Fixed ≥30% below market
Every model priced from the public marketplace median, minus 30%, rounded down. Re-checked weekly, published openly.
GPU cloud · fixed prices · per-second billing
Rent cloud GPUs 30% below market price.
80 GPU models from $0.024/hr — H100 SXM at $1.428/hr while the marketplace median sits at $2.04. Fixed prices verified weekly, no auctions, deploy in 30 seconds.
80GPU models, RTX 3060 to B300
4,800+GPUs ready to deploy now
32regions worldwide
≥30%below market median, always
99.9%uptime SLA on-demand
Cloud GPU prices: fixed, at least 30% under the market median
Marketplace medians move every hour; our price is fixed and always at least 30% under them. Same card, same hour — smaller invoice.
| GPU | VRAM | Market medianon-demand | PowerGPUon-demand, per GPU-hr | Est. / month | Availability | Action |
|---|---|---|---|---|---|---|
| B200 flagship | 192 GB | $7.75 | $5.425 −30% | $3,960 | 32× | Deploy |
| H200 flagship | 141 GB | $3.99 | $2.791 −30% | $2,037 | 50× | Deploy |
| H100 SXM flagship | 80 GB | $2.04 | $1.428 −30% | $1,042 | 54× | Deploy |
| H100 PCIE flagship | 80 GB | $2.67 | $1.867 −30% | $1,363 | 73× | Deploy |
| A100 SXM4 | 80 GB | $0.80 | $0.560 −30% | $409 | 95× | Deploy |
| L40S | 48 GB | $0.74 | $0.514 −30% | $375 | 107× | Deploy |
| RTX PRO 6000 WS | 96 GB | $1.49 | $1.040 −30% | $759 | 74× | Deploy |
| RTX 6000Ada | 48 GB | $0.67 | $0.467 −30% | $341 | 34× | Deploy |
| RTX 5090 | 32 GB | $0.63 | $0.439 −30% | $320 | 922× | Deploy |
| RTX 4090 | 24 GB | $0.47 | $0.327 −30% | $239 | 461× | Deploy |
Interruptible = 50% of on-demand, pausable under capacity pressure · Reserved = −35% with a 3-month commitment · See all 80 GPUs · Compare GPUs side by side · Cost calculator
Why rent GPUs here: marketplace prices, cloud-grade certainty
We buy capacity where the marketplaces do — then sell it like a cloud should.
No bidding, no evictions
On-demand means yours until you stop it. Interruptible is a flat −50% — not an auction you babysit at 2am.
Verified datacenters only
Tier-III facilities, redundant power and network, tested hardware — not a gaming rig in a garage.
Per-second billing
Start to stop, to the second. Storage at $0.08/GB/mo, bandwidth $0.01/GB flat. No setup fees, no minimums.
Every way to run a GPU: on-demand, interruptible, reserved, serverless
From a single interruptible card to a reserved InfiniBand cluster — same console, same API, same price sheet.
- On-demand GPUs Fixed price, guaranteed resources, per-second billing Learn more
- Interruptible Half the on-demand price for fault-tolerant jobs Learn more
- Reserved Commit 3+ months, save another 35% Learn more
- Serverless Autoscaling endpoints for vLLM, ComfyUI and your images Learn more
- Clusters Multi-node InfiniBand/NVLink for distributed training Learn more
- Virtual machines Full VMs with root, custom kernels and GUI images Learn more
- Volumes NVMe network storage at $0.08/GB/mo Learn more
- Templates PyTorch, CUDA, ComfyUI, vLLM, Jupyter — ready in one click Learn more
How to rent a GPU in 30 seconds
Pick a card, launch a template, stop when you're done. The console on the right is a live walkthrough — at our real prices.
Filter 80 models by VRAM, price or workload. The price you see is the price you pay — per second.
Search GPUs80 models · 4,800+ GPUs online
-
H100 SXM80 GB · Hopper
$2.04$1.428/hr 54× Deploy -
RTX 509032 GB · Blackwell
$0.63$0.439/hr 922× Deploy -
RTX 409024 GB · Ada Lovelace
$0.47$0.327/hr 461× Deploy -
L40S48 GB · Ada Lovelace
$0.74$0.514/hr 107× Deploy
Fixed price per GPU-hour, billed per second. Struck-through: public marketplace median, snapshot 2026-09-14.
Choose a template37 templates · or any Docker image
PyTorchpowergpu/pytorch:2.6-cuda12.8
vLLMpowergpu/vllm
ComfyUIpowergpu/comfyui
Ollamapowergpu/ollama
NVIDIA CUDApowergpu/base:cuda13
Ubuntu 22.04 VMpowergpu/kvm:ubuntu-22.04
$ powergpu launch --gpu h100-sxm --template pytorch✓ instance i-9f2c41ab running in eu-west (18.4s)✓ ssh root@i-9f2c41ab.powergpu.ai · JupyterLab on :8888# billed per second · $1.428/hr · stop anytime
SSH keys injected, ports mapped, volumes attached — the same one click from the console.
