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superserve vs tensorlake

Persistent, secure sandboxes for AI agents on Firecracker microVMs — TypeScript and Python SDKs, CLI and console; the runtime is a hosted service, the SDK stack is Apache-2.0. — versus — Serverless platform for agent sandboxes: stateful Firecracker microVMs with snapshots, cloning, auto suspend/resume and network policy, plus fan-out orchestration functions. Python SDK and CLI.

The curated verdict

Both sell persistent Firecracker microVM sandboxes for agents with an open SDK over a hosted runtime; Tensorlake adds snapshots and cloning, live migration and a serverless fan-out layer.

superservetensorlake
Stars4641.0k
Forks54148
LanguageTypeScriptPython
LicenseApache-2.0Apache-2.0
Last activityyesterdaytoday
Topicssandboxes, agentssandboxes, agents
Curated connections54

superserve — the curator's take

The pitch is persistence: sandboxes that survive between agent runs instead of being disposable, on Firecracker isolation. Know what the repo is before starring: this is the SDK/CLI/console monorepo — the actual sandbox runtime lives behind the hosted service at superserve.ai, and the README is a contributor doc, not a product doc (the substance is at docs.superserve.ai). Use it when you want managed microVM sandboxes with a clean SDK and don't want to run KVM hosts; NOT for air-gapped or self-hosted requirements — that's CubeSandbox's territory. Young project, small community — evaluate the service's durability before building on it.

tensorlake — the curator's take

Pick Tensorlake when you want hosted sandboxes that behave like real machines: stateful Firecracker VMs that suspend when idle and resume with memory intact, snapshot and clone mid-run, live-migrate, and take per-sandbox egress allowlists, plus a serverless function runtime to fan out agent work with each function in its own sandbox. This repo is the SDK and CLI; the runtime is Tensorlake Cloud, so it is an API key, not something you self-host. The filesystem benchmark against E2B, Modal and Daytona is their own. Need it on your own hardware? cubesandbox or agent-sandbox. Running one agent's code locally? A container may be enough.