Runpod vs Hyperstack
Both are GPU clouds, but they rent different things. Runpod gives you containers (pods) billed by the second, plus serverless workers that start on a request; Hyperstack gives you full virtual machines with root and Docker, billed by the minute.
The companies and products
Runpod
Runpod is a GPU cloud for AI work: you rent GPU or CPU pods by the second, run serverless endpoints, or book multi-node GPU clusters.
A Runpod Pod is a container started from a Docker image, with a GPU or CPU-only, SSH, a web terminal and Jupyter. Serverless endpoints run your handler in workers that scale to zero and start on a request, and Instant Clusters join 2 to 8 nodes of 8 GPUs each. It is built for teams that train, fine-tune and serve models, not as a sandbox API for agents, so this page compares the parts that overlap: CPU pods as machines for agent work.
- Founded
- 2022
Hyperstack
Hyperstack is the GPU cloud of NexGen Cloud, a UK company founded in 2020: you rent GPU and CPU virtual machines, Kubernetes clusters and storage by the minute.
A Hyperstack VM is a full virtual machine with root and SSH, booted from an Ubuntu image (with or without Docker) and sized from a fixed list of flavors, from one RTX A4000 to 8-GPU B300 nodes, plus CPU-only flavors from 4 to 32 vCPUs. It also runs managed Kubernetes, volumes, object storage and an AI Studio inference API. It is built for teams that train, fine-tune and serve models, not as a sandbox API for agents, so this page compares the parts that overlap: VMs as machines for agent work.
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. “32nd cheapest of 377” means 31 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 | Runpod: price rank | Hyperstack: price rank | boat: price rank |
|---|---|---|---|
| Software factory 100 at once · 4 vCPU / 8 GB · 2,200 sessions of 8 h a month Hyperstack VMs can run Docker and keep their whole disk, while a Runpod pod cannot run Docker inside and keeps only /workspace; boat does both and snapshots the disk every minute. | 203rd of 367, with limits $2,362 a month | 343rd of 367, with limits $11,458 a month | 3rd cheapest of 367 $634 a month |
| Always-on AI employees 50 machines 24/7 · 2 vCPU / 4 GB | 211th of 366, with limits $2,290 a month | 337th of 366, with limits $12,775 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 | 227th of 345, with limits $135 a month | 172nd of 345, with limits $1,167 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 has a sandbox API for your users or publishes how many machines can run at once, so 300 sandboxes at once is not confirmed on either. | 83rd of 361, with limits $733 a month | 173rd of 361, with limits $4,207 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 Runpod ranks 53rd here and Hyperstack 173rd; boat ranks 34th, and none of the three is a full match. | 53rd of 360, with limits $3,068 a month | 173rd of 360, with limits $17,500 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 | 127th of 364, with limits $614 a month | 204th of 364, with limits $3,250 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 Both fit plain build and test jobs; jobs that start Docker containers work on Hyperstack and boat, not inside a Runpod pod. | 32nd cheapest of 377 $301 a month | 122nd cheapest of 377 $1,560 a month | 4th cheapest of 377 $86 a month |
| 24/7 dev boxes 1 machine 24/7 · 4 vCPU / 8 GB Hyperstack fits a dev box that stays on, since the whole disk is kept; on Runpod anything installed outside /workspace is gone after a stop. | 161st of 368, with limits $93 a month | 115th cheapest of 368 $475 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 Runpod gives a terminal, SSH and Jupyter, Hyperstack gives SSH and a text console; neither has a desktop, while boat streams a 60fps desktop with computer use. | 189th of 369, with limits $614 a month | 332nd of 369, with limits $3,250 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 On both you install and run your own headless browser; boat ships Chromium on a desktop in every sandbox. | 224th of 367, with limits $307 a month | 335th of 367, with limits $1,750 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 | 225th of 346, with limits $202 a month | 327th of 346, with limits $1,750 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 | 138th of 338, with limits $4,035 a month | 310th of 338, with limits $35,000 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 | 180th of 360, with limits $161 a month | 309th of 360, with limits $876 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 and boat has no GPUs; Hyperstack ranks 2nd here and Runpod 13th, and Runpod adds AMD cards and multi-node clusters. | 13th cheapest of 98 $1,001 a month | 2nd cheapest of 98 $625 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 | Runpod | Hyperstack | boat |
|---|---|---|---|
| Isolation | Containers that share the host kernel | Full VMs with root, on flavors mapped 1:1 to physical resources | Every sandbox is a full VM with its own kernel |
| Docker inside | Root in the container; no Docker or Docker Compose inside a pod | Ubuntu 22.04 and 24.04 images with or without Docker | Docker, Docker Compose, root, systemd and /dev/kvm on every machine |
| Stopping a machine | A stopped pod keeps billing its /workspace volume, at double the running rate | A SHUTOFF VM bills at the full rate; hibernation bills only disk and a kept IP, and a restore needs the flavor in stock | A stopped sandbox costs nothing and keeps its whole disk |
