CoreWeave Sandboxes

About CoreWeave Sandboxes

On May 14, 2026, CoreWeave announced the launch of CoreWeave Sandboxes, an execution layer designed to provide secure, isolated environments for AI researchers and platform teams. These sandboxes are specifically tailored for running reinforcement learning (RL), agent tool use, and model evaluation workloads. CoreWeave Sandboxes addresses the need for secure and isolated environments in advanced AI workflows, which often require safe code execution, state persistence across multiple steps, and scalability for concurrent workloads. Many organizations currently rely on custom-built systems or loosely integrated tools, which can become challenging to manage, less reliable, and difficult to govern as complexity and scale increase. Key features and benefits of CoreWeave Sandboxes include: secure and isolated environments (each sandbox operates in its own isolated virtual environment with hardware-enforced isolation using NVIDIA BlueField-3 DPUs); unified execution layer (single, consistent layer for RL, agent tool use, and model evaluation); flexible access models (deployable on customer's CoreWeave infrastructure or as serverless runtime through Weights & Biases); scalability and concurrency (designed for scale, handles multiple concurrent jobs, used by IBM Research with thousands of parallel sandboxes per training step); ease of use (includes Python SDK for creating/managing isolated environments, built-in session management, storage integration, monitoring tools); and enhanced security posture (security emphasized at every layer from hardware to orchestration for data protection, network isolation, and granular identity controls).

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AI researchers, platform teams, and organizations needing secure, isolated environments for reinforcement learning, agent tool use, and model evaluation workloads at scale.

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