# FBOSS

At the 2026 OCP Global Summit, Meta published the network designs behind its latest AI models and its gigawatt-scale Prometheus cluster. Scale-out had been organized as a three-tier Clos, and the switch platform layer stayed proprietary, with each new platform repeating months of bring-up work. Meta now connects each GPU to eight network planes and flattens Clos to two tiers, and shows IcePack, its first liquid-cooled network rack, holding IceCube, a 102.4T switch with 128 800G ports; MetaRoCE goes open source and the OSPA 1.0 specification goes to OCP.

At the 2026 OCP Global Summit, Meta published the network designs behind its latest AI models and its gigawatt-scale Prometheus cluster. Scale-out had been organized as a three-tier Clos, and the switch platform layer stayed proprietary, with each new platform repeating months of bring-up work. Meta now connects each GPU to eight network planes and flattens Clos to two tiers, and shows IcePack, its first liquid-cooled network rack, holding IceCube, a 102.4T switch with 128 800G ports; MetaRoCE goes open source and the OSPA 1.0 specification goes to OCP.

Meta converted a conventional data center in New Albany, Ohio, into Prometheus, a gigawatt-scale supercluster whose first phase is complete and was used to train the Muse family of foundation models. Because one failing host can slow an entire large training job, Meta focused on system stability and reached more than 85% goodput on Muse Wonder pre-training runs and more than 90% on reinforcement learning runs. The cluster now spans hundreds of thousands of GPUs, with a target of roughly one million at full scale.

Meta converted a conventional data center in New Albany, Ohio, into Prometheus, a gigawatt-scale supercluster whose first phase is complete and was used to train the Muse family of foundation models. Because one failing host can slow an entire large training job, Meta focused on system stability and reached more than 85% goodput on Muse Wonder pre-training runs and more than 90% on reinforcement learning runs. The cluster now spans hundreds of thousands of GPUs, with a target of roughly one million at full scale.