CoreWeave

CoreWeave offers a massive scale of NVIDIA GPUs, ranging from H100s and A100s for heavy training to L40S and RTX 6000 Ada generation cards for inference and rendering. This variety allows users to match their specific workload requirements with the most cost-effective and performant hardware available.

CoreWeave is built on a bare-metal Kubernetes stack that eliminates the virtualization overhead found in legacy clouds. This architecture provides significantly faster networking and disk I/O, ensuring that your AI models train faster and inference requests are processed with lower latency.

CoreWeave's orchestration layer allows for the rapid provisioning of multi-node clusters in minutes rather than hours. Our high-speed InfiniBand interconnects ensure that these nodes communicate with the low latency required for distributed training across hundreds of GPUs.

Yes, we offer a variety of Cloud Templates and container images optimized for tasks like LLM fine-tuning, stable diffusion, and 3D rendering. These templates come pre-loaded with the necessary drivers and libraries, significantly reducing the time from setup to execution.

Yes, CoreWeave provides a dedicated Terraform provider and full Kubernetes API access, allowing DevOps teams to automate infrastructure deployment. This ensures that your GPU resources can be integrated into existing CI/CD pipelines and managed as code for better scalability.

CoreWeave is fully compatible with all major ML frameworks including PyTorch, TensorFlow, and JAX. Because we provide a standard Kubernetes environment, you can run any containerized workload or utilize pre-configured NVIDIA NGC containers to get started immediately.

We provide flexible billing options including transparent hourly on-demand rates for burstable workloads and reserved instance pricing for long-term projects. Reserved instances offer significant discounts for users who need guaranteed capacity for sustained AI training or production inference.

Unlike many large cloud providers, CoreWeave offers a much more predictable cost model with zero or significantly reduced egress fees. This makes it highly economical for data-intensive machine learning projects that require moving large datasets or model weights frequently.

CoreWeave maintains SOC 2 Type II compliance and adheres to strict data privacy standards to ensure your proprietary models and datasets are protected. Our data centers feature enterprise-grade physical security and network isolation to prevent unauthorized access to your compute resources.

No, CoreWeave provides a private cloud environment where your data and model weights remain exclusively yours. We do not use customer data for any internal model training, ensuring that your intellectual property and competitive advantages are fully preserved.

Enterprise customers have access to dedicated solutions architects and 24/7 technical support from engineers who specialize in GPU infrastructure. We provide Slack-based support channels and rapid response times to ensure your production AI workloads never experience downtime.

Our comprehensive documentation portal includes step-by-step migration guides, API references, and best practices for transitioning workloads from legacy clouds. We also offer professional services to help large organizations architect their move to a GPU-native cloud environment.