thanks for the lausanne visit and sharing these super cool results!

this seems to become a trend already: arxiv.org/abs/2510.14901

apertus also! (september release, same mission but multilingual)

cool idea. let’s us know how it goes! btw maybe these can be useful github.com/swiss-ai/ape...
or, since today, also unsloth and llamacpp

on the engineering track it renews yearly usually, but permanent is possible after some experience & paperwork. on the academic track see e.g. here www.epfl.ch/about/workin...

Link to the first version of the Apertus open-data open-weights LLM - multilingual in >1000 languages, and compliant ethical AI huggingface.co/collections/...

Several open positions at EPFL Lausanne and ETH Zurich and, as part of the Swiss AI Initiative. We cover the entire stack of foundation model training. And we're open to international applicants of course (no H-1B required ;))

funktioniert schon seit letzter woche im neusten LM Studio (mit MLX) huggingface.co/models?searc...

GGUF kommt auch bald die tage

no. the commercial models like chatGPT and gemini still can do better swiss german than apertus.

the 70b should work too if enough ram, you can just replace 8 by 70 in the swiss ai huggingface repo

MLX provides already many quantizations. But yes still working on gguf github.com/ggml-org/lla...

or this quantized version of the model, which is faster and is even easier as it requires no huggingface login:

pip install mlx-lm

mlx_lm.generate --model mlx-community/Apertus-8B-Instruct-2509-8bit --prompt "who are you?"

volle transparenz der KI modelle inkl. ihrer trainingsdaten ist hier sehr wichtig, damit man solche biases indentifizieren und nachvollziehen kann (audit). dies ist bei llama & qwen modellen (die nur open weights sind) klar nicht möglich., bei apertus aber schon

propaganda von russischen und auch anderen akteuren ist klar auf dem web vorhanden und kann trainingsdaten reinfliessen: www.newsguardtech.com/wp-content/u...