Google Gemini Cookbook
Official collection of guides, quickstarts, and Jupyter notebooks from Google for building with the Gemini API. Covers multimodal prompting, function calling, grounding with Google Search, context caching, audio/video understanding, and agent patterns.
About Gemini Cookbook
Official collection of guides, quickstarts, and Jupyter notebooks from Google for building with the Gemini API. Covers multimodal prompting, function calling, grounding with Google Search, context caching, audio/video understanding, and agent patterns.
Key Capabilities
Official Google resource — maintained by the Gemini team with model-specific examples
Best-in-class multimodal examples — image, audio, video, and PDF understanding in one API
Grounding with Google Search for real-time factual accuracy in LLM responses
Context caching for cost-efficient long-context applications (up to 2M tokens)
Function calling and agent patterns with working Jupyter notebooks
Standout Features
Multimodal Examples
Image, audio, video, and PDF understanding examples — Gemini's strongest differentiator with working notebook code.
Grounding with Google Search
Connect Gemini responses to real-time web data via Google Search grounding for factual accuracy.
Context Caching
Cache long contexts (up to 2M tokens) to reduce costs and latency for repeated queries against large documents.
Perfect for
Google Gemini Cookbook Review 2026: Vibe Coding Tool Guide & Comparison
Hands-on Google Gemini Cookbook review covering Gemini API examples, agent patterns, multimodal features, search grounding, and comparisons to Claude and OpenAI Cookbooks.
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