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.
Google Gemini API
LLM “AI for every developer”
Location: 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.
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.
Target audience
The Gemini API is aimed primarily at developers, start-ups, agency teams, internal automation and product teams, as well as companies that want to build their own LLM-powered applications. Google positions Gemini very clearly for API integration, app building, coding support, agentic workflows, and multimodal applications. Thanks to the tiering from Flash-Lite to Pro, the platform is suitable both for cost-sensitive mass processing and for more demanding reasoning and coding use cases.
Outstanding features
The most striking strengths lie in the combination of multimodality, agent/grounding capabilities, long context windows, tiered pricing, and close integration with Google’s developer and cloud ecosystem. Particularly interesting is the current three-part split: Gemini 3.1 Pro Preview for maximum intelligence and difficult tasks, Gemini 3 Flash Preview for fast, high-quality all-round workloads, and Gemini 3.1 Flash-Lite Preview for high volumes, translation, and simple data processing. Alongside these, the 2.5 models remain the more stable alternatives for everyday API use.
Key application areas
Gemini is particularly well suited for coding, agent workflows, document processing, translation, classification/extraction, internal knowledge systems, chatbots, research-supported applications, and multimodal business workflows. Google’s Vertex AI introduction cites, among other things, advanced reasoning, multiturn chat, code generation, and multimodal prompts; the model descriptions specifically add translation, simple data processing, high-volume agentic tasks, and complex coding/reasoning use cases.
Usage & notes
Operationally, you typically start with Google AI Studio and then migrate production applications to the Gemini API or, where higher governance requirements apply, to Vertex AI. For new projects, it makes sense to consciously weigh Preview models against Stable models: Preview models are often more powerful or more up to date, but they can still change. From a data protection perspective, you should also distinguish very carefully between Free/Unpaid, Paid, and Vertex AI Enterprise, because this results in relevant differences in product improvement, logging, DPA, and regional processing.
| Target audience | Assessment |
|---|---|
| Developers / product teams | Very suitable – for multimodal apps with text, image, video, audio, tool use, embeddings, and live/voice features. |
| Google Cloud teams | Very suitable – especially if Google Cloud, Vertex AI, Workspace, or BigQuery are already in use. |
| SaaS providers / startups | Suitable – thanks to the Free Tier, Paid Tier, wide model variety, and easy API integration. |
| SMEs / enterprises | Suitable to very suitable – especially via Paid Tier or Vertex AI with DPA, data controls, and regional options. |
| EU companies | Conditionally to well suited – Paid Services and Vertex AI setups are significantly easier to control than pure Free Tier usage. |
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Gemini 3.1 Pro Preview
Best suited for:
Complex reasoning, difficult coding tasks, agentic workflows with precise tool use, demanding multimodal analysis
Gemini 3 Flash Preview
Best suited for:
Fast, high-quality all-round apps, agentic work, multimodal understanding, coding-adjacent production systems with a good price-performance ratio
Gemini 3.1 Flash-Lite Preview
Best suited for:
High-volume agents, simple extraction, translation, extremely low latency, cheap production pipelines
Gemini 2.5 Pro
Best suited for:
Complex problems in code, mathematics, STEM, analysis of large datasets, codebases, and documents with long context
Gemini 2.5 Flash
Best suited for:
Productive standard applications, large processing loads, low latency, agentic use cases when reasoning is needed
Gemini 2.5 Flash-Lite
Best suited for:
Classification, simple data extraction, routing, very inexpensive fast pipelines, cost-critical standard tasks
Gemini 2.0 Flash
Best suited for:
Only for existing migrations or legacy setups that have not yet been switched over
Gemini 2.0 Flash-Lite
Best suited for:
Only for legacy workloads with an extremely simple scope
Hosting & Data
1) On-prem / local hosting
Meaning: The company operates the solution on its own hardware or within its own infrastructure. In the strictest sense, not only the application runs locally, but ideally the model as well.
2) Private cloud / data center
Meaning: The solution runs in a dedicated or more clearly separated cloud environment, often with a hosting provider or hyperscaler, but in a German data center or in a particularly controlled environment.
3) EU SaaS / managed
Meaning: The provider operates the solution itself as a service. The company uses the tool as a ready-made cloud service, ideally with EU data residency.
