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  • The absence of any comparison to Qwen3.8 Flash, another MoE model with a small-ish (6B) number of active parameters, is pretty striking. Instead, it's compared with Qwen3-Next 80B-A3B, a model released almost a full year ago.

    I get that doesn't invalidate the real "point" of the model, but...

  • I think at the moment the main thing a sovereign AI model needs to be good at is auditing the results of other models.

    Right now one could run an open model for most government applications and it would be good enough, you just cannot trust any of these.

    So having a sovereign controlled model audit the first one would basically act like a “trust adapter”.

    If the second model is cheap and fast enough, there is a business model.

    You don’t even need to audit all the intermediate steps, just tool calls and end results.

  • Qwen3.8 27B beats Kolibri 79.9 vs 70.8 in German in Kolibri's harness on Kolibri's benchmark.

    Also, once the Cohere takeover is complete will they still be able to use this "sovereign" claim despite being 90% owned and 100% operated out of Toronto?

  • For a post to make such a big deal about sovereignty it is a bit misleading to not mention that the company is slated to be merged with Cohere, a Canadian company.

    And that is a good thing - no need to hide it. Given the growing cost of keeping up, these few non-US, non-Chinese companies really need to do more sharing of efforts and costs.

    Canada too is very much in need of sovereign AI options, but funding that on its own would be pretty much a waste of money. Would love to see this new German Canadian company cooperate with Mistral too, or maybe one of the Korean AI companies.

  • The thing to note here, besides the transparency and the fact that it’s actually a good model that also works well on coding and agentic tasks, is that it’s the first release by a team formed less than a year ago, with a strong focus on iteration velocity. There’s more to come.

    disclaimer: I‘m part of the training team, happy to answer any questions

  • Thank you Aleph Alpha team for making it open.

    We as many other’s were curious to try and benchmark it.

    On that note, as a small gesture of support, we’ve hosted and made Kolibri-1 free for anyone to try for the next few days.

    No GPU. No setup. Just try it. tesseracted.com/kolibri-1-chat/

    https://x.com/konarkmodi/status/2106373678589960260?s=46

    by kkm
  • >We trained Kolibri with abstention data and with our Merlin-Arthur protocol. As a result, it is trained to say "I don't know" when the answer isn't in the context.

    https://aleph-alpha.com/en/blog/bounding-hallucinations-merl...

  • The paper explains absolutely everything as if it was a tutorial "how to made your own modern agentic LLM". They even tell how they made their dataset. https://aleph-alpha.com/downloads/tech-report.pdf ; It's the first time I see this level of openness.

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