| Files after a stop | Only /workspace is kept; the rest of the container disk is cleared | The whole disk is kept | The whole disk is kept, with snapshots every minute and on stop |
| Snapshots | No snapshot for pods; templates save the image and settings only | On request only; the VM is shut off while it is taken, one at a time, up to 100 GB | Every minute and on stop, while the sandbox keeps running |
| Fork | No pod fork | No clone or fork; you snapshot, make a custom image and deploy a new VM | Fork a running sandbox into a new one with the same disk |
| Desktop and computer use | Web terminal, SSH, JupyterLab and remote VS Code or Cursor; no desktop | SSH and text console logs; no graphical desktop | 60fps desktop and Chromium, computer use and browser control, embeddable stream |
| Reaching the machine | Up to 10 HTTP ports on a public proxy URL with no built-in auth; TCP ports on a public IP | A public IPv4 you can keep static; open ports with firewall rules and run your own TLS | HTTPS URLs for up to 50 ports, token-protected; raw TCP; dedicated IPv6 or IPv4 |
| Network rules | Pick which ports to expose; no outbound allowlist | Per-VM firewall: inbound closed by default, outbound rules by IP, protocol and port | Open internet out; inbound through HTTPS URLs and TCP ports |
| Keeping keys out of the machine | Secrets are stored encrypted and passed into the pod as environment variables | No credentials proxy; you pass keys in with cloud-init, files or environment variables | AI credentials proxy for model providers and any HTTPS API you register; switch a credential to another account when credits run out |
| Coding agents | An MCP server and skills let your own agent manage Runpod; nothing runs an agent inside a pod | A hosted MCP server lets your own agent manage Hyperstack; nothing runs an agent inside a VM | Claude Code, Codex, OpenCode and more preinstalled, driven from outside with a prompt, steer and events API |
| GPUs | Dozens of Nvidia and AMD types, from RTX A4000 to B300 and MI300X, plus multi-node clusters | Nvidia from RTX A4000 to H100, H200, B200 and B300, single cards or 8-GPU nodes, on demand, spot or reserved | None |
| Scale to zero | Serverless workers scale to zero and start when a request arrives | No start on a request; VMs run until you stop, hibernate or delete them | Sandboxes stop and resume by API; no start on an incoming request |
| Regions | 24 documented data centers in the US, Canada, Europe and Australia; says 30+ regions | Norway, Canada and the US | EU only: Germany, Finland, France |
Every feature Battleships tracks (43)
| Feature | Runpod | Hyperstack | boat |
|---|---|---|---|
| Full VM (own kernel) | No | Yes | Yes |
| Docker inside | No | Yes | Yes |
| Nested virtualization | No | Not published | Yes |
| Root | Yes | Yes | Yes |
| Systemd | No | Not published | Yes |
| Desktop GUI | No | No | Yes |
| Browser | No | No | Yes |
| Computer-use API | No | No | Yes |
| SSH | Yes | Yes | Yes |
| Persistent disk | Yes | Yes | Yes |
| Pause/resume | Yes | Yes | 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 | No | No | No |
| Wake on request | Yes | No | No |
| HTTPS preview URLs | Yes | No | Yes |
| Raw TCP inbound | Yes | No | Yes |
| Public IPv4 | Yes | Yes | No |
| Egress allowlist | No | Yes | 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 | Yes | Yes | 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 | Yes | Not published | Yes |
| Spend limits | Yes | Not published | Yes |
| Usage per sandbox (API) | No | No | Yes |
| Audit logs | Yes | Not published | No |
| SSO | Yes | No | No |
| SOC 2 | Yes | Yes | No |
| HIPAA | Yes | No | No |
| EU data residency | Yes | Yes | Yes |
| Zero data retention | Not published | Not published | Yes |
Performance
There is no comparable measurement for Runpod or Hyperstack: neither is in the public sandbox benchmark runs we use. boat did 26.69 Node.js build-and-test runs per second at 4 vCPU / 8 GB in StarSling's run of 2026-09-29, on dedicated AMD Ryzen 9 9950X (Zen 5) hosts.
Node.js build-and-test loop at 4 vCPU / 8 GB, higher is better. Measured with the open hpc-sandbox-benchmarks suite. Runpod and Hyperstack 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 | Runpod, a month | Hyperstack, 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 | $26 · Pay-as-you-go (prepaid credits) · with limits | $114 · Prepaid on-demand | $20 · $20/mo |
| One agent that never stops 4 vCPU / 8 GB, 50 GB disk, running 24/7 all month | $93 · Pay-as-you-go (prepaid credits) · with limits | $475 · Prepaid on-demand | $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 | $1,156 · Pay-as-you-go (prepaid credits) · with limits | $5,720 · Prepaid on-demand | $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 | $307 · Pay-as-you-go (prepaid credits) · with limits | $1,750 · Prepaid on-demand · 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 | $614 · Pay-as-you-go (prepaid credits) · with limits | $3,500 · Prepaid on-demand · with limits | $2,000 · $2000/mo · with limits |
Runpod: Runpod bills a running pod per second from a prepaid balance, with disk on top, and a stopped pod keeps billing its /workspace volume at double the running rate. CPU pod rates come from Runpod's public CPU catalogue, since the pricing page lists GPUs only.
