Jarvislabs vs Cerebrium
Jarvislabs rents you a GPU or CPU machine in India that you log into and keep, billed by the minute. Cerebrium runs your model or app as containers behind an endpoint that scale up with requests and back down to zero.
The companies and products
Jarvislabs
Jarvislabs is an AI cloud from India that rents Nvidia GPUs by the minute for training and serving models.
You can rent a GPU VM with root and your own kernel, a Template (a GPU container with PyTorch, ComfyUI or similar ready, opened in JupyterLab, VS Code or SSH), a plain CPU VM, or a multi-node GPU cluster. It also serves open models through Managed Endpoints, Serverless workers and a token-priced Model API. It is built for people who train, fine-tune and serve AI models, not as a sandbox for agents, though its jl CLI is written so a coding agent on your laptop can drive the GPUs.
Cerebrium
Cerebrium is a serverless GPU cloud for real-time AI: voice agents, video models, LLMs and other ML apps.
You describe an app in a cerebrium.toml file, with your Python code or your own Dockerfile, and Cerebrium builds it and serves it as HTTP or WebSocket endpoints. It starts containers when requests arrive, scales them across GPUs and regions, and scales them back to zero when traffic stops. It is built for teams that serve models in production, not for agents that need a machine of their own, so this page compares the places where the two overlap.
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. “20th cheapest of 377” means 19 of the other 376 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 workload | Jarvislabs: price rank | Cerebrium: price rank | boat: price rank |
|---|---|---|---|
| Software factory 100 at once · 4 vCPU / 8 GB · 2,200 sessions of 8 h a month A software factory needs root, Docker and a whole disk that lasts; Jarvislabs has those but no snapshots or forks, and Cerebrium keeps only one folder. | 154th of 367, with limits $1,406 a month | 182nd of 367, with limits $2,008 a month | 3rd cheapest of 367 $634 a month |
| Always-on AI employees 50 machines 24/7 · 2 vCPU / 4 GB | 185th of 366, with limits $1,670 a month | 221st of 366, with limits $2,534 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 For short code bursts both GPU clouds beat boat on price, with Cerebrium at $131 a month and Jarvislabs at $169, since boat's start limits push it to a $2,000 plan. | 103rd of 345, with limits $169 a month | 225th of 345, with limits $131 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 Neither is built to give each of your users a machine: Jarvislabs does not publish how many instances can run at once, and Cerebrium gives users a stateless endpoint, while boat ranks 1st here. | 215th of 361, with limits $539 a month | 230th of 361, with limits $821 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 | 43rd of 360, with limits $2,568 a month | 72nd of 360, with limits $4,068 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 Cerebrium fits agent evals fully and ranks 32nd, ahead of Jarvislabs at 113th, because its containers start per request and scale back to zero; boat ranks 10th. | 113th of 364, with limits $411 a month | 32nd cheapest of 364 $639 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 A Jarvislabs CPU VM makes a plain CI runner with root, Cerebrium does not document Docker inside its containers, and boat ranks 4th with Docker and /dev/kvm on every machine. | 20th cheapest of 377 $253 a month | 81st cheapest of 377 $766 a month | 4th cheapest of 377 $86 a month |
| 24/7 dev boxes 1 machine 24/7 · 4 vCPU / 8 GB A dev box needs SSH and a disk that keeps your installs, which a Jarvislabs VM gives you and Cerebrium does not, since it has no SSH and resets everything outside /persistent-storage. | 52nd cheapest of 368 $68 a month | 259th of 368, with limits $102 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 Neither has a desktop or computer-use API, so boat's 60fps desktop with Chromium puts it at 6th against 154th for Jarvislabs and 179th for Cerebrium. | 154th of 369, with limits $377 a month | 179th of 369, with limits $575 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 | 204th of 367, with limits $205 a month | 221st of 367, with limits $287 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 | 244th of 346, with limits $247 a month | 223rd of 346, with limits $195 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 | 158th of 338, with limits $4,942 a month | 135th of 338, with limits $3,991 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 | 156th of 360, with limits $127 a month | 197th of 360, with limits $191 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 Both fit GPU eval jobs: Jarvislabs ranks 9th of 98 at $876 a month and Cerebrium 28th at $1,975, while boat has no GPUs. | 9th cheapest of 98 $876 a month | 28th cheapest of 98 $1,975 a month | Can't run it |
