In a collaboration between M²LInES and AI2, researchers present SamudrACE , a machine learning based global climate model emulator. SamudrACE couples 3D atmosphere, 3D ocean, sea ice and land surface emulators to simulate centuries of climate at 1-degree horizontal resolution with 6-hourly atmospheric and 5-daily oceanic output. It produces 145 2D fields across multiple vertical levels with realistic variability in key climate phenomena such as ENSO. The model remains highly stable and shows low climate biases comparable to its individual components while capturing coupled climate behavior that uncoupled models cannot reproduce.