On-demand · No contracts · Per-second billing
Rent GPU Servers On-Demand
Instant access to NVIDIA RTX 4090, A100, H100, and more. No long-term contracts, no upfront costs. Pay per second and scale up or down as needed.
How GPU rental works on VectorLay
Go from zero to a running GPU server in under 5 minutes.
Sign up and choose your GPU
Create a free account and browse our GPU catalog. Choose from 8+ NVIDIA GPU models ranging from RTX 3080 ($0.19/hr) to H200 ($2.49/hr). No credit card required to get started.
Configure and deploy
Select your container image (or bring your own Docker image), specify the number of GPUs, and hit deploy. VectorLay handles provisioning, GPU passthrough, and networking automatically.
Use your GPU server
Within minutes you have a live endpoint with SSH access and full GPU passthrough. Auto-failover and load balancing are built in. Scale up by adding more GPUs, scale down by removing them. Pay only for what you use.
GPUs available to rent
From budget-friendly RTX 3080s to cutting-edge H200s. All with full VFIO passthrough.
GPU rental pricing vs competitors
VectorLay offers the lowest GPU rental prices with the most inclusive pricing.
| Provider | RTX 4090 | A100 | H100 |
|---|---|---|---|
| VectorLay | $0.49 | $0.80 | $1.80 |
| RunPod | $0.74 | $1.64 | $3.49 |
| Lambda Labs | N/A | $1.10 | $2.49 |
| AWS | N/A | $3.40 | $4.76 |
| GCP | N/A | $2.48 | $4.15 |
Why VectorLay is cheaper than AWS, GCP, and RunPod
Up to 76% less than hyperscalers — here's why the math works out.
Distributed infrastructure
We aggregate GPU capacity from providers worldwide instead of building our own data centers. This eliminates the massive capital expenditure that hyperscalers pass on to you as markups.
No egress fees
AWS, GCP, and Azure charge $0.08–$0.12 per GB for data transfer out. On large inference workloads, egress can add 20–40% to your bill. VectorLay charges $0 for egress, ever.
Consumer GPU efficiency
RTX 4090s deliver 82.6 TFLOPS of FP32 compute at $0.49/hr. An A10G on AWS costs $1.21/hr for less throughput. For inference workloads under 34B parameters, consumer GPUs win on price-performance.
Why rent GPUs instead of buying?
Renting gives you flexibility, lower risk, and access to the latest hardware.
No upfront capital
A single RTX 4090 costs $1,600+. An H100 costs $30,000+. Renting lets you access the same hardware with zero upfront cost and no depreciation risk.
Scale up and down instantly
Need 10 GPUs for a training run and 2 for inference? Scale your GPU fleet in minutes instead of waiting weeks for hardware procurement.
No maintenance burden
Hardware fails. Drivers need updates. Cooling systems break. When you rent GPUs, the provider handles all of this. You just run your workloads.
Access the latest hardware
New GPU generations drop every 1–2 years. Renting means you can switch to the latest H200 or RTX 5090 without being stuck with last-gen hardware.
Try before you commit
Not sure if an A100 or RTX 4090 is better for your workload? Rent both for an hour, benchmark, and choose the best fit. Total cost: under $2.
No power or cooling costs
A single H100 draws 700W. Running 8 GPUs 24/7 costs $800+/month in electricity alone. Renting includes all power and cooling in the hourly price.
Frequently Asked Questions
How do I rent a GPU server?
Sign up at vectorlay.com, choose your GPU (RTX 4090, A100, H100, etc.), select your container image or bring your own Docker image, and hit deploy. Your GPU server will be ready in minutes with a live endpoint, SSH access, and full GPU passthrough.
What is the minimum rental period?
There is no minimum rental period on VectorLay. You can rent a GPU for as little as one second. Billing is per-second with no minimum commitment, no setup fees, and no cancellation fees. Spin up a GPU, run your workload, and shut it down when you're done.
Can I rent multiple GPUs at once?
Yes. You can rent multiple GPUs and VectorLay will automatically load balance your workloads across them. This is ideal for scaling inference throughput or running distributed training. Auto-failover ensures reliability even if individual GPU nodes go down.
What kind of GPU access do I get?
You get full, dedicated GPU access via VFIO passthrough. The GPU is not shared or virtualized — your container gets bare-metal performance with direct access to all CUDA cores, VRAM, and tensor cores. You also get full root SSH access to your server.
Is renting a GPU cheaper than buying?
For most use cases, yes. An RTX 4090 costs $1,600+ to buy, plus electricity, cooling, and maintenance. At $0.49/hr on VectorLay, you'd need to run it 24/7 for over 4 months before buying becomes cheaper — and that doesn't include power costs, maintenance, or the opportunity cost of capital. For variable or part-time workloads, renting is significantly cheaper.
What is the cheapest GPU server available?
VectorLay's cheapest GPU server starts at $0.19/hr for an RTX 3080 with 10GB VRAM. For 24GB VRAM (sufficient for most LLMs and image generation models), the RTX 3090 is $0.29/hr. These are significantly cheaper than AWS ($0.53/hr for a T4 with 16GB), RunPod ($0.44/hr for an RTX 3090), and GCP ($0.35/hr for a T4). All prices include storage and networking with no egress fees.
Do you offer reserved or long-term GPU rental?
Yes. VectorLay offers reserved pricing with a 1-year commitment at 30% savings. For example, an RTX 4090 drops from $0.49/hr to $0.34/hr with reserved pricing. Contact us for custom volume pricing on larger deployments.
Rent your first GPU server
No credit card required. No contracts. No egress fees. Just fast, affordable GPU compute.