CoreWeave
GPU cloud infrastructure built for large-scale AI training and inference workloads
CoreWeave operates 32+ data centers with over 250,000 GPUs, purpose-built for AI workloads on a Kubernetes-native architecture. Offers NVIDIA A100, H100, and GB200 GPUs with usage-based, per-minute billing and no data transfer fees. Full 8-GPU HGX nodes start around $49/hr with up to 60% discounts for committed usage. Backed by a $2 billion investment from NVIDIA. Primarily serves enterprise customers for large-scale model training and inference.
Pricing: Usage-based
What CoreWeave is
CoreWeave is a GPU cloud built for large-scale AI training and inference. It targets the high end of the market: multi-node clusters of current NVIDIA hardware with InfiniBand networking, aimed at teams running demanding workloads rather than single-GPU experiments.
GPUs and pricing
The lineup runs from A100 and L40S up to the latest Blackwell systems (HGX B200, GB200 NVL72, GB300 NVL72) alongside HGX H100 and H200. On-demand rates are quoted per 8-GPU node (per their pricing page, June 2026): an HGX H100 node lists at $49.24/hr, A100 at $21.60/hr, L40S at $18.00/hr, and HGX B200 at $68.80/hr. Spot instances cut roughly 35-50% off on-demand, and reserved capacity advertises up to 60% off for committed usage.
Networking and extras
Internal and internet data transfer are free, public IPs are $4/month, and Direct Connect ranges from $1,250 to $50,000/month by speed. The platform leans toward managed Kubernetes and Slurm for orchestration.
Who it fits
CoreWeave fits teams that need a lot of GPUs wired together with fast interconnect, for training large models or running high-throughput inference. It is less oriented toward someone who just wants a single GPU by the hour. For that, a marketplace like Vast.ai or a per-minute provider like Lambda or Hyperstack is a closer match.
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