Claude Cookbooks vs OpenAI Cookbook
Which should you use? A side-by-side look at what each one does, who it suits, what it costs, how hard it is to set up, and where each falls short.
Open source · MIT
A set of Jupyter notebook recipes showing how to build with the Claude API.
Open source · MIT
Example code and guides for common tasks with the OpenAI API.
Our verdict
Both are free, MIT-licensed collections of Jupyter notebook examples, and they teach the same kind of thing for different AI providers. Claude Cookbooks shows how to use Anthropic's Claude API across tasks like tool use, retrieval, vision, and prompt caching. OpenAI Cookbook shows how to use OpenAI's API, and it is rated as the easier starting point for beginners. Pick based on which provider's API you plan to build with, since the code is specific to each.
Pick Claude Cookbooks if you are building with Anthropic's Claude API and want examples for tool use, retrieval, vision, or PDF handling.
Pick OpenAI Cookbook if you are building with the OpenAI API and want beginner-friendly, officially maintained examples to read and adapt.
| Key difference | Claude Cookbooks | OpenAI Cookbook |
|---|---|---|
| Model provider | Anthropic's Claude API | OpenAI API |
| Setup difficulty | Intermediate | Beginner |
| Covered tasks | Classification, RAG, tool use, vision, summarization, prompt caching, evaluations | Common tasks with the OpenAI API, shown as runnable notebooks |
| Account needed | Claude API access needed for examples; some recipes need third-party setup | OpenAI account and API key required; usage may incur costs |
| Community interest | 53.9k GitHub stars | 76.9k GitHub stars |
Written with AI from both products' catalogue entries · updated 2026-10-29
Who each one is for
Choose Claude Cookbooks if you need…
- Python developers who want working examples of Claude API calls
- Developers exploring tool use or retrieval augmented generation with Claude
- Teams evaluating how to add vision or PDF handling to an application
- People new to the Claude API who want to follow guided examples
Choose OpenAI Cookbook if you need…
- Developers who are new to the OpenAI API and want working examples
- Python programmers who want to see API usage patterns in notebook form
- Students or self-learners exploring how to build with language models
- Teams looking for reference code to adapt for their own projects
Side-by-side
| Claude Cookbooks | OpenAI Cookbook | |
|---|---|---|
| Type | Learning resource | Learning resource |
| Price | Free and open source | Free and open source |
| Licence | MIT | MIT |
| GitHub stars | 54.1k | 76.9k |
| Setup difficulty | Intermediate | Beginner |
| How you get it | Clone and build from source | Clone and build from source |
| Main language | Jupyter Notebook | Jupyter Notebook |
| Last code update | 7 days ago | 5 days ago |
What each one is
Claude Cookbooks
This repository is a collection of Jupyter notebooks and guides with copy-able code examples for using Claude, Anthropic's AI model, through its API. Each recipe covers a specific task, such as classification, retrieval augmented generation, tool use, vision, summarization, prompt caching, or automated evaluations. Developers use it as a starting point and adapt the snippets into their own projects.
OpenAI Cookbook
The OpenAI Cookbook is a collection of example code and written guides showing how to accomplish common tasks with the OpenAI API. Most examples are Jupyter notebooks written in Python, though the README notes the ideas can be applied in other languages. It is mainly useful as a set of working references you can read, run, and adapt.
Best for
Claude Cookbooks
- Python developers who want working examples of Claude API calls
- Developers exploring tool use or retrieval augmented generation with Claude
- Teams evaluating how to add vision or PDF handling to an application
- People new to the Claude API who want to follow guided examples
OpenAI Cookbook
- Developers who are new to the OpenAI API and want working examples
- Python programmers who want to see API usage patterns in notebook form
- Students or self-learners exploring how to build with language models
- Teams looking for reference code to adapt for their own projects
Strengths
Claude Cookbooks
- Covers many common tasks, from classification to vision to agents, in one place
- Code is meant to be copied and integrated into real projects
- Released under the MIT license, which permits reuse
OpenAI Cookbook
- Official examples maintained under the OpenAI organization
- Organized as runnable notebooks that show code and explanation together
- Released under the permissive MIT license
Not ideal for
Claude Cookbooks
- Non-programmers, since the recipes are code notebooks that assume coding knowledge
- People looking for a finished end-user app, because this is example code rather than a product
- Anyone needing non-Python examples, since the README says the code is primarily Python and other languages must be adapted
OpenAI Cookbook
- People without an OpenAI account or API key, since the examples require one (the README says a free account can be created)
- Non-programmers looking for a ready-made app, because this is a set of code examples rather than a finished product
- Developers who need a non-OpenAI model provider, since the material is specific to the OpenAI API
Trade-offs
Claude Cookbooks
- The README is short and does not list versions or detailed setup steps, so you must read each notebook for specifics
- Some recipes link to external repositories or third-party services that need their own accounts or setup
- Examples may reflect the Claude API at the time they were written, so check current docs before relying on them
OpenAI Cookbook
- Examples depend on an OpenAI account and API key, which may incur usage costs
- Most code is in Python, so other-language users must translate the concepts
- The README is short and does not describe a version schedule or release history
Getting started
Claude Cookbooks
Clone the repository
git clone https://github.com/anthropics/claude-cookbooksOpenAI Cookbook
Clone the repository
git clone https://github.com/openai/openai-cookbook.gitFrequently asked questions
Should I use Claude Cookbooks or OpenAI Cookbook?
Both are free, MIT-licensed collections of Jupyter notebook examples, and they teach the same kind of thing for different AI providers. Claude Cookbooks shows how to use Anthropic's Claude API across tasks like tool use, retrieval, vision, and prompt caching. OpenAI Cookbook shows how to use OpenAI's API, and it is rated as the easier starting point for beginners. Pick based on which provider's API you plan to build with, since the code is specific to each. Pick Claude Cookbooks if you are building with Anthropic's Claude API and want examples for tool use, retrieval, vision, or PDF handling. Pick OpenAI Cookbook if you are building with the OpenAI API and want beginner-friendly, officially maintained examples to read and adapt.
What is the difference between Claude Cookbooks and OpenAI Cookbook?
Claude Cookbooks: A set of Jupyter notebook recipes showing how to build with the Claude API. OpenAI Cookbook: Example code and guides for common tasks with the OpenAI API. Claude Cookbooks suits python developers who want working examples of claude api calls, while OpenAI Cookbook suits developers who are new to the openai api and want working examples.
Are Claude Cookbooks and OpenAI Cookbook free?
Claude Cookbooks: Free and open source. OpenAI Cookbook: Free and open source.
Which is easier to set up, Claude Cookbooks or OpenAI Cookbook?
OpenAI Cookbook is easier to get started with (rated beginner); Claude Cookbooks is rated intermediate and usually needs more setup.
Is Claude Cookbooks or OpenAI Cookbook more popular?
OpenAI Cookbook has more GitHub stars (76.9k) than Claude Cookbooks (54.1k). Popularity isn't the same as fit — check which one matches your use case above.
What are other alternatives to Claude Cookbooks and OpenAI Cookbook?
Other options people compare them with include LangChain, LlamaIndex, Semantic Kernel.
Keep comparing
Built from our catalogue entries for both products: open-source details come from each project's README (AI-assisted, refreshed weekly) and GitHub data; AI-tool details are editorial. Spotted something wrong? Let us know from either product's page.