Modal Agent Runtimes

Verified capabilities

• Code-first cloud runtime

  Modal lets developers bring their own code, stay in Python, and use the Modal SDK to specify logic, hardware, and cloud environment configuration in one place.[1]

• Agent sandboxes

  Modal Sandboxes are positioned as an execution layer for AI systems, supporting isolated, ephemeral environments for coding agents, background agents, untrusted code, and large-scale rollout environments.[1]

• Autoscaling compute

  The platform describes sub-second cold starts, instant autoscaling, scale-to-zero behavior, and the ability to route workloads across clouds and regions to access GPU capacity without commitments or capacity planning.[1]

• Inference serving

  Modal supports LLM inference, multi-modal inference, batch and async inference, online inference, token streaming, WebRTC, and WebSocket use cases across GPUs such as H100s, A100s, and A10Gs.[1]

• Training workflows

  The platform supports fine-tuning, reinforcement learning, multi-node training, and parallel hyperparameter sweeps, including single- and multi-GPU workloads.[1]

• Observability and production controls

  Modal advertises integrated logging, visibility into functions, sandboxes, and containers, team controls, isolation, SOC2 and HIPAA references, and data residency controls.[1]

• On-demand GPU infrastructure

  Modal describes GPU-accelerated research with H100s, A100s, and A10Gs available on demand, attachable to sandboxes, scalable to thousands of concurrent runs, and billed by the second with no reserved capacity.[1]