Tensorlake vs Railway

Tensorlake is built for agents: microVMs that can freeze their memory, wake up warm and copy into many clones. Railway is an app platform for services and databases that added Linux VM sandboxes, which are destroyed when they go idle.

The companies and products

Tensorlake

Tensorlake is a San Francisco company that sells infrastructure for AI agents, with sandboxes as its main product.

Tensorlake Sandboxes are microVMs, backed by Firecracker and Cloud Hypervisor, that you create through an API and that boot in a few hundred milliseconds. Named sandboxes suspend when idle and keep their memory and running processes, and you can copy a running sandbox into several warm clones. Around them Tensorlake sells versioned file systems, hosted Git, an orchestration layer and a bring-your-own-cloud option, aimed at teams running coding agents, evals and RL rollouts.

Headquarters
San Francisco

Railway

Railway is a cloud platform for deploying web apps, servers and databases, which now also sells sandboxes and cloud agents.

Railway's main product is app hosting: you deploy services and databases as containers on its own hardware. In 2026 it added Sandboxes, isolated Linux VMs you create from the CLI or a TypeScript SDK, run commands in and destroy, and Cloud Agents, a personal VM for running a coding agent, in early access. It suits teams already hosting on Railway who want throwaway machines next to their apps.

Which use cases each one fits

For each use case, Battleships prices every sandbox provider on the same workload and sorts them from the cheapest monthly bill up. “5th cheapest of 367” means 4 of the other 366 providers run that workload, with every feature it needs, for less. “With limits” means the provider runs it but misses something, so it is listed after every full match. Open a use case for its whole ranking and what each provider misses.

Use case and its workloadTensorlake: price rankRailway: price rankbochka: price rank
Software factory
100 at once · 4 vCPU / 8 GB · 2,200 sessions of 8 h a month
Tensorlake fits a software factory fully and Railway only as a compromise, since its sandboxes are destroyed when idle; bochka adds Docker, /dev/kvm and coding agents you drive by API.
5th cheapest of 367
$1,010 a month
51st of 367, with limits
$342 a month
3rd cheapest of 367
$634 a month
Always-on AI employees
50 machines 24/7 · 2 vCPU / 4 GB
All three fit an always-on agent; Tensorlake suspends it with memory, Railway needs the idle timeout set to 0, and bochka keeps the machine on with no session cap.
9th cheapest of 366
$1,381 a month
16th cheapest of 366
$3,977 a month
5th cheapest of 366
$657 a month
Code interpreter bursts
100 at once · 1 vCPU / 2 GB · 200,000 sessions of 1 min a month
Tensorlake and Railway both fit short code runs well, and bochka's start-rate limits make big bursts of new machines a compromise.
24th cheapest of 345
$250 a month
36th cheapest of 345
$413 a month
186th of 345, with limits
$2,000 a month
Sandboxes for your users
300 at once · 2 vCPU / 4 GB · 30,000 sessions of 23 min a month
Railway caps sandboxes at 100 per environment on Pro, while Tensorlake Pro allows 1,000 at once; bochka also gives each user sandbox HTTPS URLs and raw TCP.
5th cheapest of 361
$471 a month
42nd of 361, with limits
$290 a month
Cheapest of 361
$209 a month
RL rollouts
1,000 at once · 2 vCPU / 4 GB · 1,000,000 sessions of 3 min a month
Tensorlake ranks 1st for RL rollouts, with warm clones from one memory snapshot; Railway's per-environment cap makes it a compromise.
Cheapest of 360
$5,637 a month
78th of 360, with limits
$4,450 a month
34th of 360, with limits
$2,000 a month
Agent evals
250 at once · 4 vCPU / 8 GB · 15,000 sessions of 20 min a month
24th cheapest of 364
$506 a month
108th of 364, with limits
$364 a month
10th cheapest of 364
$200 a month
CI runners
40 at once · 8 vCPU / 16 GB · 6,000 sessions of 12 min a month
CI jobs that build containers need Docker, which Tensorlake documents on its systemd image and Railway's sandbox docs do not mention.
54th cheapest of 377
$424 a month
113th cheapest of 377
$1,210 a month
4th cheapest of 377
$86 a month
24/7 dev boxes
1 machine 24/7 · 4 vCPU / 8 GB
Railway fits a box that stays on all day better than Tensorlake, whose model is built around suspending idle sandboxes; bochka keeps its disk and stops for free.
185th of 368, with limits
$250 a month
66th cheapest of 368
$89 a month
18th cheapest of 368
$26 a month
Computer-use agents
50 at once · 4 vCPU / 8 GB · 20,000 sessions of 15 min a month
Tensorlake has an XFCE desktop over VNC and Railway sandboxes are headless; bochka streams a 60fps desktop with computer use.
9th cheapest of 369
$294 a month
77th of 369, with limits
$103 a month
6th cheapest of 369
$200 a month
Browser-use agents
50 at once · 2 vCPU / 4 GB · 30,000 sessions of 10 min a month
13th cheapest of 367
$250 a month
53rd of 367, with limits
$93 a month
7th cheapest of 367
$200 a month
Scraping & bots (startup scale)
50 at once · 1 vCPU / 2 GB · 100,000 sessions of 3 min a month
22nd cheapest of 346
$250 a month
60th cheapest of 346
$570 a month
6th cheapest of 346
$90 a month
Mass scraping & bots (undetectable)
1,000 at once · 1 vCPU / 2 GB · 3,000,000 sessions of 2 min a month
121st of 338, with limits
$3,484 a month
109th of 338, with limits
$2,988 a month
71st of 338, with limits
$1,800 a month
Parallel red teaming
200 at once · 2 vCPU / 4 GB · 5,000 sessions of 30 min a month
4th cheapest of 360
$250 a month
43rd of 360, with limits
$574 a month
2nd cheapest of 360
$200 a month
GPU eval jobs
10 at once · 8 vCPU / 32 GB · 500 sessions of 30 min a month
Can't run itCan't run itCan't run it
macOS agents
5 at once · 4 vCPU / 8 GB · 1,000 sessions of 20 min a month
Can't run itCan't run itCan't run it

