Kolibri: A Sovereign Open-Weight Model
- Source
- aleph-alpha.com
- Author
- bastitx
- Date
Kolibri is Aleph Alpha's bid for teams that need a capable model they can host themselves under European data-residency rules. The company's announcement describes a 78B mixture-of-experts model with about 3B parameters active per token and context of up to 1M tokens, built with a training pipeline it says is reusable for further sovereign models. The Apache 2.0 license matters as much as the size: it allows commercial use and modification without the custom terms attached to many open-weight releases. An independent walkthrough by Tejas Kumar lists slightly different figures, 3.5B active parameters and 262k context, so confirm the model card before sizing hardware or planning long-context work. That walkthrough also covers tokenizer behavior and where the model falls short, which is the more useful read if you are deciding whether Kolibri fits a German-language workload or whether a larger general model still wins.

- mixture-of-experts — A model built from many specialist sub-networks where only a few activate per token, giving big-model capability at small-model running cost.
- context window — The maximum amount of text a model can consider at once — its working memory for the current conversation or task.
- open weights — A model whose trained parameters are published for anyone to download and run — unlike API-only models you can access but never possess.
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