| macOS agents 5 at once · 4 vCPU / 8 GB · 1,000 sessions of 20 min a month | Can't run it | Can't run it | Can't run it |
Key features
| Feature | Jarvislabs | Cerebrium | boat |
|---|---|---|---|
| Kind of product | GPU cloud: GPU VMs, GPU containers, CPU VMs, clusters and model serving | Serverless GPU cloud: your app runs as autoscaling containers behind endpoints | Sandboxes for AI agents: full VMs with agents, a desktop and hosting ready |
| Isolation | GPU and CPU VMs are KVM virtual machines; Templates are containers | Containers built from your code or Dockerfile; the isolation layer is not named | Every sandbox is a full VM with its own kernel on dedicated AMD Ryzen 9 9950X hosts |
| Shell access | SSH, JupyterLab and VS Code in the browser, with root on VMs | No SSH; you reach the app through its HTTP or WebSocket endpoints | SSH, root and systemd, like a normal Ubuntu server |
| Docker and nested virtualization | Root on VMs, so you can run your own Docker daemon; nested virtualization is not documented | The app is the container; Docker inside and /dev/kvm are not documented | Docker, root, systemd and /dev/kvm on every machine |
| GPUs | Nvidia L4 up to H200, 1 to 8 per instance, plus B200 as reserved clusters | T4 up to B200 and RTX PRO 6000, up to 8 per container, plus Inferentia2 and Trainium | None, CPU only |
| Files after a stop | A paused VM keeps its whole disk; GPU containers keep only /home | Only the shared /persistent-storage volume survives; packages and files elsewhere reset | The whole disk is saved every minute and on stop |
| Cost while stopped | Compute stops billing; the disk keeps billing at $0.10/GB-month, with at least 100 GB on a VM | A container that has scaled to zero bills no compute; storage past the first 100 GB is $0.05/GB-month | A stopped sandbox costs nothing and keeps its disk |
| Snapshots and fork | No snapshot, clone or fork command | No fork; an early-beta memory checkpoint (no files) speeds up new containers of the same build | Snapshots every minute and on stop; fork a running sandbox |
| Run time | No documented cap; instances run until you pause them or the balance runs out | No container cap, but a request times out after 15 minutes by default, 12 hours at most for async runs | No session cap on paid plans; you set the time to live |
| Scale to zero and wake | Serverless model workers stop after an idle timeout and start on the next request | Apps scale to zero and start again on the next request, up to your replica limit | No wake on request; you start a stopped sandbox through the API |
| Desktop and computer use | No desktop | No desktop or browser product | 60fps desktop and Chromium, computer use and browser control, embeddable stream |
| Coding agents | A CLI and skill file so an agent on your own machine can create GPUs and run jobs | An Agent Skill and a docs MCP server help your own agent deploy to Cerebrium | Claude Code, Codex, OpenCode and more preinstalled, driven from outside with a prompt, steer and events API |
| Inbound access | VMs get a public IP with every port open by default; security groups and VPCs to lock it down | One endpoint per app on one port; custom domains on Standard | HTTPS URLs for up to 50 ports, token-protected; raw TCP; dedicated IPv4 or IPv6 |
| Keeping API keys out of the machine | Keys are passed in as environment variables or uploaded files | Secrets are exposed to the app as environment variables | AI credentials proxy for model providers and any HTTPS API you register |
| Regions | India only for new instances (IN1, IN2) | US East, US Central, Stockholm and Finland; 8 more on request | EU only: Germany, Finland, France |