Key features

FeatureTensorlakeRailwaybochka
IsolationFirecracker and Cloud Hypervisor microVMs with their own kernel; GPU sandboxes use gVisorSandboxes are isolated Linux VMs; app services are containersFull VM with its own kernel on dedicated AMD Ryzen 9 9950X hosts
When the sandbox goes idleIdle timeout (600 s by default), then named sandboxes suspend with memory and ephemeral ones endDestroyed after the idle timeout (30 minutes by default); files survive only in checkpoints you takeStops; the disk is kept with snapshots every minute and on stop, and a stopped sandbox costs nothing
Memory snapshotsYes: suspend and memory snapshots keep running processes and restore warmNo: checkpoints save the disk onlyNo: the disk is kept, and resume reboots the machine
Fork a running sandboxCopy a running or suspended sandbox into N warm clones with memoryFork a running sandbox's filesystemFork a running sandbox (disk)
Docker insideYes, on the tensorlake/ubuntu-systemd imageRoot shell on Ubuntu; the sandbox docs do not mention DockerYes, with root and systemd on every machine
Nested virtualizationNo: sandboxes set SANDBOX_KVM_AVAILABLE=0Not mentioned in the sandbox docsYes, /dev/kvm inside, so Android emulators and VMs run
Desktop and computer useXFCE desktop with Firefox over VNC, with screenshot, mouse and keyboard callsHeadless: terminal, exec and SSH only60fps desktop and Chromium, computer use and browser control, embeddable stream
Coding agentsYou bring and run your own agent; managed images are plain OS basesClaude Code, Codex, OpenCode and Pi preinstalled; you run them headless through execClaude Code, Codex, OpenCode and more preinstalled, with a prompt, steer and events API
API keysStored secrets are injected into the sandboxSecrets go into the sandbox as environment variables, or are saved in a checkpointCredentials proxy for AI providers and any HTTPS API: real keys never enter the sandbox
Reaching the sandboxHTTP, WebSocket and gRPC through an authenticated proxy on exposed portsUp to 10 public HTTPS domains, set only at creation; SSH and port forwardingHTTPS URLs for up to 50 ports, token-protected, plus raw TCP and a dedicated IP
Outbound rulesallow_out and deny_out lists by domain, IP or CIDR, or no internet at allNo sandbox outbound allowlist documentedNo provider-side allowlist; you set your own firewall as root
Apps and databases next to the sandboxSandboxes, versioned file systems and hosted Git; no app hosting describedDeploy Postgres, Redis and services in the same project; a sandbox can join their private networkNo hosted databases or app services; host your own inside a sandbox
Sandboxes at once1,000 on Pro, up to 10 on prepaid credits50 per environment on Hobby, 100 on Pro; Enterprise can ask for more100 to 2,000 by plan, with limits on starts per minute and per day
GPUs and regionsGPU sandboxes by request; US and EU, or your own cloud through BYOCNo GPU sandboxes; US West, US East, Amsterdam and SingaporeNo GPUs; EU only: Germany, Finland, France
Every feature Battleships tracks (43)
FeatureTensorlakeRailwaybochka
Full VM (own kernel)YesYesYes
Docker insideYesNot publishedYes
Nested virtualizationNoNoYes
RootYesYesYes
SystemdYesNot publishedYes
Desktop GUIYesNoYes
BrowserYesYesYes
Computer-use APIYesNoYes
SSHYesYesYes
Persistent diskYesYesYes
Pause/resumeYesYesYes
Automatic snapshotsYesNoYes
Fork/cloneYesYesYes
Live fork (no pause)YesYesYes
Memory forkYesNoNo
Custom image (Docker or snapshot)YesYesYes
≥24 h sessionsYesYesYes
Idle auto-stopYesYesNo
Wake on requestYesNoNo
HTTPS preview URLsYesYesYes
Raw TCP inboundNoNoYes
Public IPv4NoNoNo
Egress allowlistYesNoNo
Secret proxyNoNoYes
Secret proxy for any APINoNoYes
Preinstalled agentsNoYesYes
Agent harness APINoYesYes
MCP serverNoYesNo
GPUYesNoNo
WindowsNoNoNo
Arm64NoNoNo
Self-hostingNoNoNo
BYOCYesYesNo
Open sourceNoNoNo
Scoped API keysNot publishedNot publishedYes
Spend limitsNot publishedYesYes
Usage per sandbox (API)NoNoYes
Audit logsNot publishedYesNo
SSOYesYesNo
SOC 2YesYesNo
HIPAAYesYesNo
EU data residencyYesYesYes
Zero data retentionYesNot publishedYes

