EU Cloud AI Providers: Cleanest Compliance Paths

Two questions decide whether a European AI cloud is fit for regulated deployment: where the inference actually runs, and whether the provider can document the model, contract and operational controls around it. LLM Radar's read is that EU jurisdiction narrows the compliance problem, but it does not solve model provenance, licence clarity, AI Act documentation or production support depth on its own.

Verdict First

The cleanest compliance paths in Europe are not simply the providers with the longest model catalogues. They are the providers that can make four things auditable at procurement time: residency, GDPR posture, AI Act role allocation and model rights.

LLM Radar's provisional read is that STACKIT AI, dedicated deployments on Scaleway Generative APIs, and IONOS AI Model Hub are the strongest EU-ready candidates for regulated EU workloads, provided the buyer completes the contractual layer: DPA, logging terms, model documentation, incident notice, subprocessor review and lifecycle notices (as of 2026-06-09).

OVHcloud AI Endpoints and Scaleway's serverless path are attractive for fast EU-hosted deployment. They are also where the compliance analysis becomes more demanding. Shared serverless inference can be defensible for non-sensitive workloads, internal tooling and prototypes, but banking, healthcare, public-sector and defence-adjacent deployments need stronger evidence on isolation, retention, private networking, support channels and audit access (as of 2026-06-09).

Infomaniak belongs in the comparison as a sovereignty-forward Swiss option, especially for European buyers who already treat Swiss hosting as acceptable under adequacy logic. But Switzerland is not EU jurisdiction. That distinction matters for public buyers and regulated companies that have procurement rules explicitly anchored in EU establishment, EU data centres or EU-only operational control.

Mistral is the second layer of the analysis. A European cloud endpoint does not become EU-ready merely because it exposes a capable model. Mistral Large 2, Llama-family models and Qwen-family models carry different licence terms, provenance evidence and downstream obligations. Model provenance still decides whether a clean hosting stack is actually defensible.

Scoring Method

LLM Radar scores European AI cloud providers on four primary dimensions, with operational maturity as the practical fifth dimension.

Hosting jurisdiction asks where data physically sits and who operates the environment. Generic claims of European availability are not enough. The defensible evidence is a named region, data-centre country, or deployment mode: Berlin, France, Germany, EU01, dedicated EU deployment, or customer-selected European region. For regulated workloads, region pinning should be contractual, not only a console setting.

GDPR posture asks whether the provider can support a real controller-processor review. The minimum evidence is a DPA, clear subprocessor list, prompt and completion retention terms, no-training commitment, transfer mechanism where applicable, and customer control over logs. A provider that says data is hosted in Europe but cannot explain logging, telemetry and support access remains Conditional.

AI Act status asks which role the vendor is taking. An infrastructure provider, model host, model distributor, general-purpose AI model provider and downstream deployer do not carry the same obligations. IONOS is notable because its AI Model Hub documentation explicitly discusses role distinction between Distributor and Provider under the EU AI Act (as of 2026-06-09). That kind of framing is useful because it lets compliance teams map obligations rather than infer them.

Licence clarity asks whether each model can be used in production, modified, redistributed, fine-tuned or embedded into a commercial product. Open-weight does not mean permissive. Permissive licences, custom commercial licences, research-only licences and commercial-restricted licences are different risk classes. A model catalogue that lists names without model cards, licence links, version identifiers and quantization details is incomplete for regulated procurement.

Operational maturity then decides whether the paper posture can survive production. Buyers should look for SLAs, private networking, dedicated deployment options, support routes, incident notices, audit evidence, model deprecation notices, security documentation and a process for model updates. This is where smaller European providers can win on sovereignty but still lose on enterprise depth.

