Is CoreWeave a managed inference service?

CoreWeave is an AI Cloud platform purpose-built to run inference and agentic runtimes in production, with direct access to high-performance GPU infrastructure, AI-native orchestration, and CoreWeave Mission Control visibility from metal to model. Teams can deploy and operate their own inference services on CoreWeave, and for a faster start, W&B Inference powered by CoreWeave provides an integrated, managed entry point for serving and evaluating models.

AI Inference | CoreWeave Solutions

AI inference that sustains performance under real-world demand

Built on a best-in-class GPU cloud, engineered for reliable performance and cost predictability at scale.

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Inference complexity compounds at scale

AI applications and agents do not fail in development. They fail in production, under real traffic, fluctuating demand, and sustained cost pressure. As models move from experimentation to continuously operated services, performance stability, availability decisions, and cost drivers become intertwined.

Without architectural clarity, teams are forced to choose between speed and control. Innovation slows when inference behavior is hard to predict, scale, or explain.

Why production inference
breaks down at scale

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Continuous refinement under live demand becomes fragile

Inference does not stand still once deployed. Models and agents evolve, prompts change, traffic fluctuates, and new features launch under live conditions. Without integrated observability and purpose-built infrastructure, refinement slows, risk increases, and iteration becomes operationally expensive.

Innovation should not distort economics

AI teams must experiment, launch, scale, and sometimes shut down workloads quickly. Innovation slows when cost drivers are hard to explain or availability tradeoffs are unclear. CoreWeave preserves economic clarity across the inference portfolio, so teams can move fast while keeping performance, availability decisions, and spend predictable as usage changes.

Flexibility must scale with inference

Some inference approaches are designed for rapid starts and are a great fit early on. As teams need more control over infrastructure, architectures must evolve with model innovation and performance needs. As requirements mature, broader runtime choices and portable execution models help avoid constraints over time. CoreWeave Inference preserves flexibility with explicit GPU type choice and open runtimes.

Introducing guided self-service
for SUNK (in preview)

Bring SUNK clusters online through a guided, opinionated setup experience based on CoreWeave best practices. SUNK allows teams to get started faster while maintaining the control expert users need. Now available as a preview for existing CoreWeave customers.

Request preview access

CoreWeave Cloud platform
for AI inference

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Serverless Inference

With W&B Inference, you can deploy AI agents instantly without managing infrastructure. Built for rapid iteration, evaluation, and refinement, serverless inference provides autoscaling, high availability, and integrated observability out of the box. Pay-per-token pricing enables teams to move fast while maintaining o deep control as workloads grow.

Dedicated Inference (in preview)

Run custom models in production on explicitly chosen GPUs with CoreWeave-operated execution. Designed for reliable performance and cost predictability at scale, Dedicated Inference preserves explicit GPU selection and open runtimes while reducing operational burden. Ideal for teams moving from experimentation into sustained production workloads.

Inference on CKS

Operate fully self-managed inference on CoreWeave Kubernetes Service (CKS) with complete control over GPU selection, runtime configuration, and scaling behavior. Built for advanced workloads and infrastructure ownership, Inference on CKS supports multi-node deployments, custom runtimes, and deep tuning for latency-sensitive or high-throughput AI applications.

Explore the CoreWeave Cloud Platform

Optimize AI inference with fast storage solutions

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AI models need a lot of data—and they need it fast. CoreWeave empowers you to handle massive datasets with reliability and ease, enabling better performance and faster training times.

For inference, experience 5x faster model download speeds and 10x faster spin up times. Your inference at scale is more performant and cost effective.

With a choice of using local instance storage, AI Object Storage, or Distributed File Storage services, you can pick the right storage solution for the right application. All purpose-built for AI.

Local Instance Storage

Our GPU instances provide up to 60TB of ephemeral storage per node—ideal for the high-speed data processing demands of AI inference.

AI Object Storage with LOTA

CoreWeave AI Object Storage is a high-performance S3-compatible storage service designed for AI/ML workloads, with cutting-edge Local Object Transfer 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.

Fast Distributed File Storage Services

Our Distributed File Storage offering is designed for parallel computation setups essential for AI, offering seamless scalability and performance.

Proven by leading pioneers at production scale

See more customer stories

CoreWeave gives Goodfire the dedicated GPU backbone we need to ship realtime AI features with confidence. On CKS we get predictable, single‑tenant performance, tight integration with our frontier model inference stack, and the flexibility to tune our deployments without taking on cluster ops. That combination lets our team focus on iterating on Goodfire's research and product, while CoreWeave handles the heavy lifting of running the GPU backbone in production at scale.

Daniel Balsam

Co-founder and CTO, Goodfire

Working with CoreWeave Inference has dramatically simplified how we fine-tune, ship, and scale our models. They take GPU management completely off our plate, which lets our team focus on product. CoreWeave’s infrastructure just works, and that peace of mind around scaling has made them an invaluable partner to our team.

Mustafa Ali

Founding Software Engineer, Method

Cline is the leading open-source, agentic coding platform for large global enterprises. As adoption grows, so does the need for scalable inference capacity, especially for companies seeking to remain model agnostic. We use the serverless inference in Weights & Biases to support enterprise-ready environments for our most security-sensitive customers.

Saoud Rizwan

Founder, Cline

Frequently Asked Questions

What is AI Inference?

Inference is the process of running a trained model to generate outputs, such as text, images, predictions, or decisions, in response to live inputs. In production systems, inference must be fast, reliable, and scalable.

Does CoreWeave offer an inference service?

CoreWeave provides the infrastructure, orchestration, and operational visibility required to run inference and agentic AI in production. Teams can deploy and operate their own inference services on CoreWeave’s purpose-built AI cloud, or use integrated offerings such as Weights & Biases Inference powered by CoreWeave. This approach gives customers flexibility without locking them into a single runtime or abstraction.

How is agentic AI related to inference?

Agentic AI is inference that runs in loops. Instead of a single request-response, agents plan, retrieve context, call tools, and iterate, making tail latency, burst throughput, and operational visibility more important because small issues compound across steps. CoreWeave is optimized for both classic model serving and agentic inference runtimes.