CoreWeave
CoreWeave Cloud is an AI‑native GPU infrastructure platform delivering managed Kubernetes, rack‑scale NVIDIA systems, low‑latency networking, and high‑performance storage. Teams train, fine‑tune, and serve models faster with automated lifecycle management, deep observability, zero‑egress data migration, and industry‑leading MLPerf results.
Overview
Provision GPU clusters in minutes, attach high‑throughput storage, and deploy training jobs or inference services through a familiar Kubernetes interface. Monitor health and utilization with Mission Control, scale capacity plans when demand spikes, and iterate quickly using ARENA before promoting workloads to production.
Capabilities
CoreWeave suits AI labs training frontier models, platform teams operating multi‑tenant clusters, and enterprises modernizing ML platforms with predictable performance. It’s a strong fit for agentic systems, large‑scale inference, and continuous fine‑tuning workflows. Media and VFX studios benefit from elastic GPU rendering, while regulated industries gain transparent operations, security features, and auditable controls through Mission Control. MLOps, infra, and research teams can jointly optimize throughput, reliability, and cost without rewriting pipelines.
- Spin up Kubernetes‑native GPU clusters with automated provisioning and health‑checked lifecycle operations.
- Run serverless or dedicated inference to match strict latency and throughput targets.
- Validate scaling, performance, and cost in ARENA before committing production capacity.
- Migrate datasets with zero egress fees to AI object or distributed storage.
- Gain deep observability, audit visibility, and security with Mission Control.
Why CoreWeave stands out
Architecture and operations
Create an account, choose a capacity plan, and provision GPUs via the Kubernetes API or Helm. Use Zero Egress Migration to transfer datasets into AI object or distributed storage. Deploy training jobs with your preferred frameworks, then stand up serverless or dedicated inference for production traffic. Monitor health, performance, and cost with Mission Control, and iterate in ARENA to validate scaling and architecture choices before committing long‑term. Reference MLPerf results to guide instance selection for specific models and latency‑throughput goals.
Purpose‑built AI cloud delivering reliable performance, transparent operations, and faster time to results.
Getting started
CoreWeave unifies GPU compute, Kubernetes operations, storage, and observability into a coherent platform for AI builders. With rack‑scale systems, zero‑egress migration, strong MLPerf results, and ARENA for validation, teams ship faster while maintaining reliability and transparency. It’s a pragmatic path to scale without surrendering control.
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CoreWeave
CoreWeave builds an AI‑native cloud that pairs cutting‑edge NVIDIA GPUs with Kubernetes‑first operations, high‑performance networking, and robust data services. The company focuses on reliable training, inference, and agentic workloads at scale, backed by deep engineering support and transparent operations.
CoreWeave Cloud is an AI‑native infrastructure platform for training, inference, and agentic workloads. It pairs next‑generation NVIDIA GPUs (Vera Rubin NVL72, Blackwell, Hopper, Ada) with a Kubernetes‑native developer experience, automated provisioning, and high‑performance networking. Managed services deliver cluster health checks, lifecycle automation, observability, and security through Mission Control. Data services include AI object storage, distributed file storage, dedicated VAST storage, and zero‑egress migration to onboard large datasets without lock‑in. Teams can validate performance and scaling in CoreWeave ARENA before committing to production capacity. Multiple runtime paths—serverless RL, serverless inference, and dedicated inference—let builders match latency, throughput, and cost goals. Consistent leadership in MLPerf underscores performance across training and serving at scale.
www.coreweave.com/
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