diff --git a/doc.zih.tu-dresden.de/docs/jobs_and_resources/capella.md b/doc.zih.tu-dresden.de/docs/jobs_and_resources/capella.md
index 3347343e7e9ad009fdf35e700facacf7661713cf..97f2bff9245c68f72d64ac4560f99cc01e402efc 100644
--- a/doc.zih.tu-dresden.de/docs/jobs_and_resources/capella.md
+++ b/doc.zih.tu-dresden.de/docs/jobs_and_resources/capella.md
@@ -3,18 +3,14 @@
 ## Overview
 
 The multi-GPU cluster `Capella` has been installed for AI-related computations and traditional
-HPC simulations.
-
-## Details
-
-- 144 nodes, each with
-    - 4 x NVIDIA H100-SXM5 Tensor Core-GPUs
-    - 2 x AMD EPYC CPU 9334 (32 cores) @ 2.7 GHz, Multithreading disabled
-    - 768 GB RAM (12 x 32 GB DDR5-4800 MT/s per socket)
-    - 800 GB local storage on NVMe device at `/tmp`
-- Login nodes: `login[1-2].capella.hpc.tu-dresden.de`
-- Hostnames: `c[1-144].capella.hpc.tu-dresden.de`
-- Operating system: Alma Linux 9.4
+HPC simulations. Capella is fully integrated into the ZIH HPC infrastructure.
+Therefore, the usage should be similar to the other clusters.
+
+## Login
+
+You use `login[1-2].capella.hpc.tu-dresden.de` to access the system from campus (or VPN).
+In order to verify the SSH fingerprints of the login nodes, please refer to the page 
+[Fingerprints](../access/key_fingerprints.md#capella).
 
 ## Filesystems