Hyperstack: Hyperstack bills a running VM per minute from a prepaid balance at a fixed hourly price per flavor, with no charge for bandwidth. CPU-only flavors start at 4 vCPU / 4 GB, so the scenarios use the closest flavor, which is larger than Runpod's, and the totals assume you hibernate it between runs.
Hyperstack: 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 whole disk.
Limits in those scenarios
Neither Runpod nor Hyperstack publishes how many machines can run at once, so 300 user sandboxes and 1,000 short jobs at once are not confirmed on either. Runpod limits spend instead, at $80 an hour by default, and Hyperstack's API allows 500 requests a minute per IP. Every Runpod scenario also hits the /workspace rule, and the 50-agent fleet does not fit there because pods cannot run Docker inside. On boat the 1,000-job burst gets queued and needs more starts per day than the $2,000 plan allows.
| Scenario | Runpod | Hyperstack | 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 Runpod when
you want serverless workers that start on a request, AMD GPUs or multi-node clusters, regions in Australia, or volumes shared by many machines.
- Serverless that starts on a request. For spiky work: Runpod Serverless workers scale to zero when idle and start when a request comes in, billed per second.
- More GPU types, up to clusters. For teams that want AMD cards or many nodes: Runpod rents dozens of Nvidia and AMD GPUs and joins them into multi-node clusters.
- Shared volumes and more regions. For data in Australia or many machines reading one dataset: Runpod network volumes mount on several pods at once.
Use Hyperstack when
you want full GPU or CPU VMs with root and Docker, outbound firewall rules, managed Kubernetes, or CPU machines up to 32 vCPU.
- A full VM, not a container. For work that needs Docker or a whole disk: every Hyperstack machine is a full VM with root, and its images can ship Docker.
- Firewall rules and Kubernetes. For teams that must lock outbound traffic to set IPs and ports, or run managed Kubernetes clusters.
- Resources that are not shared. For steady jobs: Hyperstack maps every flavor 1:1 to physical resources, with no oversubscription, and offers CPU flavors up to 32 vCPU.
Where boat fits
Runpod and Hyperstack are GPU clouds built for training and serving models. If what you are really running is agents that write and run code on CPUs, boat gives each one a full VM with Docker and /dev/kvm, a disk saved every minute, a desktop and coding agents built in. Keep the GPU part of the work on Runpod or Hyperstack.
The whole disk, saved every minute
A stopped Runpod pod keeps only /workspace and bills it at double rate. A stopped Hyperstack VM bills in full unless you hibernate it, and snapshots are taken by hand with the VM off. Agents that break things need a recent copy to roll back to.
A desktop and HTTPS URLs on every machine
Runpod gives a terminal and Jupyter, Hyperstack gives SSH and a text console, so computer-use agents have no screen. On either one you install a desktop stack, a VNC server and certificates on every image yourself.
Coding agents and a keys proxy built in
On both clouds keys reach the machine as environment variables or files, where code an agent runs can read them and send them away. Their MCP servers manage the cloud from your laptop, so you still write the code that starts and watches each agent.
Use boat when your agents write and run code for hours on CPUs: installs, Docker, builds, tests and emulators on a full VM whose disk is saved every minute and costs nothing while stopped, with a desktop, HTTPS URLs and coding agents built in. Compare it one to one: boat vs Runpod and boat vs Hyperstack.
Questions people ask
Is Runpod cheaper than Hyperstack?
For CPU work in our scenarios, yes: one coding agent on workdays comes to $26 a month on Runpod and $114 on Hyperstack, and one agent running all month to $93 versus $475. Hyperstack's closest flavor has 8 vCPU / 8 GB against Runpod's 4 vCPU / 8 GB, so part of the gap is size. boat comes to $20 and $26 for the same two.
Which is faster, Runpod or Hyperstack?
We have no comparable CPU measurement for either one. boat did 26.69 Node.js build-and-test runs per second at 4 vCPU / 8 GB in StarSling's benchmark run.
Can Runpod run Docker like Hyperstack?
No. A Runpod pod is itself a container, and Runpod's docs say you cannot start your own Docker or use Docker Compose on a pod. Hyperstack VMs are full machines with root, and their Ubuntu images come with or without Docker. boat sandboxes come with Docker, Docker Compose, systemd and /dev/kvm.
Do stopped machines cost money on Runpod and Hyperstack?
Yes on both. A stopped Runpod pod keeps billing its /workspace volume, and a SHUTOFF Hyperstack VM bills at the full rate until you hibernate or delete it. On boat a stopped sandbox costs nothing and keeps its whole disk.
Which has more GPUs?
Runpod lists more types, including AMD MI300X, and joins nodes into multi-node clusters. Hyperstack rents Nvidia cards from RTX A4000 to B300, as single cards or 8-GPU nodes, with spot and reserved prices. boat has no GPUs.
Where does my data run?
Runpod has data centers in the US, Canada, Europe and Australia. Hyperstack has regions in Norway, Canada and the US. boat runs only in the EU (Germany, Finland and France), with EU data residency.
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