Leading AI models on a secure platform operated in Germany.
DeutschlandGPT provides models such as GPT, Claude, Gemini, Llama, and Mistral through a single interface. Users can chat, analyze documents and images, perform real-time web searches, configure their own assistants or specialized applications, and integrate external business systems. The platform is designed for individual users, teams, companies, and public or data-sensitive organizations.
GermanyGPT
Leading AI models on a secure platform operated in Germany.
Location: Germany ⓘ DeutschlandGPT GmbH, 3 Gabriele-Münter-Straße, 82110 Germering, Germany.
5x Pro Pro features with significantly higher usage limits for more intensive individual use.
Business Pro features plus centralized user management, white labeling, prioritized support, and configurable retention periods; for SMBs and teams.
Enterprise Business features plus custom domain, SAML SSO, SCIM provisioning, Customer Success Manager, dedicated onboarding, invoice billing, and AI training. Other Enterprise Trial Access Time-limited trial access for larger organizations, available by arrangement.
Germany GPT API Usage-based access to various AI models; billing depends on the model and token consumption.
Fair Use Model Paid platform plans have higher limits but are subject to rules against automated bulk usage and resale.
DeutschlandGPT is a German multi-model platform for generative AI. Instead of using separate accounts and interfaces for different model providers, users can select multiple language and multimodal models from a single hub. The platform combines general chat functions with research, document analysis, projects, specialized assistants, and enterprise integrations.
Target audience
The platform is designed for individuals, freelancers, knowledge workers, agencies, consulting firms, small and medium-sized businesses, and larger organizations. It is particularly relevant for companies that want to provide their employees with access to multiple AI models without allowing individual accounts or uncontrolled shadow AI.
Outstanding features
Notable features include the selection of various models, centralized administration, and processing via European infrastructure. Users can choose a different model depending on the task, analyze files, research web sources, export results to Office formats, and integrate applications from existing business systems. Business plans include role-based access, centralized management, and enterprise authentication.
Key Areas of Application
GermanyGPT is suitable for text generation, summarization, translation, research, document analysis, email drafting, marketing, programming assistance, and internal knowledge assistants. Through integrations and APIs, recurring workflows can also be automated, or AI functions can be embedded into existing applications.
Usage & Notes
Users select a model in the interface and enter their task as a prompt. When dealing with sensitive information, it should be determined in advance which model, data region, and integration will be used. Even when data is stored in Germany, results must be reviewed by experts, and personal data must be processed in accordance with the principle of data minimization.
| Target audience | Assessment |
|---|---|
| Individuals | Yes – permanently free access and centralized use of various AI models without separate provider accounts. |
| Self-employed / Freelancers | Very well suited – useful for text processing, research, document analysis, customer communication, and recurring workflows. |
| SMEs | Very well suited – core target group due to German data storage, user management, integrations, and business plans. |
| Large enterprises | Yes – Enterprise offers SAML SSO, SCIM, custom domain, Customer Success, onboarding, and AI training. |
| Developers / technical teams | Yes – API access, model switching, integrations, and workflow-based applications are available. |
| Line of business departments | Very well suited – Specialized applications and workflows support marketing, sales, HR, administration, and knowledge work. |
| Organizations with critical data protection requirements | Very well suited – German hosting, AVG, configurable retention periods, zero data retention, and non-training are major advantages. |
| Highly regulated organizations | Moderately suitable to good – generally well-positioned; however, model selection, integrations, special data categories, and internal approvals must still be reviewed. |
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 true on-premises/local hosting on the customer’s own hardware. The only option documented is a “self-hosted” open-source model on the provider’s dedicated, isolated servers in the Open Telekom Cloud in Germany—that is, not on the customer’s infrastructure.
Private Cloud / Data Center: Covered
The website describes dedicated, isolated servers in the Open Telekom Cloud in Germany for the self-hosted Llama setup, as well as BSI-C5-certified hosting and German data centers in general. This clearly indicates isolated or specially controlled environments.
