Written by Jakub Rusinowski · Last updated September 19, 2026
Switzerland's open model, from EPFL, ETH Zurich and the Swiss National Supercomputing Centre. Trained on roughly 15 trillion tokens spanning more than 1,000 languages, with weights, data and process published under Apache-2.0 — the European sovereignty argument made concrete.
| Licence | What it permits | Applies to |
|---|---|---|
Apache-2.0 | Commercial use permitted Commercial use permitted. No usage restrictions beyond attribution. | Apertus 8B, Apertus 70B |
| Apertus 8B | Min 6 GB VRAM · Q4_K_M · 65,536 ctx · |
| Apertus 70B | Min 43 GB VRAM · Q4_K_M · 65,536 ctx · |
The cheapest GPU that runs Apertus locally (min 6 GB VRAM) is the Intel Arc B570 (10 GB).
Install Ollama then run: ollama run apertus
Minimum VRAM: 6 GB. For best results use Q4_K_M quantization.
Apertus needs about 6 GB VRAM at Q4_K_M quantization for its smallest variant. Variants: Apertus 8B (6 GB, Q4_K_M); Apertus 70B (43 GB, Q4_K_M). On Apple Silicon, unified memory counts toward this requirement.
Yes — Apertus runs on an RTX 4090 (24 GB) and other 24 GB cards such as the RTX 3090. Smaller variants also fit comfortably on 8–16 GB GPUs at Q4_K_M.
Q4_K_M is the best balance of quality and VRAM for Apertus in most cases. Choose Q8_0 for near-lossless quality if you have spare VRAM, or smaller quants (Q3/Q2) only when memory is tight.
Apertus has no local Ollama tag — the published tag is cloud-hosted, so running it sends your prompts to a hosted GPU rather than your own machine.