Provider Comparison

Provider	Residency and controls	Model and licence visibility	LLM Radar verdict for regulated personal-data workloads
STACKIT AI	German/EU positioning, AI Model Serving posture says data and queries are neither stored nor used for training; EU01 usage pricing is visible (as of 2026-06-09).	Catalogue and licence evidence still need model-by-model review before production.	EU-ready where contracts, region pinning, logging controls and model evidence are completed.
IONOS AI Model Hub	Documentation states Berlin hosting, GDPR alignment and explicit AI Act role discussion (as of 2026-06-09).	Stronger than average compliance framing; catalogue still requires licence inspection per model.	EU-ready candidate for regulated workloads with procurement-grade DPA and operational evidence.
Scaleway Generative APIs dedicated	Official FAQ says Generative APIs are hosted in European data centres and distinguishes serverless from dedicated deployment; private models are supported in dedicated mode (as of 2026-06-09).	Dedicated deployments give better room for private models and customer-specific controls.	EU-ready candidate for sensitive workloads when deployed dedicated with private controls.
Scaleway serverless	Same European hosting posture, faster route to API use, shared operational model (as of 2026-06-09).	Useful for experimentation and lower-risk production; less clean for sensitive data unless retention and isolation terms are strong.	Conditional for regulated personal-data workloads.
OVHcloud AI Endpoints	Serverless model access; OVHcloud advertises more than 40 models and says customer data is not used to train or improve models (as of 2026-06-09).	Broad catalogue including Llama, Qwen and DeepSeek-style choices increases licence review burden.	Conditional until regulated-sector controls, logging, isolation and model lifecycle evidence are documented.
Infomaniak AI Tools	Sovereignty-forward Swiss posture; useful European benchmark, but not EU jurisdiction.	Model and operational evidence must be assessed per service.	Conditional for EU-regulated workloads that require EU jurisdiction; potentially defensible where Swiss adequacy is accepted.

STACKIT's advantage is the simplicity of the compliance story: German/EU cloud positioning, explicit statements on query storage and training use, and a product framed around secure model serving. The caveat is not unusual: the model layer still needs evidence. The cloud may be clean, but a regulated deployment still needs to know exactly which model is running, under which licence, at which version, and with what update policy.

IONOS is strong because it treats governance as part of the product documentation rather than a sales afterthought. Berlin hosting, GDPR framing and AI Act role language are all useful signals. The verdict is EU-ready only after the buyer verifies the contract stack and model-specific documentation. Public documentation is a starting point, not the procurement file.

Scaleway's split between serverless and dedicated deployment is important. The dedicated route is the more defensible path for regulated data because it can support private models and a cleaner control story. Serverless is valuable, but LLM Radar's read is Conditional for sensitive personal data unless the provider's DPA, retention, logging and isolation commitments are strong enough to withstand sector review.

OVHcloud is credible on European infrastructure and useful for rapid model access. Its AI Endpoints posture includes a no-training-on-customer-data statement and a broad catalogue (as of 2026-06-09). The risk is the catalogue itself: more models mean more licence and provenance work. For regulated sectors, broad choice is not a substitute for documented lifecycle, licence and isolation controls.

Model Provenance Still Decides

European hosting is necessary for many regulated deployments. It is not sufficient.

Mistral Large 2 is the obvious European reference point. Mistral's release reports 84.0% MMLU for the pretrained model and states that self-deployed commercial use requires a Mistral Commercial License (as of 2026-06-09). That is a workable production path, but it is not the same as a permissive open-source licence. Compliance teams should record the licence, permitted uses, redistribution limits and any fine-tuning restrictions before treating the model as procurement-ready.

Llama-family models are commercially usable under Meta's custom licence, but they are not permissive open source. They carry acceptable-use restrictions and scale-triggered licence terms. That does not make them unusable. It means a provider catalogue exposing Llama models should surface the exact licence and version, not just the brand name.

Qwen-family models are mixed. Some releases are Apache 2.0; others use different or custom terms depending on size and release line. A catalogue entry that says "Qwen" is not enough. The relevant compliance unit is the specific model artefact: base or instruct, size, version, quantization, source, licence, and update date.

DeepSeek-style catalogue entries create a separate issue. Even if an EU provider hosts the weights in Europe, regulated buyers still need to assess model provenance, training transparency, licence terms, safety documentation and geopolitical risk. Hosting jurisdiction can solve data residency; it cannot launder uncertainty in the model supply chain.

Benchmark numbers should be treated as selection evidence, not compliance evidence. A high MMLU score, coding score or multilingual benchmark can justify why a model was shortlisted. It does not answer whether prompts are retained, whether personal data leaves the EU, whether the licence permits production use, or whether the AI Act documentation package is adequate.

