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Continker

Own the model. Own the cloud it runs on.

Continker is an Amsterdam studio building sovereign AI cloud platforms, applied AI, and local models that run offline. Infrastructure organizations own and run themselves, on European terms.

Sovereign AI cloud platforms

The infrastructure layer organizations own and run themselves. Model serving, retrieval, and agent workflows on hardware the customer controls, with audit and air-gap built in.

Applied AI

The systems that run on it. Language-model agents, retrieval, and automation built for real operational work.

Local models

Small, fine-tuned models that run offline on commodity hardware, so the model layer is owned too.

Sovereignty here is technical, not geographic. It is about who controls the keys, the runtime, and the operators, not where the data sits.


Open work

MetroLLM-Bench is one example. It is a benchmark and a set of open-weight students for running a transit kiosk from a prose prompt. A small local language model handles the task offline on commodity hardware, and the 2.6 GB student matches a frontier cloud API.

Model Size Runs on
Qwen3.5-2B-metro-v24 1.2 GB anything, including CPU-only
Qwen3.5-4B-metro-v24 2.6 GB a 16 GB laptop
Qwen3.5-9B-metro-v24 5.3 GB a 24 GB machine
Qwen3.5-27B-metro-v24 16 GB a 32 GB machine

Try the live demo · Browse the collection · Benchmark and code


More at continker.ai.

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