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Google Gemini

The multimodal AI for file, image and audio analysis.

Gemini by Google is the model I reach for when it comes to multimodality: understanding files, images and audio, plus AI-assisted image generation via Nano Banana. Very large context windows and deep Google Cloud integration make it a strong tool for data-intensive work.

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What is Gemini

Gemini and Google DeepMind in brief

Gemini is Google's family of AI models, developed by Google DeepMind. Unlike purely text-based models, Gemini is natively multimodal from the ground up - text, code, images, audio and video are processed within the same model rather than stitched together afterwards.

For practical use, what matters most is the combination of a very large context window and tight Google Cloud integration. Gemini 3 Pro processes up to one million tokens of input in a single call - enough to take in extensive documents, long videos or entire datasets at once.

Natively multimodal

Text, image, audio and video are processed within the same model - the basis for genuine understanding of mixed content.

Very large context window

Up to one million tokens of input with Gemini 3 Pro - extensive documents and long media can be processed in a single pass.

Google Cloud integration

Via Vertex AI, Gemini integrates cleanly into existing Google Cloud environments - including EU regions.

Why I use Gemini

My reasons for Gemini

Gemini is not a replacement for me but a deliberate complement: wherever it comes to understanding media and to image generation, it is my tool of choice. The following points come from real day-to-day work.

File and document analysis

Thanks to the large context window, extensive files and documents can be taken in and evaluated in one piece - without tedious chunking.

Image and audio understanding

Gemini analyses images and audio natively. For tasks such as image description, content classification or transcription, this is a real advantage.

AI image generation via Nano Banana

With Nano Banana - Google's image model built on Gemini - I create images with high fidelity, legible text and consistent subjects across multiple steps.

Cloud integration

Via Vertex AI, Gemini fits into Google Cloud architectures - including EU data processing for privacy-sensitive projects.

„When it comes to understanding files, images and audio, I reach for Gemini - multimodality is the decisive difference here.“

Current models

The Gemini model family

From fast agentic work to deep multimodal reasoning - the right model for every task.

Gemini 3.5 Flash

Current

Fast, agentic and strong at coding.

  • Generally available since Google I/O (19 May 2026)
  • Default model in the Gemini app and the Gemini API
  • Beats Gemini 3.1 Pro on several coding and agentic benchmarks
  • For fast, agentic workflows

Gemini 3 Pro

Reasoning

Deep multimodal reasoning for complex tasks.

  • Released on 18 November 2025
  • Context window: up to 1 million tokens of input
  • Maximum output: 64,000 tokens
  • Natively multimodal across text, code, image, audio and video

Gemini Omni

Multimodal

Conversational generation across media.

  • Unveiled at Google I/O 2026
  • Combines text, images, audio and video
  • First model: Gemini Omni Flash
  • Available to paid Gemini subscribers
Up to date

I stay close to the model landscape

Google's model cycle is fast. At Google I/O 2026 (19 May 2026), Gemini 3.5 Flash became generally available and the default model - faster and, on many benchmarks, better than the previous Gemini 3.1 Pro. At the same time, Gemini Omni was introduced, a new multimodal model that can be combined with Nano Banana and Veo. For me that means: I test new models before adopting them in projects and deliberately pick the version that fits the task.

Gemini 3.5 Pro was announced for June 2026 - a fixed date was still pending at the time of this page.

GDPR & use in projects

GDPR-compliant use

For European businesses, GDPR is the central test when choosing an AI provider. Gemini can be used compliantly - with the right prerequisites via Google Cloud.

Via Vertex AI, Gemini can be run with EU data residency: processing stays within the EU region, and a data processing agreement under Article 28 GDPR is part of the Google Cloud terms. For sensitive data I therefore use access via Vertex AI EU rather than the consumer app.

EU data residency via Vertex AI

Via Vertex AI, processing can be pinned to EU regions - the data does not leave the EU geography.

DPA via Google Cloud

A data processing agreement under Article 28 GDPR is part of the Google Cloud contractual terms.

Clean documentation

Clear rules on which data ever enters a prompt - complemented by a documented data protection assessment.

FAQ

Frequently asked questions about Gemini

Answers to the most important questions on model choice, data protection and use.

What do you use Gemini for?
Mainly for multimodal tasks: analysing files, images and audio, as well as AI-assisted image generation via Nano Banana. Wherever mixed content needs to be understood or large amounts of data need to be processed in one piece, Gemini plays to its strengths.
What is the advantage of the large context window?
Gemini 3 Pro processes up to one million tokens of input in a single call. This means extensive documents, long videos or entire datasets can be taken in at once, without having to laboriously split them into small parts.
Can Gemini be used in a GDPR-compliant way?
Yes, with the right prerequisites via Google Cloud. Via Vertex AI, Gemini can be run with EU data residency so that processing stays within the EU region. A data processing agreement under Article 28 GDPR is part of the Google Cloud terms. For sensitive data, access via Vertex AI EU rather than the consumer app is recommended.
What is Nano Banana?
Nano Banana is Google's image generation model built on Gemini. The Pro variant produces images with high fidelity, can render legible text and keeps subjects consistent across multiple editing steps. I use it for AI-assisted image creation in projects.
Why Gemini and not another AI model?
It is not an either-or. For demanding code and reasoning tasks I rely on Claude; for multimodal work - file, image and audio analysis as well as image generation - Gemini is the right tool. I pick the model with the best fit for each task.

Want to use Gemini in your business?

In a free initial consultation we look together at where AI creates the most value for you - from model choice through integration to GDPR-compliant implementation.

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