Thanks! What matters to us right now is not so much our current position, but the velocity with which we’re moving. Kolibri 1 is the first measurement of our position, there’ll be more. We want to build this in Europe and this is only the start. The report also shows our focus on building out proper tooling with our Model Factory.
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
- Is it possible to train only on math and logic materials and expect the model's response in math questions to be superior to general models with the same training/inference compute hardware?
- Are there non-LLM approaches to the above task with the goal of achieving a non-hallucinatory agent?
Any future plans you can share to further evolve / train models in this size class?
It seems like a very suitable size for local AI models on reasonably high end consumer devices, given it's low active parameter count and a mixed 8bit/4bit quant would fit easily inside 64GB of memory.
I can't comment on concrete sizes of future models, partly because it's not decided yet. But: Pre-training for Kolibri only started in August so there's a high chance continued post-training - which we plan to do - will yield some nice checkpoints. We believe this size and sparsity allows achieving great inference throughput at reasonable levels of intelligence.
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
Please don't copy-paste comments - it makes merging threads a pain! (and indeed the temptation to copy-paste is indication that a discussion needs merging)
p.s. It's a great comment! no problem on that level
Model Training as Code - https://news.ycombinator.com/item?id=48673450 - June 2026 (24 comments)