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Aleph Alpha releases Kolibri, an open-weight LLM for German and English

Aleph Alpha has released Kolibri, an open-weight Large Language Model designed for German and English. This Mixture of Experts model boasts 78.1 billion parameters, with only a fraction active per token. Kolibri was trained on approximately 24 trillion tokens, with a significant portion in German, utilizing 768 NVIDIA B200 GPUs across Germany and Finland. The model is available under the Apache 2.0 license and its weights can be found on Hugging Face. AI

IMPACT Provides a new open-weight LLM option for German and English language tasks, potentially accelerating research and development in these areas.

RANK_REASON Frontier-lab model release with system card. [lever_c_demoted from frontier_release: ic=1 ai=1.0]

Read on Mastodon — mastodon.social →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Aleph Alpha releases Kolibri, an open-weight LLM for German and English

How we ranked this

Signal score
8 / 100
Composite score across the factors below. Higher = stronger signal that this story matters right now.
Newsworthiness bucket
Significant
Frontier-lab model release with system card. [lever_c_demoted from frontier_release: ic=1 ai=1.0]
Source corroboration
Single-source cluster
Only one publisher covered this so far. Single-source stories can still rank when the publisher is high-authority, but they lack cross-source corroboration.
Topics
model release, product
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High
Clearly on-topic for AI-industry coverage.
Story freshness
Breaking (< 6h)
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Full methodology in our editorial standards.

COVERAGE [1]

  1. Mastodon — mastodon.social TIER_1 English(EN) · [email protected] ·

    🐦 # AlephAlpha released # Kolibri , an open-weight # LLM for German and English under the Apache 2.0 license. A # MixtureOfExperts with 78.1B parameters, of whi

    🐦 # AlephAlpha released # Kolibri , an open-weight # LLM for German and English under the Apache 2.0 license. A # MixtureOfExperts with 78.1B parameters, of which only 3.46B are active per token. Trained from scratch on ~24T tokens (over a fifth German) using 768 # NVIDIA B200 GP…