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Fastest Agent Sandboxes Are Here
Instant, stateful execution environments for AI agents, spin up millions of VMs, auto-suspends when idle, resumes under a second.
Tye Davis
March 27, 2026
Tensorlake
Product Update · March 2026
Sandbox infrastructure hasn't kept up with agents.
We built one that has.
Introducing Sandboxes: execution environments built from the ground up for agents, developers, and the scale you actually need.
Sandboxes are in beta. We're offering free credits to developers who try Tensorlake Sandboxes and share their feedback. Whether you're building coding agents, running RL environments, or scaling parallel developer workflows, we want to hear what you build and what we can improve. Read the documentation to get started.
What's new
Sandboxes are foundational for building agents. They provide an isolated and stateful file system for agents to offload context from tool calls and to recall information.
We built a stateful sandbox infrastructure that enables deploying agents which start in a few hundred milliseconds, and scale down to zero while retaining the file system and memory of the sandbox to not lose any context when they restart again.
Why Tensorlake Sandboxes
Fastest filesystem in the business
Tensorlake built a state-of-the-art file system that achieves near-SSD speeds in virtual machines, enabling effortless data-intensive work in sandboxes. Independent benchmarks show they are approximately 2x faster than Vercel, 5x faster than E2B, and 1.5x faster than Daytona.
Sandboxes can live forever
Tensorlake seamlessly live-migrates sandboxes to healthy machines during cluster updates or security patches, causing only a brief blip of a few seconds for connected clients. Upon restoration, both memory and file-system state are precisely recovered to the moment of the snapshot.
Auto suspend and resume
Sandboxes can be put to sleep after a certain amount of time, and they boot up automatically when they receive any external traffic.
Serverless boot
Each Tensorlake sandbox gets its own URL and can be configured to timeout after inactivity, then automatically restart in milliseconds to a few seconds when invoked. They function like stateful serverless functions, spinning up on demand while preserving their state.
Does it scale?
Tensorlake can spin up hundreds of sandboxes per second, supporting up to 5 million sandboxes in a single project.
What powers this
Tensorlake's sandboxes are built on four core technical innovations:
Lattice
A dynamic cluster scheduler for high-throughput, fast resource allocation. It creates sandboxes with dynamic resources in under a second.
Fastest File System I/O
A block-based file system with near-SSD speeds, built with Tensorlake-specific modifications that enable better performance for coding agents and lazy memory snapshot loading.
Dynamic Cloning and Snapshotting
Clone running VMs across the network, auto suspend and resume based on activity inside sandboxes and network traffic.
Content-addressable filesystem
A purpose-built storage layer that deduplicates sandbox data, reducing storage costs and dramatically accelerating restoration from snapshots.
How we compare
While there are many sandbox infrastructure companies out there, we have a product which gets you more dynamic capabilities.
In SQLite benchmarks across all major sandbox providers, Tensorlake finishes in 2.45s, that's 1.2x faster than Vercel (3.00s), 1.6x faster than E2B (3.92s), 1.9x faster than Modal (4.66s), and 2.2x faster than Daytona (5.51s). Benchmarks are open-sourced and you can run them yourself: github.com/tensorlakeai/sandbox-sqlite-bench
Tensorlake sandboxes are built to live forever. While most sandbox providers cap environments at 24 hours, we built warm migration from the ground up. Sandboxes move to healthy machines automatically when we patch or retire nodes, with no disruption to agents running inside them. Memory and filesystem state are preserved exactly as they were. Your agents never lose work to infrastructure maintenance.
| Feature | Tensorlake | Vercel | E2B | Modal | Daytona |
| Filesystem Speed | 2.45s (fastest) | 1.2x slower | 1.6x slower | 1.9x slower | 2.2x slower |
| Auto Suspend / Resume | Yes | No | Yes | No | No |
| Clone Sandboxes | Yes | No | No | No | No |
| Point-in-Time Snapshots | Yes | Filesystem only | No | Alpha (expires in 7 days) | Filesystem only |
| Dynamic Resources | Yes | No | At creation only | Yes | At creation only |
| Live Migration | Automatic | No | No | No | No |
| Adaptive Timeouts | Yes | No | No | No | No |
Benchmarks SQLite performance across five sandbox providers. All sandboxes configured with 2 vCPUs and 4GB RAM. Each benchmark run 3 times, reporting mean +/- standard deviation. Source: github.com/tensorlakeai/sandbox-sqlite-bench
Try Sandboxes
We're offering free credits to developers who try Tensorlake Sandboxes and share their feedback. Whether you're building coding agents, running RL environments, or scaling parallel developer workflows, we want to hear what you build and what we can improve.
Check out our docs page to get started
Tensorlake · AI Infrastructure for Agents