Run agentic AI with predictable inference performance

Run agentic AI with predictable inference performance

Low latency inference, elastic throughput, and predictable unit economics are table stakes for running agents in production. CoreWeave Mission Control adds metal-to-model visibility to keep performance predictable as systems change.

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Reliable agentic AI needs reliable inference

Agentic systems run inference across multiple steps like planning, retrieval, tool use, and iteration. In production, latency compounds across steps, demand is bursty, and small regressions can quickly show up for users. To run agents reliably, teams need responsive performance under load, fast scale-up during spikes, and clear operational control as models, prompts, and tools evolve.

Inference optimized for agentic systems

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Low latency for agent workflows

Agentic' workflows stack latency across retrieval, tool calls, and response generation. CoreWeave keeps model responses times consistent under peak load with high-performance GPUs, fast networking, and high-speed interconnects. Fast model loading and caching reduce cold starts so agents stay responsive under real traffic.

Elastic throughput with predictable unit economics

Agent traffic is bursty. CoreWeave scales inference with demand to protect user experience during spikes and avoid waste when traffic falls. Built-in visibility helps teams keep unit economics predictable as agents, context, and tool calls increase.

Metal-to-model visibility for operational control

CoreWeave Mission Control delivers reliability, transparency, and actionable insights for agentic inference in production. It brings together security and audit visibility, expert-led services, and full-stack observability so teams can trace latency and behavior changes to releases and infrastructure, then recover faster with automation and runbooks.

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Exemplary inference. Validated by NVIDIA.

CoreWeave recently achieved NVIDIA Exemplar Cloud validation for inference, confirming our ability to deliver high-throughput, low-latency inference performance on modern GPU infrastructure. This enables agentic systems to stay responsive and consistent, even under bursty traffic.

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Infrastructure that powers agentic AI inference

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GPU Compute

Run distributed workloads with predictable performance and full control as your workloads scale into production. Purpose-built cloud infrastructure for serving  and running AI models, CoreWeave provides bare metal access to the latest architectures.

CoreWeave AI Object Storage

Simplify data management and ensure consistent access to large-scale training data throughout the model lifecycle. A high-performance object storage system built for AI training pipelines, CoreWeave AI Object Storage provides a single, global dataset accessible across clusters.

SUNK (Slurm on Kubernetes)

Run distributed workloads efficiently, isolating failures and managing GPU resources across complex research environments. SUNK is an AI-native research cluster designed for large-scale, distributed model training, combining Slurm scheduling with Kubernetes orchestration.

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Explore the CoreWeave Cloud Platform

Observe, evaluate, and improve agent behavior in production

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CoreWeave Mission Control is the operating standard for running AI workloads in the cloud. Working together with Weights & Biases, it allows you to understand agentic AI behavior in context. Monitor latency and errors, compare agent and model variants with structured evaluations, and roll out updates with clear versioning and lineage context.

With CoreWeave Mission Control + Weights & Biases you can:

  • Track live latency, throughput, and error rates
  • Compare variants with consistent evaluations
  • Validate changes with controlled rollouts (e.g., canary/shadow)
  • See version and lineage for models and datasets
  • Alert on anomalies before users are impacted

With end-to-end lineage, audit visibility, and real-time metrics, CoreWeave Mission Control plus Weights & Biases make inference both dependable and accountable—so teams can ship faster without sacrificing control.

W&B Inference

W&B Inference provides API and playground access to open-source LLMs so you can develop AI agents without standing up your own hosting. Bring your own Low Rank Adaption (LoRA) weights to run serverless inference with fine-tuned models.

W&B Registry

W&B Registry enables you to version models and datasets with lineage to improve auditability, rollback control, and clarity about what is serving and why.

W&B Weave

W&B Weave helps you evaluate, monitor, and iterate on agents without extra instrumentation, fragmented workflows, or complexity to deliver the best performing agents to production.

Powering next-gen quantitative research with scalable GPU compute

Read more customer stories

“CoreWeave has been an excellent provider for our machine learning and research workloads, combining the GPU infrastructure we need with the technical expertise to support it.”

Craig Falls
Head of Quant Research, Jane Street

Jane Street scales quant trading with the #1 AI Cloud

Jane Street is a global, technology-driven trading firm that depends on advanced quantitative research. As its workloads became increasingly GPU-intensive, the firm partnered with CoreWeave in 2024 to access secure, high-performance, fully managed GPU compute—enabling faster deployment, higher performance, and scalable training and inference.

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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.

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, Weights & Biases Inference powered by CoreWeave provides an integrated, managed entry point for serving and evaluating models.

How do you help teams hit tight latency SLOs for agents?

Low-variance latency comes from direct GPU access, high-bandwidth fabrics, and locality-aware scheduling so inference runs close to data. CoreWeave Mission Control provides full-stack visibility out of the box to track p50/p95/p99 and tune batching and concurrency with confidence.

What runtimes and model types can I run?

Run LLM, multimodal, vision, or speech models in containerized services with AI-native orchestration. Deploy agent services alongside retrieval and tool layers, and operate with integrated observability and audit visibility so production changes are understandable and accountable.

How do I control cost while scaling throughput?

Elastic capacity matches demand, and workload-aware orchestration keeps resources aligned to priority paths so you avoid constant overprovisioning. CoreWeave Mission Control turns raw signals into insight so you can right-size context, adjust batching, and keep cost-per-token predictable as traffic and agent behavior evolve.

What about reliability, transparency, and governance in production?

CoreWeave Mission Control unifies observability, security and audit visibility, and expert-led operations so teams can detect issues early, diagnose faster, and maintain verifiable trust. This high visibility is especially important for agentic systems, where failures can be intermittent, non-deterministic, and costly.

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On-demand webinar

Unlock Agentic Breakthroughs with a Purpose-Built AI Cloud

Unlock what it takes to run agentic AI in production. In this on-demand webinar, CoreWeave Solutions Architect Jacob Feldman and Forrester VP and Principal Analyst Mike Gualtieri break down the architectural and orchestration foundations required for high-performing agentic AI workloads. Learn how to overcome bottlenecks across data access, fine-tuning, reinforcement learning, and multi-step inference—and why purpose-built AI infrastructure is essential for delivering speed, reliability, and scale in real-world systems.

Watch on demand

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Run agents on an AI cloud built for low latency and elastic throughput, backed by CoreWeave Mission Control insight so you can scale with confidence.

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