EU SaaS / Managed: Covered
DeutschlandGPT is described on the website as a ready-to-use cloud service. Data processing is to take place exclusively within the EU; core data is stored in Germany; and several pages mention the Open Telekom Cloud in Germany or European infrastructure.
Hybrid: partially
The website illustrates an architecture featuring internal systems, integrations, and externally provided AI models on EU infrastructure. Integrations with on-premises Active Directory and local file servers are also mentioned. However, an operating model explicitly described as a “hybrid deployment” is not documented separately.
AVV / DPA: Covered
A separate AVV/DPA is published on the website. The terms and conditions for data processing explicitly refer to Art. 28 of the GDPR and also include an appendix listing subprocessors.
No Training: Covered
The website states on multiple occasions that conversations, uploads, and information from integrations are not used for training language models. Additionally, zero-data-retention agreements with the AI providers are described.
Open Source / Transparency Path: Partially
There is a documented transparency/sovereignty path via a self-hosted open-source Llama 3.3 70B model on dedicated infrastructure. However, the website does not provide a complete disclosure of all components or a general self-hosting/export strategy for the entire platform.
Data Processing
The website describes a multi-tiered model: persistent data and core data are stored on the Open Telekom Cloud in Germany, while model processing, depending on the model, takes place via European infrastructure provided by Microsoft, AWS, Google, IONOS, Mistral, or OpenAI Ireland. For particularly sensitive cases, a self-hosted open-source model on dedicated, isolated servers in Germany is mentioned. Subprocessors, including their processing locations, are listed in the AVV.
Conclusion
For users in the EU/EEA, the hosting and data protection documentation on the website is strong overall. Particularly positive aspects include EU processing, German data storage, a published DPA, named subprocessors, “no training,” and the self-hosted open-source option. A true customer on-premises solution is not documented, but the best available option on the website is clearly documented from a data protection perspective and well-suited for EU/EEA use.
Sources
- https://www.deutschlandgpt.de/
- https://www.deutschlandgpt.de/datenschutzhinweise
- https://www.deutschlandgpt.de/auftragsverarbeitung
- https://www.deutschlandgpt.de/modelle
- https://www.deutschlandgpt.de/plattform/integrationen
- https://www.deutschlandgpt.de/downloads
- https://www.deutschlandgpt.de/organisationen
| 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 true on-premises/local hosting on the customer’s own hardware. The only option documented is a “self-hosted” open-source model on the provider’s dedicated, isolated servers in the Open Telekom Cloud in Germany—that is, not on the customer’s infrastructure.
Private Cloud / Data Center: Covered
The website describes dedicated, isolated servers in the Open Telekom Cloud in Germany for the self-hosted Llama setup, as well as BSI-C5-certified hosting and German data centers in general. This clearly indicates isolated or specially controlled environments.
EU SaaS / Managed: Covered
DeutschlandGPT is described on the website as a ready-to-use cloud service. Data processing is to take place exclusively within the EU; core data is stored in Germany; and several pages mention the Open Telekom Cloud in Germany or European infrastructure.
Hybrid: partially
The website illustrates an architecture featuring internal systems, integrations, and externally provided AI models on EU infrastructure. Integrations with on-premises Active Directory and local file servers are also mentioned. However, an operating model explicitly described as a “hybrid deployment” is not documented separately.
AVV / DPA: Covered
A separate AVV/DPA is published on the website. The terms and conditions for data processing explicitly refer to Art. 28 of the GDPR and also include an appendix listing subprocessors.
No Training: Covered
The website states on multiple occasions that conversations, uploads, and information from integrations are not used for training language models. Additionally, zero-data-retention agreements with the AI providers are described.
Open Source / Transparency Path: Partially
There is a documented transparency/sovereignty path via a self-hosted open-source Llama 3.3 70B model on dedicated infrastructure. However, the website does not provide a complete disclosure of all components or a general self-hosting/export strategy for the entire platform.