Performance

TensorlakeNot measured
RailwayNot measured
bochka26.69 runs/s

There is no comparable measurement between Tensorlake and Railway: neither has a result in StarSling's public hpc-sandbox-benchmarks. bochka did 26.69 Node.js build-and-test runs per second at 4 vCPU / 8 GB there, the fastest result measured, but we cannot say how much faster it is than either. Tensorlake's docs say its default image starts in a few hundred milliseconds.

Node.js build-and-test loop at 4 vCPU / 8 GB, higher is better. Measured with the open hpc-sandbox-benchmarks suite. Tensorlake and Railway have no published run in this suite yet, so there is no like-for-like number to compare.

Pricing in five scenarios

Each bill is priced from the providers' public price lists by the open Battleships engine, with the cheapest plan that runs the scenario.

ScenarioTensorlake, a monthRailway, a monthbochka, a month
One coding agent, workdays
4 vCPU / 8 GB, 50 GB disk, 8 hours a day, 22 days a month, files kept between days
$250 · Pro$16 · Hobby · with limits$20 · $20/mo
One agent that never stops
4 vCPU / 8 GB, 50 GB disk, running 24/7 all month
$250 · Pro$70 · Hobby · with limits$26 · $20/mo
50 agents in parallel
50 machines of 4 vCPU / 8 GB at once, 8-hour sessions, 1,100 sessions a month, Docker inside
$1,030 · Pro$739 · Hobby · with limits$317 · $20/mo × 3 seats
Sandboxes for your users
2 vCPU / 4 GB, 30,000 sessions of 10 minutes a month, up to 300 at once
$293 · Pro$223 · Pro · with limits$200 · $100/mo × 2 seats
1,000 short jobs at once
2 vCPU / 4 GB, 1,000 at once, 3 minutes each, 200,000 jobs a month
$1,127 · Pro$781 · Pro · with limits$2,000 · $2000/mo · with limits

Tensorlake: Pro is $250 per billing cycle, which includes $250 of usage, then $0.01 per CU. CPU bills only while active, RAM and disk bill on what you allocate while the sandbox runs, and a suspended sandbox pays snapshot storage; small users can buy prepaid packs from $5 instead.

Railway: Railway bills sandboxes per second at $50 per vCPU-month on CPU actually used and $50 per GB-month on memory in use, which keeps billing while a sandbox waits. The Hobby ($5) and Pro ($20) fees count toward usage, and sandbox disk has no published price, so our numbers leave it out.

Railway: You pick a monthly plan from $20, and all of it becomes usage credit spent per second on running sandboxes. A stopped sandbox costs nothing and keeps its disk.

Limits in those scenarios

Railway is not a clean fit in any of the five scenarios, because it is an app platform first and publishes no sandbox disk price, so its bills count CPU and memory only. Its Pro cap of 100 sandboxes per environment means 300 sandboxes for your users or 1,000 jobs at once need several environments or an Enterprise limit. Tensorlake Pro fits all five, with 1,000 at once, but every bill starts at the $250 Pro fee. On bochka, the 1,000-job burst is queued above 90 starts a minute and needs more starts per day than the $2,000 plan allows.

ScenarioTensorlakeRailwaybochka
One coding agent, workdaysNone that bite
  • different kind of product: app platform
  • disk beyond 0 GiB: price unknown
None that bite
One agent that never stopsNone that bite
  • different kind of product: app platform
  • disk beyond 0 GiB: price unknown
None that bite
50 agents in parallelNone that bite
  • not confirmed: Docker inside
  • different kind of product: app platform
  • disk beyond 0 GiB: price unknown
None that bite
Sandboxes for your usersNone that bite
  • Pro: max 100 concurrent
  • different kind of product: app platform
  • disk beyond 0 GiB: price unknown
None that bite
1,000 short jobs at onceNone that bite
  • Pro: max 100 concurrent
  • different kind of product: app platform
  • disk beyond 0 GiB: price unknown
  • max 2,400 starts/day (needs ~6,667)
  • max 600 starts/hour (needs ~1,000)
  • bursts above 90 starts/min are queued (a burst of 333 takes ~4 min to start)

Which one should you use?