Your instancelive demo · real H100 SXM rate
Runningi-9f2c41ab eu-west
GPU1× H100 SXM · 80 GB
TemplatePyTorch 2.6 · CUDA 12.8
Rate$1.428/hr
Running for00:00per-second clock
Billed so far$0.0000= $0.000397 per second
Snapshot to a volume
Stop it and the meter stops with it — storage is the only line that keeps running ($0.08/GB-month).
- No card — pay in USDT, BTC, XMR…
- Per-second billing, no minimums
- Stop = billing stops
Best GPU for each workload, priced for the run
Pick by workload — we pre-matched the best value card for each.
-
LLM training
80 GB HBM3, NVLink, multi-node
Best value: H100 SXM $1.428/hr
-
LLM inference
Best $/token for 7B–70B models
Best value: RTX 5090 $0.439/hr
-
Fine-tuning
LoRA/QLoRA sweet spot
Best value: A100 SXM4 $0.560/hr
-
Image & video gen
SDXL, Flux, ComfyUI pipelines
Best value: RTX 4090 $0.327/hr
-
3D rendering
Blender, Octane, Redshift
Best value: RTX PRO 6000 WS $1.040/hr
-
Scientific compute
FP64, huge memory bandwidth
Best value: H200 $2.791/hr
PowerGPU vs GPU marketplaces vs hyperscalers
PowerGPU against GPU marketplaces and the big clouds, line by line.
| PowerGPU | GPU marketplaces | Hyperscalers | |
|---|---|---|---|
| H100 SXM, per GPU-hour | $1.428 fixed | US$2.04 median, varies by host | $4–$7 |
| Pricing model | Fixed, ≥30% below market median | Auction — changes hourly | Fixed, list price |
| Price floor guarantee | Re-checked weekly, published | None | None |
| Billing | Per-second | Per-second | Per-second to per-hour |
| Interruptible discount | 50% off, flat | Bidding — you manage bids | Spot — can spike |
| Hosts | Verified datacenters only | Anyone — reliability varies | Own datacenters |
| Egress / bandwidth | $0.01/GB flat | Set per host, up to $0.02+/GB | $0.05–$0.12/GB |
| Storage | $0.08/GB/mo NVMe | Set per host, varies | $0.08–$0.17/GB/mo |
| Payment | Crypto — USDT, BTC, XMR, SOL… | Card, some accept crypto | Card + invoicing, KYC |
| Setup fee / minimums | None | None | Commit contracts common |
| Deploy time | Under 30 seconds | Under a minute | Minutes |
Market figures: public marketplace pricing feed, snapshot 2026-09-14; hyperscaler ranges: public list prices, September 3, 2026.
Teams that switched, and stayed
-
“We moved our nightly fine-tuning runs from a marketplace to PowerGPU. Same A100s, but the invoice stopped being a lottery — flat rate, per-second, done.”
Lena K. · ML lead, computer-vision startup
-
“The H100 price was 30% under what we were bidding elsewhere, and I did not have to babysit spot auctions at 2am anymore. Deploy, train, tear down.”
Marcus T. · Independent LLM researcher
-
“Rendering on RTX PRO 6000s by the second changed our delivery math. We quote clients from the price sheet — it has not moved under us once.”
Aiko S. · Founder, 3D animation studio
Cloud GPU rental FAQ
Everything else lives in the docs — or ask a human from the console support desk, answered 24/7.
How can prices stay 30% below the market?
We track the public marketplace median for every GPU model and set our on-demand price at least 30% under it, rounding down. Prices are re-checked against the market weekly (last check: September 3, 2026) and published on the pricing page — no auctions, no surprises.
What is the difference between on-demand, interruptible and reserved?
On-demand gives you guaranteed resources at the listed fixed price. Interruptible costs 50% of on-demand but can be paused when capacity is needed — ideal for checkpointed training or batch jobs. Reserved takes another 35% off on-demand for a 3-month commitment.
How is billing calculated?
Per second, from the moment the instance starts to the moment you stop it. Storage is billed per second too ($0.08/GB/mo, also while the instance is stopped), and bandwidth is a flat $0.01/GB in and out. No minimums, no rounding up, no setup fees.
How fast can I get a GPU running?
Under 30 seconds for container instances launched from a template (PyTorch, vLLM, ComfyUI, CUDA…). Full virtual machines take a couple of minutes. Everything is available from the console, CLI, Python SDK or REST API.
Can I run multi-GPU or multi-node workloads?
Yes. Instances go up to 8× GPUs with NVLink where the hardware supports it, and clusters connect nodes over InfiniBand for distributed training. The per-GPU price is the same from 1× to 8× — no multi-GPU premium.
How do I pay?
Crypto only: USDT (TRC-20 or ERC-20), Bitcoin, Monero, Litecoin, Ethereum, TRON and Solana. You top up a credit balance and usage draws it down per second — no card, no bank account. Deposits are credited after network confirmation.