Data Processing
The website describes a multi-tiered model: persistent data and core data are stored on the Open Telekom Cloud in Germany, while model processing, depending on the model, takes place via European infrastructure provided by Microsoft, AWS, Google, IONOS, Mistral, or OpenAI Ireland. For particularly sensitive cases, a self-hosted open-source model on dedicated, isolated servers in Germany is mentioned. Subprocessors, including their processing locations, are listed in the AVV.
Conclusion
For users in the EU/EEA, the hosting and data protection documentation on the website is strong overall. Particularly positive aspects include EU processing, German data storage, a published DPA, named subprocessors, “no training,” and the self-hosted open-source option. A true customer on-premises solution is not documented, but the best available option on the website is clearly documented from a data protection perspective and well-suited for EU/EEA use.
Sources
- https://www.deutschlandgpt.de/
- https://www.deutschlandgpt.de/datenschutzhinweise
- https://www.deutschlandgpt.de/auftragsverarbeitung
- https://www.deutschlandgpt.de/modelle
- https://www.deutschlandgpt.de/plattform/integrationen
- https://www.deutschlandgpt.de/downloads
- https://www.deutschlandgpt.de/organisationen
Strengths & weaknesses at a glance
| Strengths | Weaknesses |
|---|---|
| • Wide selection of models without the need for multiple individual subscriptions | • Quality, availability, and feature set depend on external model providers. |
| • German contract partner and German-language interface | • DeutschlandGPT is not equivalent to a proprietary, sovereign base model. |
| • Centralized user, role, and permission management | • There is no publicly documented, fully on-premises operation of the platform. |
| • General Terms and Conditions (GTC) and technical and organizational measures available | • Some subcontractors or their parent companies have ties to the U.S.; storing data solely in Germany does not automatically eliminate all third-country risks. |
| • No training of base models with customer input according to provider specifications | • Model limits and features vary depending on the pricing plan. |
| • Widely applicable for general office, research, and knowledge tasks | • AI outputs may be factually incorrect, incomplete, or distorted. |
| • Integrations and API for business processes | • For particularly sensitive data, model selection, retention periods, integrations, and permissions must be configured individually. |
| • SSO and SCIM in the enterprise environment. |
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GDPR-compliant usage possible?
The website outlines a concrete, actionable GDPR compliance path for the entire EU/EEA region. DeutschlandGPT describes data processing in EU data centers, persistent storage in Germany, a published data processing agreement (DPA) in accordance with Article 28 of the GDPR, designated subprocessors, and a documented “no training” approach. In addition, the website highlights a particularly privacy-strong operational approach using the self-hosted open-source model Llama 3.3 70B on dedicated, isolated servers in Germany. From an EU/EEA perspective, this documents a clearly substantiated path to GDPR-compliant use.
Positive
The following are positively documented: EU/Germany hosting, AVV, a list of subprocessors, no training using user data, ISO 27001, BSI C5-related hosting information, and a self-hosted open-source path for Llama 3.3 70B on dedicated infrastructure in Germany.
Negative
A limitation is that while the website describes EU processing and storage in Germany, it does not explain a separate data residency or transfer logic for every single service in a fully granular manner for all processing activities. Furthermore, the AVV list includes Sentry, a service based in the U.S.; while the website lists the “EU” as the place of processing, it does not provide further details regarding any international access or transfer mechanisms.
Server Location
The website lists several server/processing locations: persistent core data on the Open Telekom Cloud in Germany, specifically in Magdeburg and Biere; general AI processing exclusively within the EU, for example in Frankfurt, Ireland, or Sweden; for individual model paths, the website lists Microsoft Azure in the EU, AWS in Germany, Google Vertex in the EU, IONOS in the EU, and self-hosted Llama on dedicated Open Telekom Cloud servers in Germany.