Use Tensorlake when

you fan out hundreds of short rollouts or evals from one warm state, need memory snapshots, outbound rules, GPUs or sandboxes in your own cloud account.

  • Memory snapshots and warm clones. Useful when an agent must pick up mid-process: Tensorlake saves a sandbox's memory and copies it into warm clones.
  • Big fan-outs from one state. Useful for RL rollouts and evals: Tensorlake Pro runs 1,000 sandboxes at once, where Railway caps Pro at 100 per environment.
  • Outbound rules, GPUs and your own cloud. Tensorlake can allow or deny outbound traffic per sandbox, offers GPUs by request and can run in your own cloud account.

Use Railway when

your app and databases already live on Railway and you want short-lived sandboxes on the same private network, or you need US or Asia regions.

  • Your apps and databases in one place. Useful if your app already runs on Railway: sandboxes can join the same private network as your Postgres and services.
  • Regions in the US and Asia. Useful if your users or data are in the US or Asia: Railway runs in California, Virginia, Amsterdam and Singapore.
  • Coding agents in the image. Useful if you just want to run an agent headless: Railway's default image ships Claude Code, Codex, OpenCode and Pi.

Where bochka fits

Tensorlake is strongest at short, wide fan-outs from a warm state, and Railway at sandboxes that sit next to apps you already host. If your agents instead work for hours on one machine, with Docker, emulators, a desktop and servers others must reach, bochka gives each one a full VM that keeps its disk. Its coding agents are driven from outside while their keys stay outside the machine.

A disk that stays, with no session cap

A Tensorlake ephemeral sandbox ends after 10 idle minutes and a Railway sandbox is destroyed after 30, unless you keep it awake and pay for its memory. A bochka sandbox stops, saves its disk every minute and costs nothing while stopped.

Emulators, Docker and a real desktop

Tensorlake sandboxes have no /dev/kvm, so Android emulators and VMs do not start, and Railway's docs mention neither Docker nor /dev/kvm and give no screen at all. bochka has Docker, systemd, /dev/kvm and a 60fps desktop on every machine.

Agents driven from outside, keys kept out

On Tensorlake you install the agent yourself, and on Railway you shell it through exec and parse its output. Both put API keys inside the sandbox, where code the agent runs can read them. bochka's proxy keeps them outside.

Use bochka when your agents work for hours or days: a full VM that keeps its disk, with Docker, /dev/kvm, a desktop, and coding agents you drive from outside while their keys stay outside. Compare it one to one: bochka vs Tensorlake and bochka vs Railway.

Questions people ask

Is Tensorlake cheaper than Railway?

In our five scenarios Railway comes out lower: one agent running all month is $70 on Railway and $250 on Tensorlake Pro, and 50 agents in parallel are $739 against $1,030. But Railway's numbers leave out disk, which it does not price, and its 100-per-environment cap means it does not cleanly fit the bigger jobs. On bochka the same always-on agent is $26 a month.

Which is faster, Tensorlake or Railway?

We cannot say: neither has a result on the CPU benchmark we use. bochka scores 26.69 runs per second there, the fastest measured. Tensorlake says its sandboxes boot in a few hundred milliseconds.

Can Tensorlake or Railway run Docker?

Tensorlake runs Docker on its tensorlake/ubuntu-systemd image. Railway's sandbox docs give a root shell on Ubuntu but do not mention Docker. bochka has Docker, root and systemd on every machine.

What happens when a sandbox goes idle?

On Tensorlake, after 600 seconds by default a named sandbox suspends with its memory and an ephemeral one ends. Railway destroys the sandbox after 30 minutes by default, and only checkpoints you took survive. A bochka sandbox stops, keeps its disk and costs nothing while stopped.

Which has a desktop for computer-use agents?

Tensorlake has an XFCE desktop with Firefox over VNC, with screenshot, mouse and keyboard calls. Railway sandboxes are headless. bochka streams a 60fps desktop with Chromium, computer use and browser control.

Is bochka SOC 2 compliant?

SOC 2 is in progress. We're open about where we stand: live status at status.bochka.xyz and our data retention policy at docs.bochka.xyz/data-retention.

Try bochka

Install the CLI, then run bochka new.

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More comparisons

Bochka product preview · Pricing, benchmarks and commands are illustrative. Sandbox provisioning is not connected.