A neocloud is worth adding to your stack when GPU price, availability, or interconnect performance for your workload beats what your hyperscaler offers by enough to cover the cost of running a second environment. Evaluate it on workload fit, networking, capacity and lead times, reliability, compliance, integration time, and total price. Control Plane lets teams add a neocloud GPU cluster as another location next to AWS, GCP, or Azure and run the same workloads across them from a single definition, which cuts integration time.

Disclosure: Control Plane publishes this guide.

TL;DR

Core evaluation criteria:

Workload fit: Does the provider offer the GPU model, memory, and cluster topology your training or inference job needs?

Networking: Does the interconnect (InfiniBand, RoCE, or EFA) support your distributed training communication patterns?

Capacity and lead times: Can you get the GPUs you need, when you need them, at a commitment term that matches your planning horizon?

Reliability: What uptime SLA…