Northflank vs Runloop: AI sandboxes, pricing, and infrastructure compared

Northflank and Runloop both use microVM-based isolation for AI agents and untrusted code, but they address different scopes of the agent lifecycle. Runloop centers on persistent Devbox environments for coding agents, offering snapshots, suspend-and-resume workflows, networking controls, agent evaluation tools, and enterprise VPC deployment. Northflank positions its sandboxing as part of a wider application and AI infrastructure platform, extending isolation from agent development environments to the services, workers, jobs, databases, GPUs, preview environments, and production workloads agents create. It uses Kata Containers with Cloud Hypervisor primarily, while also supporting Firecracker and gVisor where available, and provides features such as private networking, persistent volumes, templates, workflows, BYOC deployments, observability, and enterprise governance. The comparison also highlights different persistence and scaling models: Runloop preserves Devbox state, whereas Northflank separates persistent data from compute workloads that can scale to zero or be recreated. According to the stated pricing example, Northflank’s published CPU and memory rates are lower, though actual costs depend on workload configuration and infrastructure choices.

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