--- title: "JOOD vs gorilla" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/naver-ai-jood-vs-shishirpatil-gorilla" tools: ["naver-ai-jood", "shishirpatil-gorilla"] --- # JOOD vs gorilla *GraphCanon updated Aug 8, 2026* ## Verdict Pick JOOD if jOOD is an implementation for exploring strategies to jailbreak language and multimodal models using out-of-distribution inputs. It leverages Python and is licensed under Apache-2.0; pick gorilla if gorilla specializes in training and evaluating large language models (LLMs) to perform function calls or tool usages. [JOOD](https://github.com/naver-ai/JOOD) reports 21 GitHub stars, 4 forks, and 2 open issues, last pushed Jun 11, 2025. [gorilla](https://gorilla.cs.berkeley.edu/) has 13k stars, 1.4k forks, and 272 open issues, last pushed Apr 13, 2026. Figures are from public GitHub metadata via [JOOD's repository](https://github.com/naver-ai/JOOD) and [gorilla's repository](https://github.com/ShishirPatil/gorilla). | | [JOOD](/tools/naver-ai-jood.md) | [gorilla](/tools/shishirpatil-gorilla.md) | | --- | --- | --- | | Tagline | Implementation for multimodal LLM jailbreaking strategy | Training and Evaluating LLMs for Function Calls (Tool Calls) | | Stars | 21 | 12,988 | | Forks | 4 | 1,397 | | Open issues | 2 | 272 | | Language | Python | Python | | Adopt for | JOOD is an implementation for exploring strategies to jailbreak language and multimodal models using out-of-distribution inputs. It leverages Python and is licensed under Apache-2.0. | Gorilla specializes in training and evaluating large language models (LLMs) to perform function calls or tool usages. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Gorilla can be used freely under the Apache 2.0 license for both academic and commercial purposes. | | Categories | Computer Vision, Model Training | Evaluation & Observability, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [JOOD](/tools/naver-ai-jood.md) | [gorilla](/tools/shishirpatil-gorilla.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Slowing (36%) | | Days since push | 419d | 117d | | Open issues (now) | 2 | 272 | | Owner type | Organization | User | | Full report | [trust report](/tools/naver-ai-jood/trust.md) | [trust report](/tools/shishirpatil-gorilla/trust.md) | ## Shared compatibility - **Python**: [JOOD](/tools/naver-ai-jood.md) - Python runtime; [gorilla](/tools/shishirpatil-gorilla.md) - Python runtime ## Decision facts: JOOD - **Requirements:** Python version to install requirements: Python >= 3.12.7; The package list for dependencies should be sourced from the `requirements.txt` file provided in the repository. - **Adopt for:** JOOD is an implementation for exploring strategies to jailbreak language and multimodal models using out-of-distribution inputs. It leverages Python and is licensed under Apache-2.0. ## Decision facts: gorilla - **Pricing:** freemium - **Requirements:** Gorilla works best with Python environments and requires installation through pip or local repository cloning. - **Adopt for:** Gorilla specializes in training and evaluating large language models (LLMs) to perform function calls or tool usages. - **License detail:** Gorilla can be used freely under the Apache 2.0 license for both academic and commercial purposes. ## Choose when ### Choose JOOD if… - Requirements: Python version to install requirements: Python >= 3.12.7; The package list for dependencies should be sourced from the `requirements.txt` file provided in the repository.. - Tags unique to JOOD: jailbreaking, multimodal-llms. - Also covers Computer Vision. - Use JOOD when you need to explore how a multimodal model behaves with unforeseen or out-of-distribution inputs, thus pushing the boundaries of its conventional responses or outputs. ### Choose gorilla if… - Requirements: Gorilla works best with Python environments and requires installation through pip or local repository cloning.. - Tags unique to gorilla: api, chatgpt, claude-api, gpt-4-api. - Also covers Evaluation & Observability. - You should consider using Gorilla if you need a comprehensive framework for developing LLMs capable of leveraging external functions effectively. ## When NOT to use JOOD - Avoid using JOOD if jailbreaking strategies are not of interest, such as in scenarios requiring strict adherence to model limitations and ethical constraints. - JOOD may not be suitable if you require tools that focus on improving performance or stability of models rather than exploring unconventional behavior or vulnerabilities. ## When NOT to use gorilla - Avoid Gorilla if your primary focus is not on function calling or tool usage capabilities for LLMs; another model-specific framework may better fit your needs. - If the lack of a direct comparison tool to other models' function-calling performance is critical in your decision process, and you find no suitable alternatives listed on their leaderboard. ## Common questions ### What is the difference between JOOD and gorilla? JOOD: Implementation for multimodal LLM jailbreaking strategy. gorilla: Training and Evaluating LLMs for Function Calls (Tool Calls). See the comparison table for live GitHub stats and shared categories. ### When should I choose JOOD over gorilla? Choose JOOD over gorilla when Requirements: Python version to install requirements: Python >= 3.12.7; The package list for dependencies should be sourced from the `requirements.txt` file provided in the repository.; Tags unique to JOOD: jailbreaking, multimodal-llms; Also covers Computer Vision; Use JOOD when you need to explore how a multimodal model behaves with unforeseen or out-of-distribution inputs, thus pushing the boundaries of its conventional responses or outputs. ### When should I choose gorilla over JOOD? Choose gorilla over JOOD when Requirements: Gorilla works best with Python environments and requires installation through pip or local repository cloning.; Tags unique to gorilla: api, chatgpt, claude-api, gpt-4-api; Also covers Evaluation & Observability; You should consider using Gorilla if you need a comprehensive framework for developing LLMs capable of leveraging external functions effectively. ### When should I avoid JOOD? Avoid using JOOD if jailbreaking strategies are not of interest, such as in scenarios requiring strict adherence to model limitations and ethical constraints. JOOD may not be suitable if you require tools that focus on improving performance or stability of models rather than exploring unconventional behavior or vulnerabilities. ### When should I avoid gorilla? Avoid Gorilla if your primary focus is not on function calling or tool usage capabilities for LLMs; another model-specific framework may better fit your needs. If the lack of a direct comparison tool to other models' function-calling performance is critical in your decision process, and you find no suitable alternatives listed on their leaderboard. ### Is JOOD or gorilla more popular on GitHub? gorilla has more GitHub stars (12,988 vs 21). Stars measure visibility, not whether either tool fits your constraints. ### Are JOOD and gorilla open source? Yes - both are open-source projects on GitHub (JOOD: Apache-2.0, gorilla: Apache-2.0). ### Where can I find alternatives to JOOD or gorilla? GraphCanon lists graph-backed alternatives at [JOOD alternatives](/tools/naver-ai-jood/alternatives) and [gorilla alternatives](/tools/shishirpatil-gorilla/alternatives) ([JOOD markdown twin](/tools/naver-ai-jood/alternatives.md), [gorilla markdown twin](/tools/shishirpatil-gorilla/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/naver-ai-jood-vs-shishirpatil-gorilla.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, JOOD or gorilla? JOOD: Dormant. gorilla: Slowing. 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 JOOD and gorilla? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [JOOD trust report](/tools/naver-ai-jood/trust); [gorilla trust report](/tools/shishirpatil-gorilla/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=naver-ai-jood`](/api/graphcanon/graph?tool=naver-ai-jood) - 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/_