Aleph Alpha Releases Kolibri: 78.1B Open-Weight English-German MoE With Only 3.46B Active Parameters

Aleph Alpha has released Kolibri, a 78.1-billion-parameter open-weight mixture-of-experts model that activates only 3.46 billion parameters per forward pass, making it computationally efficient despite its large total capacity. The model is bilingual in English and German, targeting European enterprise and sovereign AI use cases where data residency and language fidelity are critical. For developers, the sparse activation profile means Kolibri can run with inference costs closer to a 3-4B dense model while potentially benefiting from the knowledge capacity of a much larger one. Its open-weight release means it can be fine-tuned, self-hosted, or integrated into existing pipelines without API dependency. This is a meaningful addition to the MoE open-model landscape, particularly for teams building applications that require strong German-language performance.