# Google Gemini API

## Kurzbeschreibung
**Google **offers a family of models with the Gemini API for text generation, reasoning, coding, agent workflows, tool use, multimodal prompts, and document-centric processing. 


For current API LLMs, Gemini 3.1 Pro Preview, Gemini 3 Flash Preview, Gemini 3.1 Flash-Lite Preview, Gemini 2.5 Pro, Gemini 2.5 Flash, and Gemini 2.5 Flash-Lite are particularly relevant. Older Gemini 2.0 Flash variants are still available, but are already marked as deprecated.

## Claim
LLM “AI for every developer”

## Geeignet für
- API Integration
- Automation / Workflows
- Data Analysis
- Data Extraction / Document Analysis
- Customer Service & Chatbots
- Programming / Software Development
- Research
- Texts / Content
- Translations
- Knowledge Management / Internal Search

## Kernfunktionen
- Audio
- Batch
- Context Caching
- Data Residency
- Embeddings
- Gemini API
- Grounding
- Live API
- Multimodal
- Text
- Tool Use
- VertexAI
- Video
- Vision

## Preismodell
- **free:** Free or unpaid use with limits; content may be used for product improvement and should not contain sensitive or confidential data.
- **other:** **Gemini API Paid Tier** For production applications with higher limits, context caching, Batch API, access to advanced models, and without using content for product improvement.


**Batch / Context Caching / Priority / Flex** Additional billing and operational options for controlling cost, latency, and throughput.


**Vertex AI / Google Cloud** Enterprise-oriented operation with Cloud DPA, IAM, regional endpoints, data residency, monitoring, and zero-data-retention configurations.


**Grounding / Tuning / Embeddings / Live API** Advanced features for search, context enrichment, model customization, vector search, real-time audio, and multimodal applications.

## DSGVO und Datenschutz
**Gesamteinschätzung:** Conditional

**Overall assessment of hosting & data: **

The Gemini API is a managed cloud API service for multimodal LLM applications with text, image, video, audio, embeddings, Live API, TTS, image generation, tool use, grounding, context caching, and batch processing. Local on-premises hosting of the Gemini models is not publicly documented as a standard option. Positive aspects include the free/paid tier, broad model range, paid-tier data controls, Vertex AI integration, regional data residency, zero-data-retention approaches in Vertex AI, and the Google Cloud DPA. A critical point is that the free tier may use data for product improvement, grounding functions have additional data rules, in-memory caching may be enabled by default, and some zero-retention goals require project-specific settings. 


**Conclusion: **

Gemini is very strong for multimodal, cloud-native, and Google-centric AI applications; for EU companies, the paid tier or Vertex AI with DPA, regional settings, disableable caching, and clear grounding rules should be preferred.


[Gemini API – Additional Terms](https://ai.google.dev/gemini-api/terms?hl=de) [Vertex AI and no data retention](https://docs.cloud.google.com/vertex-ai/generative-ai/docs/vertex-ai-zero-data-retention?hl=de)

**GDPR assessment:** From a GDPR perspective, the Gemini API depends heavily on the usage path: Google AI Studio/Gemini API Free Tier, Paid Tier, or Vertex AI. 


**Positive** is that Google states for Paid Services that prompts and responses are not used for product improvement and are processed in accordance with the Data Processing Addendum. For the Free Tier, however, the following applies: content and responses may be used to provide, improve, and develop Google products and ML technologies; human reviewers may examine API input and output, and Google explicitly warns against entering sensitive, confidential, or personal information into Unpaid Services. For the EEA/Switzerland/UK, the Gemini API Terms state: API clients for users in these regions may only use Paid Services. 


**Server location:** For Gemini Developer API Paid Services, prompts/responses may be temporarily stored or cached in countries where Google or its agents operate facilities for safety/abuse detection; with Vertex AI, data at rest remains in the selected location, and ML processing takes place for supported models in the chosen region or multi-region. Further link: Gemini API Terms, Gemini API Pricing, and Vertex AI Data Residency.


[Gemini API – Additional Terms](https://ai.google.dev/gemini-api/terms?hl=de) [Vertex AI and no data retention](https://docs.cloud.google.com/vertex-ai/generative-ai/docs/vertex-ai-zero-data-retention?hl=de)

## Hosting und Daten
- **On-Prem / lokales Hosting:** unknown
- **Private Cloud / Rechenzentrum:** teilweise / indirekt
- **EU SaaS / Managed:** teilweise / indirekt
- **Hybrid:** teilweise / indirekt
- **AVV / DPA:** abgedeckt
- **Kein Training auf Kundendaten:** teilweise / indirekt
- **Open-Source / Transparenz-Pfad:** unknown

## Herkunft
**Land:** USA

**Taxonomie:** USA

Global parent company: Google LLC, 1600 Amphitheatre Parkway, Mountain View, California 94043, United States.
For EMEA Gemini API Paid Services: Google Cloud EMEA Limited, 70 Sir John Rogerson’s Quay, Dublin 2, Ireland.

## Vorteile
- Very broad range from high-end reasoning to very low-cost high-volume processing.
- Strong combination of multimodality, coding, agents, grounding, tooling, and long context windows.
- Clear production pricing logic with Standard, Batch, Flex, and in some cases Priority.
- For Paid Services, prompts/responses are not used for product improvement according to the Terms.
- For enterprise environments via Vertex AI, there are stronger security/compliance options and regional processing models.

## Nachteile
- The portfolio is currently somewhat confusing because stable 2.5 models, 3.x previews, and deprecated 2.0 models coexist in parallel.
- For the direct Gemini API, data localization is documented less clearly than for Vertex AI; according to the Terms, for Paid Services logs may be stored transiently or cached in countries where Google or its agents operate facilities.
- The cheaper models are strong for volume and standard tasks, but not ideal for the most difficult analysis and precision use cases.
- Preview models may still change before GA and have more restrictive limits.

## Quellen
- Offizielle Website: https://ai.google.dev/gemini-api/docs/pricing?hl=de

## Letzter Datenstand
2026-04-17

## Originalseite
https://kifox.ai/en/ki-tools/google-gemini-api-en/