Every feature Battleships tracks (43)
| Feature | Jarvislabs | Cerebrium | boat |
|---|---|---|---|
| Full VM (own kernel) | Yes | No | Yes |
| Docker inside | Yes | No | Yes |
| Nested virtualization | Not published | No | Yes |
| Root | Yes | Not published | Yes |
| Systemd | Not published | Not published | Yes |
| Desktop GUI | No | No | Yes |
| Browser | No | No | Yes |
| Computer-use API | No | No | Yes |
| SSH | Yes | No | Yes |
| Persistent disk | Yes | Yes | Yes |
| Pause/resume | Yes | No | Yes |
| Automatic snapshots | No | No | Yes |
| Fork/clone | No | No | Yes |
| Live fork (no pause) | No | No | Yes |
| Memory fork | No | No | No |
| Custom image (Docker or snapshot) | Yes | Yes | Yes |
| ≥24 h sessions | Yes | Yes | Yes |
| Idle auto-stop | Yes | Yes | No |
| Wake on request | Yes | Yes | No |
| HTTPS preview URLs | Yes | Yes | Yes |
| Raw TCP inbound | Yes | Not published | Yes |
| Public IPv4 | Yes | No | No |
| Egress allowlist | Yes | No | No |
| Secret proxy | No | No | Yes |
| Secret proxy for any API | No | No | Yes |
| Preinstalled agents | No | No | Yes |
| Agent harness API | No | No | Yes |
| MCP server | No | No | No |
| GPU | Yes | Yes | No |
| Windows | No | No | No |
| Arm64 | No | No | No |
| Self-hosting | No | No | No |
| BYOC | No | No | No |
| Open source | No | No | No |
| Scoped API keys | Not published | Not published | Yes |
| Spend limits | Yes | Not published | Yes |
| Usage per sandbox (API) | Yes | Yes | Yes |
| Audit logs | Not published | Yes | No |
| SSO | No | No | No |
| SOC 2 | No | Yes | No |
| HIPAA | No | Yes | No |
| EU data residency | No | Yes | Yes |
| Zero data retention | Not published | Not published | Yes |
Performance
There is no comparable measurement: neither Jarvislabs nor Cerebrium was part of the public StarSling CPU benchmark run, so we cannot say which is faster at CPU work. boat did 26.69 Node.js build-and-test runs per second at 4 vCPU / 8 GB in that run, on dedicated AMD Ryzen 9 9950X hosts. Both GPU clouds publish speed claims about GPUs and cold starts, which this test does not cover.
Node.js build-and-test loop at 4 vCPU / 8 GB, higher is better. Measured with the open hpc-sandbox-benchmarks suite. Jarvislabs and Cerebrium 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.
| Scenario | Jarvislabs, a month | Cerebrium, a month | boat, 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 | $21 · On-demand | $53 · Hobby · with limits | $20 · $20/mo |
| One agent that never stops 4 vCPU / 8 GB, 50 GB disk, running 24/7 all month | $71 · On-demand | $210 · 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 | $892 · On-demand | $2,557 · 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 | $231 · On-demand · with limits | $715 · Hobby | $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 | $514 · On-demand · with limits | $1,681 · Standard | $2,000 · $2000/mo · with limits |
Jarvislabs: Jarvislabs bills per minute from a prepaid wallet with no plan fee. CPU VMs cost $0.012 per vCPU-hour plus $0.0032 per GB of RAM, and the disk is extra at $0.10/GB-month, billed while running and while paused.
Cerebrium: Cerebrium bills per second for each vCPU, GB of memory and GPU while a container runs; the default tier can be interrupted and the protected tier costs 2x. Hobby has no fee, and Standard is $100 a month on top of compute, needed for A100, H100, H200 and B200.
Limits in those scenarios
Cerebrium does not fit the coding agent, always-on and 50-agent scenarios: only /persistent-storage survives a stop, and the fleet also needs Docker inside, which is not documented. Jarvislabs fits those, but does not publish how many machines can run at once, so 300 sandboxes for your users or 1,000 short jobs at once are not confirmed until you ask. Cerebrium publishes 500 containers at once on Hobby and 1,000 on Standard, which covers both. boat's start limits queue the 1,000-job burst, even on its $2,000 plan.
| Scenario | Jarvislabs | Cerebrium | boat |
|---|---|---|---|
| One coding agent, workdays | None that bite |
| None that bite |
| One agent that never stops | None that bite |
| None that bite |
| 50 agents in parallel |
|
| None that bite |
| Sandboxes for your users |
|
| None that bite |
| 1,000 short jobs at once |
|
|
|
Which one should you use?