4) Hybrid
Meaning: One part of the processing remains internal / local / in a private cloud, while another part runs in an external cloud or EU SaaS.
5) AVV / DPA
Meaning: This is the data processing agreement or Data Processing Addendum. It governs that the provider processes personal data on behalf of the customer and is bound by the customer's instructions.
6) No training
Meaning: The provider does not use your prompts, uploads, attachments, chat histories, or outputs for training or improving the general model — ideally excluded by contract.
7) Open-source / transparency path
Meaning: There is a path toward greater technical transparency and sovereignty, for example through:
- open models
- documented components
- self-hostable parts
- traceable architecture
- export / switching options
| On-prem / local hosting | ❓ |
| Private cloud / data center | ⚠️ |
| EU SaaS / Managed | ⚠️ |
| Hybrid | ❓ |
| DPA / AVV | ✅ |
| No training on customer data | ⚠️ |
| Open source / transparency path | ⚠️ |
On-prem / local hosting: indirect / not available
The website does not specify any on-premises or self-hosting options for the Gemini API itself. The API is described as a hosted service.
Private Cloud / Data Center: Partially
The website refers to use via cloud projects and to “Google Cloud hosted solutions,” but does not specify a dedicated private cloud, an isolated EU data center, or an explicitly segregated customer environment for the Gemini API on ai.google.dev.
EU SaaS / Managed: Partially
Google operates a SaaS/API service. However, the website does not specify an explicit EU data residency or an EU/EEA data center for the Gemini API; rather, according to the additional terms, certain data may be stored in any country where Google or its agents operate facilities.
Hybrid: Indirect / Not Available
An explicit hybrid operating model for the Gemini API is not described on the website. The documentation only shows the hosted API; local or internal partial processing for the same solution is not specified there.
T&C / DPA: Covered
For “Paid Services,” the Additional Terms explicitly state that prompts and responses are processed in accordance with the “Data Processing Addendum for Products Where Google is a Data Processor.”
No training: partially
For “Paid Services,” the website explicitly states that prompts and responses are not used to improve the products. At the same time, they are logged for a limited period for security and compliance purposes; for “Unpaid Services,” content is generally used for improvement, though EEA users are referred to the “Paid Services” rule. Additionally, more extensive ZDR controls exist only under certain conditions.
Open Source / Transparency: Partially
To promote greater transparency and user autonomy, the website refers to open Gemma models and notes that Gemma can also run on-device. However, for the Gemini API itself, neither open core components nor the option to self-host the service are specified.
Data Processing
The website describes the Gemini API as a service operated by Google. For “Paid Services,” according to the additional terms, prompts and responses are not used for training or product improvement, but are logged for a limited time to detect and prevent violations, as well as for required legal or regulatory disclosures. According to the website, this data may be stored transiently or in cache in any country where Google or its agents operate facilities. The ZDR documentation describes additional restrictions and configurations: certain stateful or storage-intensive functions must be disabled or avoided, and for certain grounding functions, the storage mentioned there cannot be disabled.
Conclusion
From an EU/EEA perspective, the Gemini API is not documented on the provider’s website as a service that is clearly EU-resident. A viable data protection pathway is apparent if the service is used as a “Paid Service,” the DPA applies, and storage functions are configured restrictively. However, because no explicit EU data residency is specified and, according to the website, log data can be temporarily stored worldwide, the service’s overall compliance with the GDPR is only partially substantiated.
Sources
| On-prem / local hosting | ❓ |
| Private cloud / data center | ⚠️ |
| EU SaaS / Managed | ⚠️ |
| Hybrid | ❓ |
| DPA / AVV | ✅ |
| No training on customer data | ⚠️ |
| Open source / transparency path | ⚠️ |
On-prem / local hosting: indirect / not available
The website does not specify any on-premises or self-hosting options for the Gemini API itself. The API is described as a hosted service.
Private Cloud / Data Center: Partially
The website refers to use via cloud projects and to “Google Cloud hosted solutions,” but does not specify a dedicated private cloud, an isolated EU data center, or an explicitly segregated customer environment for the Gemini API on ai.google.dev.
EU SaaS / Managed: Partially
Google operates a SaaS/API service. However, the website does not specify an explicit EU data residency or an EU/EEA data center for the Gemini API; rather, according to the additional terms, certain data may be stored in any country where Google or its agents operate facilities.
