Get game-changing access to compute at scale for high-throughput and low latency AI inference.
CoreWeave’s cloud infrastructure is made to handle the computing demands of running modern-day AI inference workloads, helping you bring innovations to market faster. Our customers get access to the latest and greatest NVIDIA GPUs for ultra-high performance, low costs per token, and ease of use.
With a full stack of cloud services, you can focus on accelerating the deployment of your AI applications—and leaving managing infrastructure to us.
Get the latest and greatest NVIDIA GPUs, coupled with other cutting-edge hardware components—such as latest generation CPUs and networking interconnects and offered as bare-metal instances.
That helps deliver record-breaking performance, enabling your teams to get the most throughput out of your GPUs, lower inference latency, and industry-leading price-to-performance.
With no virtualization layer, get full performance out of your compute infrastructure, coupled with industry-leading observability.
Streamline Kubernetes management with pre-installed, pre-configured components via CKS.
With InfiniBand support for multi-node inference—get access to the most capable infrastructure for running trillion parameter count AI models in production.
GenAI models need a lot of data—and they need it fast. Handle massive datasets with reliability and ease, enabling better performance and faster training times.
With a choice of using local instance storage, AI Object Storage, or Distributed File Storage services, pick the right storage solution for the right application. All purpose-built for AI.
Our GPU instances provide up to 60TB of ephemeral storage per node—ideal for the high-speed data processing demands of AI inference.
CoreWeave AI Object Storage is a high-performance S3-compatible storage service designed for AI/ML workloads, with cutting-edge Local Object Transport Accelerator (LOTA™) technology.
LOTA™ caches objects on GPU nodes' local disks, reducing latency and enabling data access speeds of up to 2 GB/s/GPU. This purpose-built storage helps customers accelerate their AI initiatives by providing faster data retrieval, enhanced scalability, and cost-effective storage, all while seamlessly integrating with existing workflows.
Our Distributed File Storage offering is designed for parallel computation setups essential for Generative AI, offering seamless scalability and performance.
CoreWeave Tensorizer accelerates AI model loading, so your platform is ready to quickly support any changes in your inference demand,
Tensorizer revolutionizes your workflow by dramatically reducing model loading times. Your inference clusters can quickly scale up or down in response to application demand, optimizing resource utilization while maintaining desired inference latency.
Tensorized works by serializing AI models and their associated tensors into a single, compact file. This optimizes data handling and makes it faster and more efficient to manage large-scale AI models.
Tensorizer enables seamless streaming of serialized models directly to GPUs from local storage in your GPU instances or from HTTPS and S3 endpoints. This minimizes the need to package models as part of containers, giving you greater flexibility in building agile AI inference applications.
Ditch the case of underutilized GPU clusters. Run training and inference simultaneously with SUNK—our purpose-built integration of Slurm and Kubernetes that allows for seamless resource sharing.
Share compute with ease. Run Slurm-based training jobs and containerized inference jobs—all on clusters managed by Kubernetes.
Effortlessly scale up or down your AI inference workloads based on customer demand. Use remaining capacity to support compute needs for pre-training, fine-tuning, or experimentation—all on the same GPU cluster.
Gain enhanced insight into essential hardware, Kubernetes, and Slurm job metrics with intuitive dashboards.
Work on a platform made to support AI inference, not retrofit for it after the fact.
