CPU Compute

At the frontier, the compute split has moved from 90 percent pre-training to roughly half. The gap shows up as queued rollouts, delayed evals, and iterations waiting on the loop’s slowest half.

Sandbox and RL fleets spike to hundreds of thousands of concurrent environments per training step, then fall to near idle. Reserve for the peak and it sits empty; run on-demand and the training step waits.

Published benchmarks rarely reflect how your own workloads behave. A wrong match is costly and sticky, paid back in porting work, stranded reservations, and re-validation.

No hypervisor overhead, no noisy neighbors, no shared tenancy. The throughput you validated in the PoC is the throughput your fleet delivers.

Vera’s Spatial Multithreading gives every thread its own share of the processor, and a DPU on each node keeps infrastructure work off your sandboxes’ cores.

Agent work is branch-heavy and memory-bound. Up to 1.8x faster agentic sandbox execution versus comparable x86, with 3x the memory bandwidth per core.

Steady load on committed CKS and SUNK capacity, spikes on serverless, through the same control plane as your GPU fleet. You buy the shape of your workload, not its worst hour.

CoreWeave Sandboxes runs RL, agent tool use, and evaluation environments on the same infrastructure as your training. One operational surface at any burst size.

Rollout generation and preprocessing tolerate interruption. Spot at up to 60 percent savings, with a 7-minute preemption warning to checkpoint and drain cleanly.

EPYC and Xeon bare metal today, Vera coming soon, all under the same CKS, SUNK, and Mission Control operating model. The workload moves between silicon; your tooling doesn’t.

Vera brings ARM instances consistent with the hosts inside modern GPU systems, alongside CoreWeave’s x86 fleet. One toolchain, and the dual-validation tax goes away.

Workload-fit guidance drawn from running agent, RL, and pipeline workloads at scale. Guided going in, reversible after: a working choice rather than a leap of faith.

The only cloud rated Platinum, twice running.

Top rating for managing distributed AI workloads.

Purpose-built execution environments inside existing training infrastructure reduce operational sprawl and fragility.