Micro-VM Infrastructure for AI

Micro-VMs for AI workloads

Zero-downtime snapshots. Native branching. 50-90% compute savings. Built for coding agents, browser automation, and RL training.

~170ms

Boot time

0ms

Snapshot pause

50-90%

Cost savings

Launch a VM Read Docs

Developer Experience

A few lines of Python

import asyncio
from fastvm import FastVM

async def main():
    async with FastVM() as client:
        # Launch a micro-VM (~170ms boot)
        vm = await client.launch(machine="c1m2")

        result = await client.run(vm, "python3 --version")
        print(result.stdout)  # => Python 3.13.5

asyncio.run(main())

PythonReady

Micro-VMs for AI workloads

Zero-downtime snapshots. Native branching. 50-90% compute savings. Built for coding agents, browser automation, and RL training.

~170ms

Boot time

0ms

Snapshot pause

50-90%

Cost savings

Launch a VM Read Docs

import asyncio
from fastvm import FastVM

async def main():
    async with FastVM() as client:
        # Launch a micro-VM (~170ms boot)
        vm = await client.launch(machine="c1m2")

        result = await client.run(vm, "python3 --version")
        print(result.stdout)  # => Python 3.13.5

asyncio.run(main())

PythonReady

Performance

How we compare

Purpose-built infrastructure for AI workloads. Not retrofitted containers or legacy VM architectures.

Metric	Fast VM	E2B	Modal	Daytona
Boot time	~170ms	300ms	1s	~300ms
Memory snapshots	Zero downtime	Interrupts existing processes	VM shutdown requiredFeature in Alpha	Not possibleFilesystem only
Fork into N VMs	Up to 1000 VMs in 170ms	Not available	Not available	Not available
Storage cost scaling	Logarithmic	Linear	Linear	Linear
Compute cost	50-90% savings	Standard	Standard	Standard
Isolation	StrongDedicated kernel per VM	StrongDedicated kernel per VM	ModerateShared kernel (gVisor)	WeakDocker (Kata optional)

Fast VM

Others

Boot time

~170ms

300ms

Memory snapshots

Zero downtime

Interrupts existing processes

Fork into N VMs

Up to 1000 VMs in 170ms

Not available

Storage cost scaling

Logarithmic

Linear

Compute cost

50-90% savings

Standard

Isolation

StrongDedicated kernel per VM

Use Cases

Built for AI workloads. Ready for anything.

Snapshot every step. Roll back instantly on failure instead of retrying from scratch.

Need code to pass a test suite? Spin up 10 parallel agents. Seven fail, three succeed. Let an agent pick the best result and merge it.

AI Coding Agents

Snapshot every step. Roll back instantly on failure instead of retrying from scratch.

Need code to pass a test suite? Spin up 10 parallel agents. Seven fail, three succeed. Let an agent pick the best result and merge it.

Ready to build?

Launch a VM