Gemini API Cookbook: fix(quickstarts): demonstrate client.models.get in Models notebook (#1356)
fix(quickstarts): demonstrate client.models.get in Models notebook (#1356) * fix(quickstarts): demonstrate client.models.get in Models notebook - Update quickstarts/Models.ipynb to use client.models.get(model='...') directly to retrieve model details, instead of filtering client.models.list().
Opening of the original on Gemini API Cookbook
Summary
Google Gemini updated its API cookbook to demonstrate a more direct method for retrieving model details. The change shows developers how to use `client.models.get(model='...')` instead of filtering a list of models. This simplifies the process for developers working with Gemini's models through its API.
Why it matters
This update refines the developer experience for Google Gemini. Previously, developers had to list all available models and then filter them to find specific details. The new `client.models.get()` method streamlines this, making it faster and easier to access information about a particular model. This benefits developers building applications with Gemini, offering a more efficient way to interact with the API. Competitors like OpenAI and Anthropic also provide direct methods for model introspection, making this change a step towards parity in developer tooling.
Related: OpenAI: Playco cut manual fixes 50% prototyping games with GPT-6 Astra · Anthropic: this JUST became the #1 AI model... · Microsoft: Gemini 3.8 Flash is now available in GitHub Copilot · Meta: Nvidia launches free tool that links idle computers into a personal AI data center · xAI: OpenAI cuts out SpaceX-owned Cursor
Access the Gemini API cookbook on GitHub. Locate the 'Models notebook' within the quickstarts directory. Run the code examples to see how `client.models.get()` retrieves specific model information directly.
Rated low: routine. Worth knowing, not worth rearranging your day for.
- Harness Engineering in LLM Tool Use via Agent-Native Reusable Tool PrimitivesarXiv cs.AI · Web · Sep 1, 2026
- Whose Assessment of Distress? Community Perspectives and LLM Alignment on Well-Being PostsarXiv cs.AI · Web · Aug 29, 2026
- Google releases Gemini 3.8 Flash, its third Flash model in six weeksArs Technica AI · Web · Sep 2, 2026
- AI News: OpenAI Made a Massive Move Against NVIDIAMatt Wolfe · Web · Aug 28, 2026
- Deals: Nothing Ear (3a) from $67, Galaxy Flip 8 $320 off, 2026 IdeaPad $620 off, Sony Google Gemini TV $800 off, more9to5Google · Web · Sep 2, 2026
- SIR: Self-improving Red-teaming for Compute Use AgentsarXiv cs.AI · Web · Aug 30, 2026
- Gemini API Cookbook: Notebook proposal: Hybrid File Search + Google Search grounding (#1338)Gemini API Cookbook
- Whose Assessment of Distress? Community Perspectives and LLM Alignment on Well-Being PostsarXiv cs.AI
- Planetary prediction engine: Automating global models via Earth AIGoogle Research Blog
- SIR: Self-improving Red-teaming for Compute Use AgentsarXiv cs.AI
- Pairing Google Antigravity with Gemini 3.7 Flash solves notable multi-agent math and engineering problems.The Keyword: Developers
- AI News: OpenAI Made a Massive Move Against NVIDIAMatt Wolfe
Questions people ask
- What changed in the Gemini API cookbook?
- The cookbook now demonstrates using `client.models.get(model='...')` to directly retrieve model details, replacing the older method of filtering `client.models.list()`.
- How does this affect developers?
- Developers can now get information about specific Gemini models more efficiently, simplifying their API interactions and code.
More from Gemini API Cookbook 29 more
Page generated Sep 3, 2026. Summaries are Subvolts' own; the story belongs to Gemini API Cookbook.