Beam is a GPU compute platform built specifically for AI workloads. It handles serverless inference, durable task queues, and isolated sandboxes, all defined in Python without Dockerfiles or YAML config. You can run on Beam's cloud or connect your own AWS, GCP, or bare metal accounts and let Beam orchestrate across all of them.

The core differentiator is boot time. Beam uses memory snapshots to restore GPU containers in under a second, up to 35× faster than a traditional cold start. That matters when you're running inference at scale or building agent pipelines where latency compounds quickly.

Key capabilities:

• GPU inference endpoints – deploy models on H100s, A10Gs, or 4090s with autoscaling baked in. Scale to zero when idle, burst to hundreds of containers when traffic spikes.
• Task queues – durable, queue-depth-based autoscaling with automated retries, scheduled jobs, and event callbacks. Good for batch workloads like transcription or document processing.
• Sandboxes – stateful, long-running environments for AI agents. Attach persistent storage, run Docker-in-Docker, snapshot the filesystem, and branch into thousands of parallel isolated runs.
• Multi-cloud routing – workloads route across clouds and 30+ regions in real time, keeping execution close to your users.
• CI/CD integration – deploy directly from GitHub Actions without changing your workflow.

Compared to tools like Modal or dstack, Beam leans hard on the sandbox and snapshotting story, which makes it a natural fit for agent frameworks that need stateful, parallelizable execution environments.

Pricing starts at $0.69/hr for a 4090, with $30 in free credits refreshed monthly. SOC 2 Type II certified.

Most AI agents run on disposable sandboxes: spin up, execute a task, disappear. That works for throwaway scripts. It breaks down the moment an agent needs to remember what it installed, keep files between sessions, or pick up mid-task after a pause. OpenComputer is built for that second category.

Each VM is a real machine with a full filesystem and full OS access. It stays running until you explicitly stop or delete it. No timeouts, no teardowns. State persists across sessions without any extra plumbing on your end.

Key capabilities:

• Persistent VMs: always-on instances that survive across agent sessions, so nothing gets re-installed from scratch because a container timed out
• Hibernate and wake: when a VM isn't needed, hibernate it and restore it in seconds, state exactly where you left it
• Elastic compute: resize memory and CPU while the VM is running, no restart required, useful when workload spikes mid-session
• Checkpoints: instant snapshots let you fork or roll back to any previous state, handy when an agent puts the VM in a bad spot
• Agent framework support: purpose-built to run agent harnesses like the Claude Agent SDK
• Scale: runs to thousands of VMs in the cloud, billed only while running

OpenComputer targets teams building agent platforms where end users expect continuity. Think coding assistants like Devin or Lovable, where a user's environment needs to remember yesterday's installs and today's open files. Ephemeral sandboxes give isolation. OpenComputer gives isolation plus persistence, without forcing you to manage state externally.

Pricing starts at $0.004 per minute for a 4 GB / 1 vCPU configuration. Disk beyond the included 20 GB is metered separately, and hibernated VMs don't accrue compute charges.