--- title: "AI-For-Beginners vs gorilla" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/microsoft-ai-for-beginners-vs-shishirpatil-gorilla" tools: ["microsoft-ai-for-beginners", "shishirpatil-gorilla"] --- # AI-For-Beginners vs gorilla *GraphCanon updated Jul 11, 2026* ## Verdict Pick AI-For-Beginners when aI-For-Beginners is primarily Jupyter Notebook; gorilla is Python; pick gorilla when gorilla is primarily Python; AI-For-Beginners is Jupyter Notebook. [AI-For-Beginners](https://github.com/microsoft/AI-For-Beginners) reports 52k GitHub stars, 11k forks, and 4 open issues, last pushed Jul 8, 2026. [gorilla](https://gorilla.cs.berkeley.edu/) has 13k stars, 1.4k forks, and 264 open issues, last pushed Apr 13, 2026. Figures are from public GitHub metadata via [AI-For-Beginners's repository](https://github.com/microsoft/AI-For-Beginners) and [gorilla's repository](https://github.com/ShishirPatil/gorilla). | | [AI-For-Beginners](/tools/microsoft-ai-for-beginners.md) | [gorilla](/tools/shishirpatil-gorilla.md) | | --- | --- | --- | | Tagline | 12 Weeks, 24 Lessons, AI for All! | Training and Evaluating LLMs for Function Calls (Tool Calls) | | Stars | 52,098 | 12,940 | | Forks | 10,536 | 1,387 | | Open issues | 4 | 264 | | Language | Jupyter Notebook | Python | | Adopt for | - | Gorilla specializes in training and evaluating large language models (LLMs) to perform function calls or tool usages. | | Persona | - | - | | Runtime | - | - | | License | MIT | Gorilla can be used freely under the Apache 2.0 license for both academic and commercial purposes. | | Categories | Model Training, Vector Databases, Computer Vision | Model Training, Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [AI-For-Beginners](/tools/microsoft-ai-for-beginners.md) | [gorilla](/tools/shishirpatil-gorilla.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Steady (60%) | | Days since push | 2d | 89d | | Open issues (now) | 4 | 264 | | Owner type | Organization | User | | Security scan | 3 low (3 low) | No lockfile | | Full report | [trust report](/tools/microsoft-ai-for-beginners/trust.md) | [trust report](/tools/shishirpatil-gorilla/trust.md) | ## 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 AI-For-Beginners if… - AI-For-Beginners is primarily Jupyter Notebook; gorilla is Python. - License: AI-For-Beginners is MIT, gorilla is Apache-2.0. - Tags unique to AI-For-Beginners: deep-learning, microsoft-for-beginners, ai, artificial-intelligence. - Also covers Vector Databases, Computer Vision. ### Choose gorilla if… - gorilla is primarily Python; AI-For-Beginners is Jupyter Notebook. - License: gorilla is Apache-2.0, AI-For-Beginners is MIT. - Requirements: Gorilla works best with Python environments and requires installation through pip or local repository cloning.. - Tags unique to gorilla: llm, openai-functions, gpt-4-api, chatgpt. - 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 AI-For-Beginners - Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. - Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ## 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 AI-For-Beginners and gorilla? AI-For-Beginners: 12 Weeks, 24 Lessons, AI for All!. 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 AI-For-Beginners over gorilla? Choose AI-For-Beginners over gorilla when AI-For-Beginners is primarily Jupyter Notebook; gorilla is Python; License: AI-For-Beginners is MIT, gorilla is Apache-2.0; Tags unique to AI-For-Beginners: deep-learning, microsoft-for-beginners, ai, artificial-intelligence; Also covers Vector Databases, Computer Vision. ### When should I choose gorilla over AI-For-Beginners? Choose gorilla over AI-For-Beginners when gorilla is primarily Python; AI-For-Beginners is Jupyter Notebook; License: gorilla is Apache-2.0, AI-For-Beginners is MIT; Requirements: Gorilla works best with Python environments and requires installation through pip or local repository cloning.; Tags unique to gorilla: llm, openai-functions, gpt-4-api, chatgpt; 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 AI-For-Beginners? Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate. ### 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 AI-For-Beginners or gorilla more popular on GitHub? AI-For-Beginners has more GitHub stars (52,098 vs 12,940). Stars measure visibility, not whether either tool fits your constraints. ### Are AI-For-Beginners and gorilla open source? Yes - both are open-source projects on GitHub (AI-For-Beginners: MIT, gorilla: Apache-2.0). ### Where can I find alternatives to AI-For-Beginners or gorilla? GraphCanon lists graph-backed alternatives at [AI-For-Beginners alternatives](/tools/microsoft-ai-for-beginners/alternatives) and [gorilla alternatives](/tools/shishirpatil-gorilla/alternatives) ([AI-For-Beginners markdown twin](/tools/microsoft-ai-for-beginners/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/microsoft-ai-for-beginners-vs-shishirpatil-gorilla.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, AI-For-Beginners or gorilla? AI-For-Beginners: Very active. gorilla: 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 AI-For-Beginners and gorilla? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [AI-For-Beginners trust report](/tools/microsoft-ai-for-beginners/trust); [gorilla trust report](/tools/shishirpatil-gorilla/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=microsoft-ai-for-beginners`](/api/graphcanon/graph?tool=microsoft-ai-for-beginners) - 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/_