LLM EU

Frequently asked questions

Basics

What is a context window, and what is a token?

A token is a small piece of text, roughly a word fragment. A context window is the maximum number of tokens one call may hold: instructions, the conversation so far, retrieved passages and the reply.

What is an LLM?

An LLM is a program trained on large amounts of text to predict the next token, a small piece of text. It answers from its weights and the prompt you send, not from a database it searches.

Retrieval

What is RAG?

RAG is a pipeline, not a model: your application retrieves passages and the model answers from those. Only the last stage is a chat completion; embedding and reranking are separate calls.

Hosting

How do LLMs run in the EU?

A model runs where an endpoint runs, and the row records its region and class. Residency is a filter applied before scoring: if nothing satisfies it, the request returns 409 no_endpoint_for_policy.

Open weights or an API: which should I use?

Open weights mean the files are downloadable; an endpoint means someone runs them for you. Many European deployments use both: an API for variable load, a self-hosted checkpoint for sensitive work.

Cost

Licences

How do open model licences work?

A licence is a recorded field on every model card: an SPDX identifier and a link to the text. Open weights means the weights are downloadable, not that commercial use is allowed.

API

What are LLM API rate limits?

A rate limit here is a ceiling per bucket in a fixed window: 600 calls per key and 1800 per organization each minute, with at most 8 requests in flight on one key.

Routing

How does an LLM router work?

A router turns a request naming no machine into one endpoint response. A pure function filters candidates by policy and residency, scores what survives and takes the highest score.