AI developers aren’t just running a single model anymore—they’re orchestrating multiple models in parallel, chaining inference calls, and experimenting with frontier-class architectures that demand hundreds of gigabytes of memory. NVIDIA DGX Spark was built to bring AI development to the desk, and now you’ll be able to link even more Spark nodes together.

At GTC Berlin, NVIDIA announced official support for eight-node DGX Spark clusters, scaling unified memory to 1 TB and opening the door to frontier-class models, multi-agent workloads, and near-linear pre-training—all running locally.

NVIDIA Sync makes it easy to cluster. Its Cluster Assistant handles setup and device management. Support for eight-node clusters in NVIDIA Sync is coming by the end of the year.

Read on for benchmark data on how inference, orchestration, and training scale as the cluster grows.

Run larger, newer frontier-class models

The biggest benefit of an eight-node cluster is memory.…