up such a library might add unnecessary complexity ## Common questions ### What is the difference between agentdojo and habitat-lab? agentdojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents. habitat-lab: A modular high-level library to train embodied AI agents. See the comparison table for live GitHub stats and shared categories. ### When should I choose agentdojo over habitat-lab? Choose agentdojo over habitat-lab when 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: benchmark, large language models, prompt-injection, security; Also covers Evaluation & Observability; 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 habitat-lab over agentdojo? Choose habitat-lab over agentdojo when Requirements: Min 8 GB RAM; Requires Docker; Python >=3.9 is required along with cmake>=3.14 for installation; For users working on machines equipped with NVIDIA GPUs, nvidia-docker installation is necessary to run the provided Docker containers; Tags unique to habitat-lab: ai, computer-vision, deep-learning, reinforcement-learning; Also covers Computer Vision; habitat-lab ships Docker support for self-hosted deployment; Use Habitat-Lab when your project requires the simulation of complex environments for embodied AI tasks, such as navigation and interaction with objects. ### When should I avoid 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 habitat-lab? Avoid Habitat-Lab if the computational resources required for running the simulations exceed what is available or feasible in terms of cost Do not use Habitat-Lab when the project is solely focused on real-world data and does not necessitate virtual training environments, as setting up such a library might add unnecessary complexity ### Is agentdojo or habitat-lab more popular on GitHub? habitat-lab has more GitHub stars (3,082 vs 716). Stars measure visibility, not whether either tool fits your constraints. ### Are agentdojo and habitat-lab open source? Yes - both are open-source projects on GitHub (agentdojo: MIT, habitat-lab: MIT). ### Where can I find alternatives to agentdojo or habitat-lab? GraphCanon lists graph-backed alternatives at [agentdojo alternatives](/tools/ethz-spylab-agentdojo/alternatives) and [habitat-lab alternatives](/tools/facebookresearch-habitat-lab/alternatives) ([agentdojo markdown twin](/tools/ethz-spylab-agentdojo/alternatives.md), [habitat-lab markdown twin](/tools/facebookresearch-habitat-lab/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/ethz-spylab-agentdojo-vs-facebookresearch-habitat-lab.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agentdojo or habitat-lab? agentdojo: Steady. habitat-lab: 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 agentdojo and habitat-lab? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agentdojo trust report](/tools/ethz-spylab-agentdojo/trust); [habitat-lab trust report](/tools/facebookresearch-habitat-lab/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=ethz-spylab-agentdojo`](/api/graphcanon/graph?tool=ethz-spylab-agentdojo) - 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/_