Hybrid: Indirect / Not Available
An explicit hybrid operating model for the Gemini API is not described on the website. The documentation only shows the hosted API; local or internal partial processing for the same solution is not specified there.
T&C / DPA: Covered
For “Paid Services,” the Additional Terms explicitly state that prompts and responses are processed in accordance with the “Data Processing Addendum for Products Where Google is a Data Processor.”
No training: partially
For “Paid Services,” the website explicitly states that prompts and responses are not used to improve the products. At the same time, they are logged for a limited period for security and compliance purposes; for “Unpaid Services,” content is generally used for improvement, though EEA users are referred to the “Paid Services” rule. Additionally, more extensive ZDR controls exist only under certain conditions.
Open Source / Transparency: Partially
To promote greater transparency and user autonomy, the website refers to open Gemma models and notes that Gemma can also run on-device. However, for the Gemini API itself, neither open core components nor the option to self-host the service are specified.
Data Processing
The website describes the Gemini API as a service operated by Google. For “Paid Services,” according to the additional terms, prompts and responses are not used for training or product improvement, but are logged for a limited time to detect and prevent violations, as well as for required legal or regulatory disclosures. According to the website, this data may be stored transiently or in cache in any country where Google or its agents operate facilities. The ZDR documentation describes additional restrictions and configurations: certain stateful or storage-intensive functions must be disabled or avoided, and for certain grounding functions, the storage mentioned there cannot be disabled.
Conclusion
From an EU/EEA perspective, the Gemini API is not documented on the provider’s website as a service that is clearly EU-resident. A viable data protection pathway is apparent if the service is used as a “Paid Service,” the DPA applies, and storage functions are configured restrictively. However, because no explicit EU data residency is specified and, according to the website, log data can be temporarily stored worldwide, the service’s overall compliance with the GDPR is only partially substantiated.
Sources
Strengths & weaknesses at a glance
| Strengths | Weaknesses |
|---|---|
| - Very broad range from high-end reasoning to very low-cost high-volume processing. | - The portfolio is currently somewhat confusing because stable 2.5 models, 3.x previews, and deprecated 2.0 models coexist in parallel. |
| - Strong combination of multimodality, coding, agents, grounding, tooling, and long context windows. | - 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. |
| - Clear production pricing logic with Standard, Batch, Flex, and in some cases Priority. | - The cheaper models are strong for volume and standard tasks, but not ideal for the most difficult analysis and precision use cases. |
| - For Paid Services, prompts/responses are not used for product improvement according to the Terms. | - Preview models may still change before GA and have more restrictive limits. |
| - For enterprise environments via Vertex AI, there are stronger security/compliance options and regional processing models. |
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GDPR-compliant usage possible?
For the EU/EEA region, a more privacy-friendly use of the Gemini API based on the provider’s documentation appears to be possible only under certain conditions. On the positive side, according to the additional terms, a DPA applies to “Paid Services,” and prompts and responses are not used for product improvement. On the negative side, Google nevertheless logs prompts and responses for Paid Services for a limited time for security and compliance purposes and may store this data temporarily or in cache “in any country” where Google or its agents operate facilities. The website does not specify an explicit EU data residency or an EU/EEA server location for the Gemini API.
Positive
The website lists three key points for “Paid Services”: processing in accordance with a DPA, no training on prompts or responses for product improvement, and specific notes for EEA users. Additionally, the “Zero Data Retention” page explains that, for certain projects and upon approval, user-identifying content and metadata can be removed before logging, and that individual storage options can be disabled for stateful features.
Negative
The website does not specify a guaranteed EU data residency for the Gemini API or a specific EU/EEA data center location. Rather, the additional terms state that log data for Paid Services may be stored transiently or in cache in any country where Google or its agents operate facilities. Furthermore, data-minimizing configurations such as “Zero Data Retention” and the disabling of certain storage functions require additional prerequisites; according to the website, it is not possible to disable the storage described there for specific functions such as “Grounding with Google Search” or “Grounding with Google Maps.”
Server Location
Not specifically listed on the website as an EU/EEA location. For paid services, it states that log data may be stored temporarily or in cache in any country where Google or its agents operate facilities.