Use Jarvislabs when
you want a GPU or CPU machine you log into and keep, billed by the minute, or machines in India.
- A GPU machine you log into. For hands-on training work, a Jarvislabs GPU VM gives you root, SSH and a disk that is still there after a pause.
- Per-minute billing with no plan fee. For occasional use, Jarvislabs bills per minute from a prepaid wallet, with no monthly fee before you can rent bigger GPUs.
- Network rules and India regions. For teams in India or who want firewall rules, Jarvislabs has security groups, VPCs and reserved IPs on its VMs.
Use Cerebrium when
you serve a model, voice or video app as an endpoint that scales with traffic and down to zero.
- Endpoints that scale to zero. For apps that wait for traffic, Cerebrium starts containers on the next request and grows to many replicas under load.
- More GPU types. For inference at scale, Cerebrium adds T4, A10 and L40S GPUs and on-demand B200, plus AWS Inferentia2 and Trainium.
- US, EU and more regions. For users spread around the world, Cerebrium runs in the US and the EU, with Asia and South America on request.
Where boat fits
Jarvislabs and Cerebrium are GPU clouds, and boat has no GPUs, so model training and serving belong on one of them. If what you are really running is agents that work inside a machine, boat gives each one a full VM with its own kernel, coding agents and a desktop ready. You can keep the GPUs on a GPU cloud and run the agents on boat.
A whole machine that keeps everything
On Cerebrium an agent loses every package it installed outside /persistent-storage when the container scales down. Jarvislabs keeps the disk, but bills at least 100 GB while paused. boat saves the whole disk every minute and a stopped sandbox costs nothing.
Fork a running sandbox
Neither Jarvislabs nor Cerebrium can copy a running machine, so branching an agent's work means setting up a new one by hand. boat forks a running sandbox with its disk, so one set-up machine becomes many.
Agents, desktop and keys built in
Neither ships a coding agent to run inside, a desktop for computer use, or a way to keep keys off the machine, so secrets sit there as environment variables. boat has preinstalled agents, a 60fps desktop and a credentials proxy for any HTTPS API.
Use boat when you run agents: full VMs with Docker and /dev/kvm, coding agents and a desktop ready, that snapshot every minute, fork while running and cost nothing while stopped. Compare it one to one: boat vs Jarvislabs and boat vs Cerebrium.
Questions people ask
Is Jarvislabs cheaper than Cerebrium?
In most of our scenarios, yes. One agent running all month comes to $71 on Jarvislabs and $210 on Cerebrium, and 1,000 short jobs at once to $514 versus $1,681, though Jarvislabs does not confirm that many machines at once. For the same scenarios boat comes to $26 and $2,000.
Which is faster, Jarvislabs or Cerebrium?
We have no comparable CPU measurement for either. Neither ran the public StarSling benchmark, where boat did 26.69 runs per second at 4 vCPU / 8 GB.
Can Jarvislabs or Cerebrium run Docker?
A Jarvislabs VM gives you root, so you can run your own Docker daemon. Cerebrium builds your app from a Dockerfile, but running Docker inside the app is not documented. Every boat sandbox runs Docker, systemd and /dev/kvm.
Can I SSH into Cerebrium like Jarvislabs?
No. Cerebrium has no SSH; you reach your app through its HTTP or WebSocket endpoints. Jarvislabs gives you SSH, JupyterLab and VS Code in the browser, and boat gives you SSH with root.
What happens to my files when I stop?
A paused Jarvislabs VM keeps its whole disk and keeps paying for it, with at least 100 GB. On Cerebrium only /persistent-storage survives; the rest resets. boat saves the whole disk every minute and a stopped sandbox costs nothing.
Does boat have GPUs?
No. boat runs CPU VMs on dedicated AMD Ryzen 9 9950X hosts. If your work trains or serves models, rent the GPUs on Jarvislabs or Cerebrium.
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