Search Central LiveDeep Dive Europe 2026

Knowledge base v2.13.0 · Community edition · data through 2 October 2026

Thing · Product

Gemini

Google's family of AI models and the assistant app built on them; Gemini models also power AI features in Search and Google Trends.

ProductAlso calledGemini app, Gemini apps, Gemini models

Open in Reef mapOpen in Graph

Narrative see the topic Gemini and Search

Claims
41
In Google’s docs
7
Said at the event
25
Not in docs
10
Kit items
8

Google’s documentation 7

Documented in

DocsSourceD2-C771

Google announced Nano Banana, a new image editing model from Google DeepMind in the Gemini app, on 26 August 2025.

Google blog (26 August 2025) · Day 2 · Google Trends

DocsSourceD3-C094

Google's Gemini API documentation on grounding with Google Search says the model automatically generates and runs one or more search queries when needed, and the response lists the search queries it executed.

Google AI for Developers (Gemini API docs) · Day 3 · Making sense of users' queries

Said at the event 25

Slide and stage claims that name it, the ones Google’s documentation does not cover first.

Not in docs 10

StageNot in docsD1-C162

Google said that after the launch of Nano Banana, its image generation model, the Gemini app became the number one app in the app store in 2025.

Lino Cattaruzzi · Day 1 · Welcome and opening keynotes

StageNot in docsD1-C335

Crawling for Gemini may be set to care less about quality and more about the amount of content, because for large language models the number of tokens matters more than quality.

Gary Illyes · Day 1 · How crawling works

StageNot in docsD2-C118

To train Gemini models, Google renders every page just as it does for Search, so a page that renders correctly for Search also works for Gemini training, provided the site allows its content to be used for training.

Erin Sparling · Day 2 · Lightning session D: Rendering and JavaScript

StageNot in docsD2-C120

When a Gemini user asks about a specific web page (for example, whether it says anything about the ruby HTML tag), the page is read at that moment rather than during crawling and may be used to ground the answer, which takes extra time.

Erin Sparling · Day 2 · Lightning session D: Rendering and JavaScript

StageNot in docsD2-C825

Gary Illyes added that, once chunk size is thought of in millions of tokens as Gemini's context window allows, chunking has perhaps lost its meaning anyway.

Gary Illyes · Day 2 · Understanding what's on a page

StageNot in docsD2-C770

Google attributed the September 2025 surge in worldwide search interest for Gemini to the viral launch of Nano Banana (the image editing model in the Gemini app), as people searched for both Gemini and Nano Banana.

Omri Weisman · Day 2 · Google Trends

StageNot in docsD2-C773

After the Nano Banana surge faded, worldwide baseline search interest in Gemini stayed much higher than before, which Google read as a sustained gain in brand recognition.

Omri Weisman · Day 2 · Google Trends

Consistent with docs 12

StageConsistent with docsD1-C496

Google said that last year (2025) it delivered a decade of innovation in 12 months, with its new Gemini model at the top of all the benchmarks.

Lino Cattaruzzi · Day 1 · Welcome and opening keynotes

StageConsistent with docsD1-C522

Google said a site can keep a directory or the whole site out of Gemini model training by disallowing it for the Google-Extended token in robots.txt, and that Google respects that policy; the speaker believed Google was the first to offer such an opt-out from model training.

Day 1 · How Google interprets robots.txt

StageConsistent with docsD2-C869

Right after saying Gemini's context window holds millions of tokens, Gary Illyes put its size at perhaps 900,000 or even closer to a million, without a unit that the recordings capture.

Gary Illyes · Day 2 · Understanding what's on a page

Confirmed by docs 1

StageConfirmed by docsD1-C163

Google described a full-stack approach to AI, from its own TPU chips for AI inference through research and frontier models such as Gemini to its apps.

Lino Cattaruzzi · Day 1 · Welcome and opening keynotes

Nothing to verify 2

StageD2-C951

A community speaker named the limits of the title-based alt-text script: it rewrites only the hero image, assumes the page title states the user's intent, had been tested in only one language or market, and runs on the free Gemini model.

Day 2 · Lightning session F: Media

StageD3-C187

Google's quality talk showed a surface-level example article (not photographed) that the speaker said Gemini could have generated, while stressing that humans have written such content for a long time too.

Day 3 · How Google thinks about Quality

Press and analysis 9

AnalysisD1-C486

The panel spoke of blocking Google's 'AI crawling or training' with Google-Extended, but Google documents Google-Extended as a usage token, not a crawler: disallowing it does not stop Googlebot fetching pages and only controls use for Gemini training and grounding.

Ibrahim Anjro · Day 1 · Q&A

AnalysisD2-C329

Day 1's slide said Gemini shares technologies such as tokenization with Search, while on Day 2 Gary Illyes showed that the two tokenizers split the same text differently ('or mostly'); read this as a shared processing step with different outputs, so Search's word tokens and Gemini's sub-word tokens are not the same units.

Ibrahim Anjro · Day 2 · Understanding what's on a page

AnalysisD2-C333

Do not rewrite pages into short, self-contained chunks for AI systems; Google says Gemini reads context windows of millions of tokens, so structure content for readers, with clear headings and complete explanations.

Ibrahim Anjro · Day 2 · Understanding what's on a page

AnalysisD2-C872

The talk gave Gemini's context window both as millions of tokens and as roughly 900,000 to a million; Google's long-context docs say Gemini models have context windows of 1 million or more tokens (about eight average novels per million), so plan with about one million tokens as the documented floor rather than several million.

Ibrahim Anjro · Day 2 · Understanding what's on a page

AnalysisD2-C772

On stage the Nano Banana launch was placed in September 2025, but Google announced it on 26 August 2025, so the September 2025 surge in Gemini search interest described in the talk came in the weeks after the launch.

Ibrahim Anjro · Day 2 · Google Trends

Built on these claims 8

Kit items about Gemini: their own words name it, or several of the claims they rest on do.

Developer requirements 3

Myths 1

Also inglossary terms Google-Extended, Grounding, SpamBrain, Web Guide

Connected things 21

Relations

  • Affected by Google-Extended
    3 claims, 3 documented
    • DocsSourceD1-C086

      Google-Extended is a control token, not a crawler with its own user agent string. It decides whether crawled content may be used to train future Gemini models and to ground Gemini apps and Vertex AI.

    • StageConsistent with docsD1-C522

      Google said a site can keep a directory or the whole site out of Gemini model training by disallowing it for the Google-Extended token in robots.txt, and that Google respects that policy; the speaker believed Google was the first to offer such an opt-out from model training.

    • DocsSourceD2-C121

      Google's crawler documentation defines grounding in Gemini Apps and in Grounding with Google Search on Vertex AI as providing content from the Google Search index to the model at prompt time, and sites manage whether their content is used for it with the Google-Extended robots.txt token.

Most often named with it

Things named in the same claim, with the number of claims they share.

4 more things

Topics that feature it