European open-source model Kolibri released with 3.46 billion active parameters and 1 million context support

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MetaEra reports that German company Aleph Alpha has launched Kolibri, an open-source bilingual model supporting English and German. The model employs a MoE architecture with a total of 781 billion parameters, activating 34.6 billion per token. Weights are available on Hugging Face under the Apache 2.0 license. Kolibri supports up to 1 million tokens, with a recommended deployment limit of 262,000 tokens. In testing, it achieved 96.9% on AIME 2025 and 85.9% on LiveCodeBench v6. Open interest in open-source models is growing, as reflected by the Fear & Greed Index, which shows cautious optimism. Kolibri outperforms Qwen3.5 35B-A3B in both English and German, but lags behind Qwen3.8 with 27 billion active parameters.
ME AI News: German AI company Aleph Alpha has released and open-sourced the English-German bilingual model Kolibri. The model employs a MoE architecture with a total of 78.1 billion parameters, but only approximately 34.6 billion parameters are activated per token. Weights have been uploaded to Hugging Face under the Apache 2.0 license. Kolibri supports tool calling and adjustable inference modes, with context length extendable up to approximately 1 million tokens. However, the official recommendation for daily deployment is to keep context length under 262,000 tokens, which also represents the maximum context length the model was trained on. In Aleph Alpha’s official evaluations, Kolibri achieved 96.9% on AIME 2025 and 85.9% on LiveCodeBench v6. Its combined English and German performance is slightly higher than Qwen3.5 35B-A3B, which also has around 3B activated parameters, but still falls short of Qwen3.8 with 27B fully activated parameters. (Source: BlockBeats)
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