Apertus – Open Foundation Model for Sovereign AI

previous thread: https://news.ycombinator.com/item?id=45108401

As long as the following remains true, this release ends up a bigger contribution to science at large than most other models trained "behind closed doors":

> Fully open model: open weights + open data + full training details including all data and training recipes

I use it extensively. It is not ready for agentic use, but as a generic driving model for RAG use cases, it is pretty competent. You can build useful software with it.

Other fully open LLMs include Allen AI's OLMo 3.1 and MBZUAI's K2 Think V2, both of which have released their full training pipelines and datasets.

Nvidia Nemotron is also an open training source model, though a portion of its dataset remains proprietary.

Quoting lambda's comment:

> Note that the Nemotron models are generally stronger than Olmo and K2 Think V2 (according to Artificial Analysis benchmarks), and there is a lot of overlap in their datasets (lots of datasets are based on the same sources with different filtering, Olmo and K2 Think V2 both have used some Nemotron datasets).

> But yeah, Nemotron is a modern and fairly capable LLM, even the 122b is more capable than Deepseek R1 (a 671b model) on most benchmarks, and there's also the recently released 550b Ultra now.

https://news.ycombinator.com/item?id=48492439

For a model that claims to focus on many languages, it's quite unreliable when it comes to simple questions like "how to say X in language Y" or "how to conjugate verb X in language Y". It keeps hallucinating words that do not exist, and when corrected, it only hallucinates a new lie.