Choosing a sandbox for reinforcement learning and agent evals
RL rollouts and evals need thousands of identical environments, cheap reset, and snapshot forking to branch many attempts from one prepared state, all on per-second billing. Check each provider’s documented concurrency limits and fork speed. Compute platforms (Modal) lead on raw scale and GPUs, while snapshot-first VMs (Morph, Freestyle) lead on branching. Labs with their own clusters often run Kubernetes Agent Sandbox.
What RL training and evals need from a sandbox
Training or evaluating agents on real tasks means running thousands of identical environments, resetting them constantly and comparing outcomes:
- Concurrency in the thousands to hundreds of thousands.
- Snapshots and forking to branch many rollouts from one prepared state.
- Fast reset and per-second billing so short episodes are cheap.
- Reproducibility — identical images and deterministic setup.
- Sometimes GPUs alongside the environment.
Sandboxes that fit, by kind
10 sandboxes document what this workload needs. They are grouped by kind and listed alphabetically; the order is not a ranking. Shortlist two or three, then pilot them with your own workload.
Hosted sandbox platforms
SDK-driven sandboxes you create, run code in and destroy through an API.
Daytona
Stateful sandboxes for AI-generated code — Linux containers, Linux and Windows VMs, macOS and GPU sandboxes — with snapshots, volumes and preview URLs.
- Containers or VMs
- BYOC
- GPU
- Pause/resume
Why it fits: Fast creation, snapshots and fork on VM sandboxes, plus GPU sandboxes up to 8 GPUs.
E2B
Open-source cloud sandboxes for AI agents, each a Firecracker microVM, with pause/resume, snapshots and forking.
- Firecracker microVM
- Open source
- Self-hostable
- BYOC
- Pause/resume
Why it fits: Snapshots of running sandboxes with forking into many copies, microVM isolation and concurrency add-ons up to 1,100 on Pro (more on Enterprise).
Tensorlake Sandboxes
MicroVM sandboxes with memory snapshots, copy-on-the-fly cloning, warm pools and egress policy, alongside hosted Git and a versioned filesystem, with an Apache-2.0 runtime and BYOC on AWS.
- MicroVM (gVisor for GPU)
- Open source
- Self-hostable
- BYOC
- GPU
- Pause/resume
Why it fits: Memory snapshots, cloning and warm pools at scale for RL rollouts and agent harnesses, on Firecracker and Cloud Hypervisor VMs.
Persistent VMs and agent computers
Full, long-lived virtual machines that an agent keeps, forks and returns to.
Freestyle
Full Linux VMs for AI agents with live forking of running VMs, memory-preserving hibernation, VPCs and nested virtualization.
- VM
- Pause/resume
Why it fits: Live forking of running VMs including memory, for branching rollouts from a warm state.
Morph Cloud
VM-based cloud computers for AI agents built on “Infinibranch” snapshot, branch and restore, plus persistent Devboxes.
- VM
- Pause/resume
Why it fits: Snapshot-and-branch infrastructure designed for running many parallel agent attempts from the same state.
Compute platforms with sandboxes
General serverless or app platforms that also offer sandboxes, often with GPUs.
Modal Sandboxes
Sandboxes on Modal’s serverless compute platform for running untrusted code at very high scale, with GPUs, snapshots and tunnels.
- gVisor or VM
- GPU
- Pause/resume
Why it fits: Scheduler tested with over a million concurrent sandboxes, memory and filesystem snapshots, and GPUs in-sandbox — the most complete scale story.
Prime Sandboxes
Disposable, hardware-isolated microVMs that boot OCI images with Docker inside, built for agentic RL rollouts at the scale of thousands of concurrent sandboxes.
- microVM, own kernel
- Pause/resume
Why it fits: Thousands of Docker-capable microVMs at low hourly cost, built for RL environment rollouts and agent evaluations.
Open-source runtimes to self-host
Open-source sandbox runtimes you run on your own servers or Kubernetes.
Kubernetes Agent Sandbox
Open-source Kubernetes controller and CRDs for isolated, stateful sandbox pods for AI agents, with first-class support on GKE.
- gVisor or Kata
- Open source
- Self-hostable
- BYOC
- GPU
- Pause/resume
Why it fits: For labs with their own clusters: warm pools and Pod snapshots on Kubernetes, with GPUs and TPUs on GKE.
OpenHands Runtime
The sandbox layer of the OpenHands agent SDK: an agent server that runs in a Docker container, in-process locally, or on the hosted OpenHands Runtime API.
- Docker container
- Open source
- Self-hostable
Why it fits: Disposable Docker sandboxes for OpenHands agents, with a hosted runtime option for large evaluations.
SWE-ReX
Runtime interface from the SWE-agent team for running agent shell sessions locally or in Docker, Modal and AWS Fargate sandboxes, built for massively parallel runs.
- Docker / Modal / Fargate
- Open source
- Self-hostable
Why it fits: Open-source runtime for running many SWE-agent-style shell sessions in parallel across local, Docker, Modal or Fargate backends.
Side by side
| Sandbox | Isolation | Open source | Self-host / BYOC | Cold start (vendor) | Max session | Snapshots / pause | GPU | SDKs |
|---|---|---|---|---|---|---|---|---|
| Daytona | Containers or VMs | No | Not documented / Yes | <90 ms | Unlimited | Yes / Yes | Yes | Python, TypeScript, Ruby, Go, Java |
| E2B | Firecracker microVM | Yes | Yes / Yes | Not documented | 1 h / 24 h (Pro) | Yes / Yes | No | Python, JavaScript/TypeScript |
| Freestyle | VM | No | No / Not documented | 65 ms | Unlimited (paid) | Yes / Yes | Not documented | TypeScript |
| Kubernetes Agent Sandbox | gVisor or Kata | Yes | Yes / Yes | <1 s (warm pool) | Not documented | Yes / Yes | Yes | Kubernetes CRDs, Python, kubectl |
| Modal Sandboxes | gVisor or VM | No | No / Not documented | <1 s | Up to 24 h | Yes / Yes | Yes | Python, JavaScript/TypeScript, Go |
| Morph Cloud | VM | No | No / Not documented | <250 ms (restore) | Configurable | Yes / Yes | Not documented | Python, TypeScript |
| OpenHands Runtime | Docker container | Yes | Yes / No | Not documented | Not documented | Not documented / Not documented | Not documented | Python, JavaScript/TypeScript, REST API |
| Prime Sandboxes | microVM, own kernel | No | No / No | Not documented | 60 min default, unlimited | Yes / Yes | No | Python, CLI, REST API |
| SWE-ReX | Docker / Modal / Fargate | Yes | Yes / No | Not documented | Not documented | No / Not documented | Not documented | Python, REST API |
| Tensorlake Sandboxes | MicroVM (gVisor for GPU) | Yes | Yes / Yes | ~100s of ms (claim) | 2 h / 24 h / unlimited (Pro) | Yes / Yes | Yes | Python, JavaScript/TypeScript, Rust, CLI, REST API |
Frequently asked questions
Which sandboxes handle large-scale RL rollouts?
Cite this page
Agent Sandboxes. (2026). Choosing a sandbox for reinforcement learning and agent evals. agentsandboxes.org. Last reviewed November 9, 2026. https://agentsandboxes.org/use-cases/rl-and-evals/
Found an error or a missing sandbox? Submit a correction — every entry links to the sources it relies on.