STACKIT

Schwarz Group cloud from Bad Friedrichshall whose AI Model Serving offers an OpenAI-compatible API on open models and states that no customer data is stored

Quick Overview

Company Schwarz Digits Cloud GmbH & Co. KG
Category LLM API Providers Alternatives
Headquarters Bad Friedrichshall, Germany
EU Presence EU (Germany)
Data Location Germany: the AI Model Serving pricing table names the region Germany South
Open Source No
Replaces Azure OpenAI, AWS Bedrock

Detailed Review

STACKIT AI Model Serving is a managed hosting environment for language models such as Llama and Mistral inside the STACKIT cloud. The documentation describes an inference API that is OpenAI compatible, auth tokens, rate limits, tool calling, vision, and tutorials for LangChain, retrieval-augmented generation and OpenCode.

The site footer names Schwarz Digits Cloud GmbH & Co. KG at Am Campus 1 in Bad Friedrichshall. The FAQ states that no customer data from requests is stored or used by STACKIT, that no model is trained on customer data, and that only open-source models are served. The AI Model Serving pricing table names the region Germany South, and the imprint page itself returned no content.

The pages read do not publish a token price, and point to the STACKIT calculator for costs, which could not be read as it loads in the browser.

What STACKIT does well

  • No customer data from requests stored or used for training, per the FAQ
  • OpenAI-compatible inference API with tool calling and vision
  • Sits inside a full European cloud catalog

Where STACKIT falls short

  • No token price on the pages read
  • The shared-model list is selected by STACKIT, with manual instance selection not possible
  • The imprint page returned no content, so the entity comes from the footer

Standout feature. It is the only provider here whose FAQ says plainly that the model is assigned by availability and cannot be picked by instance.

Pros and Cons

Pros

  • No customer data from requests stored or used for training, per the FAQ
  • OpenAI-compatible inference API with tool calling and vision
  • Sits inside a full European cloud catalog

Cons

  • No token price on the pages read
  • The shared-model list is selected by STACKIT, with manual instance selection not possible
  • The imprint page returned no content, so the entity comes from the footer

Alternatives to STACKIT

See all LLM API providers alternatives →

Frequently Asked Questions

What is STACKIT?

STACKIT AI Model Serving is a managed hosting environment for language models such as Llama and Mistral inside the STACKIT cloud. The documentation describes an inference API that is OpenAI compatible, auth tokens, rate limits, tool calling, vision, and tutorials for LangChain, retrieval-augmented generation and OpenCode.

Where is STACKIT based?

STACKIT operates from Bad Friedrichshall, Germany, which places it under EU (Germany).

What does STACKIT cost?

null.

Who is STACKIT best for?

Companies already on a Schwarz Group cloud that want a model API with no content stored. It is the only provider here whose FAQ says plainly that the model is assigned by availability and cannot be picked by instance.

What are the drawbacks of STACKIT?

No token price on the pages read. The shared-model list is selected by STACKIT, with manual instance selection not possible. The imprint page returned no content, so the entity comes from the footer.

Is STACKIT a good alternative to Azure OpenAI?

STACKIT is built as a European alternative to Azure OpenAI: Schwarz Group cloud from Bad Friedrichshall whose AI Model Serving offers an OpenAI-compatible API on open models and states that no customer data is stored. It will not be a like-for-like feature match in every respect, so check the review above for where the two genuinely differ before switching.

How does STACKIT compare to other LLM API Providers Alternatives tools?

STACKIT is one of several European LLM API Providers Alternatives tools we cover. It is most often compared with Azure OpenAI, AWS Bedrock.

Who worked on this review

Three people touch every tool page: one writes it, a second edits it, and a third checks the compliance and pricing claims against the vendor's own documentation.

Daniel Brandt
Written by

Daniel Brandt

Privacy & Compliance Researcher · Berlin, Germany

Checks the compliance claims: where the company is established, where the data sits, and what the DPA actually says.

Ingrid Halvorsen
Edited by

Ingrid Halvorsen

Managing Editor · Oslo, Norway

Runs the review process and decides when a page is ready to publish or needs another pass.

Sebastiaan Smits
Fact-checked by

Sebastiaan Smits

Founder & Editor · Netherlands

Selects the tools, writes the reviews, and checks where each company is actually established.

Read our editorial process for how we source, verify and update these pages — and how we keep affiliate income separate from what we recommend.

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