Nebius vs CoreWeave: 27% Cheaper On-Demand vs. Zero-Egress Frontier Scale

Nebius challenges the market standard by setting its on-demand HGX H100 pricing at $4.50 per GPU-hour, a roughly 27% discount against CoreWeave's $6.16 per GPU-hour baseline. For smaller AI development setups, this gap expands further due to packaging policies: CoreWeave mandates full 8-GPU node increments ($49.24 per node-hour), whereas Nebius allows provisioning isolated single-GPU VMs.

Furthermore, Nebius meters compute in true 1-second intervals. CoreWeave bills on an hourly basis, meaning short automated test suites, CI/CD evaluation loops, and spot-like batch inference workloads end up paying for unused headroom when spinning down instances within the hour.

Both providers deploy non-blocking 3.2 Tbps NVIDIA Quantum-2 InfiniBand networks with GPUDirect RDMA for multi-node training clusters. However, their total cost models diverge drastically once training checkpoints leave the internal fabric. Nebius charges standard cloud egress rates around $0.015 per GiB for external traffic.

CoreWeave differentiates itself by completely waiving internet data egress charges. For foundational model training teams streaming hundreds of terabytes of model weights to external object stores, datalakes, or customer endpoints, zero egress creates predictable runway and can offset CoreWeave's higher base compute rates.

The commercial decision hinges on cluster duration and scale. For short-term contracts under 12 months, mixed workloads, or cluster footprints below 32 GPUs, Nebius is structurally more economical due to lower on-demand rates and per-second elasticity.

CoreWeave dominates when entering 1 to 3 year take-or-pay commitments for dedicated clusters of 64 or more GPUs. With maximum enterprise discounts reaching up to 60%, the effective rate drops to ~$2.46 per H100 hour, giving continuous frontier pre-training operations an unmatched sustained-use cost profile.