The strongest provider catalogues will expose original model cards, licence links, version identifiers, quantization details, context length, deprecation policy, safety notes and update notices. Without that, a European endpoint remains at best Conditional for regulated use.

EU-Ready Patterns

The cleanest compliance pattern depends on risk class.

Shared serverless inference is usually Conditional for personal data. It can be appropriate for low-risk internal tooling, summarisation of non-sensitive documents, synthetic test data, developer workflows and public-content processing. It becomes harder to defend when prompts contain patient data, financial records, employee files, law-enforcement material, defence information or children's data. The decisive documents are the DPA, retention schedule, logging controls, support-access rules and isolation model.

Dedicated EU inference is the strongest default for regulated sectors. A defensible deployment usually has region pinning, private networking, customer-controlled logging, model licence evidence, named subprocessors, incident notice terms and a documented lifecycle process. Scaleway dedicated deployments, STACKIT AI Model Serving and IONOS-style EU-hosted model hubs are the patterns LLM Radar would put first in a regulated review, assuming the contract file confirms the public posture.

Self-hosting can be EU-ready, but only when the team treats the model as production infrastructure rather than a downloaded artefact. Self-hosted open-weight or commercially licensed models still need patching, monitoring, access control, abuse controls, licence records, evaluation evidence, rollback plans and model update governance. For public-sector and defence-adjacent use cases, self-hosting may be the cleanest sovereignty posture, but it shifts operational burden onto the deployer.

Public-sector teams should ask providers for:

• Exact processing region and failover region.
• DPA and subprocessor list.
• Prompt, completion, telemetry and support-log retention terms.
• Written no-training and no-model-improvement commitment.
• Private networking or dedicated deployment option.
• Model card, licence, version and quantization details for each model.
• AI Act role statement and documentation support.
• Incident notice terms and audit-support workflow.
• Model deprecation and replacement notice policy.
• SLA and escalation route for production incidents.

The cleanest compliance path is not the widest model catalogue. It is the provider that makes residency, contracts, model rights and operations auditable.

Final Read

LLM Radar's read on EU cloud AI providers is that jurisdiction is necessary but insufficient. European cloud AI is materially better for sovereignty than routing sensitive EU personal data through US-only APIs, but not every European endpoint is EU-ready.

EU-ready providers are those with concrete EU hosting, a usable DPA posture, documented AI Act role allocation, private or dedicated controls, clear support routes and model catalogues that surface licence and provenance evidence. STACKIT, IONOS and Scaleway dedicated deployments are the cleanest candidates in this category based on public posture (as of 2026-06-09).

Conditional providers are those with credible residency claims but weaker evidence on operational maturity, model lifecycle, licence surfacing or regulated-sector support. OVHcloud AI Endpoints and Scaleway serverless sit here for sensitive personal-data workloads unless the buyer obtains stronger written commitments than the public product pages provide. Infomaniak is also Conditional for EU-jurisdiction requirements because Swiss adequacy and European sovereignty are not the same as EU establishment.

Blocked means the path cannot document where personal data is processed, whether prompts are retained, who the subprocessors are, or what licence permits production use. That applies regardless of whether the provider has a European brand, a European data centre, or a model catalogue full of open-weight names.

The strongest counter-argument is that US hyperscalers may offer deeper enterprise controls, mature IAM, private networking, audit reports, SLAs and support coverage. That argument has weight. But stronger enterprise operations do not remove transfer-risk, sovereignty and jurisdiction concerns for sensitive EU personal data. The defensible read is not "Europe at any cost." It is "European jurisdiction plus auditable controls, or the deployment remains Conditional."

Sources

• OVHcloud AI Endpoints — Official product posture on serverless model access, model families, data privacy and no training on customer data.
• Scaleway Generative APIs FAQ — Official documentation on European hosting, serverless versus dedicated deployments, private models and operational model support.
• IONOS AI Model Hub: European Union AI Act — Official IONOS statement on GDPR foundation, EU AI Act role split and high-risk deployer responsibilities.
• STACKIT AI Model Serving — Official STACKIT posture on data-sovereign model serving, storage, training use and EU01 pricing.
• Mistral Large 2 announcement — Official benchmark, model-size and licence posture for a European frontier model often offered through EU cloud stacks.