Cheapest GPU Cloud in 2026 — Live Price Comparison
The GPU cloud market is fragmented — prices vary 4-5× for the same hardware depending on provider, region, and pricing tier. GPUHawk tracks 108 live listings across 11 providers so you don't have to check each one manually.
Cheapest GPU Cloud Options by Model
These are the lowest on-demand prices we're currently tracking for each GPU model. Prices update every 6 hours from 11 providers. Click any GPU model to see all providers and pricing tiers.
| GPU Model | Cheapest Price | Est. Monthly | Provider | VRAM | Action |
|---|---|---|---|---|---|
| RTX A4000 | $0.0700/hr | $51/mo | TensorDock | 16 GB | Rent → |
| RTX 3090 | $0.1000/hr | $73/mo | Salad Cloud | 24 GB | Rent → |
| RTX 4090 | $0.1600/hr | $117/mo | Salad Cloud | 24 GB | Rent → |
| RTX A5000 | $0.2100/hr | $153/mo | TensorDock | 24 GB | Rent → |
| RTX A6000 | $0.4022/hr | $294/mo | Vast.ai | 48 GB | Rent → |
| L40S | $0.6000/hr | $438/mo | Salad Cloud | 48 GB | Rent → |
| A100 SXM | $0.6563/hr | $479/mo | Vast.ai | 39 GB | Rent → |
| A100 PCIe | $0.6951/hr | $507/mo | Vast.ai | 80 GB | Rent → |
| L40 | $0.8200/hr | $599/mo | RunPod | 48 GB | Rent → |
| Gaudi 2 | $1.2100/hr | $883/mo | Sesterce | 96 GB | Rent → |
| GH200 | $1.6400/hr | $1197/mo | Sesterce | 96 GB | Rent → |
| H100 PCIe | $1.8000/hr | $1314/mo | FluidStack | 80 GB | Rent → |
| H100 SXM | $1.8300/hr | $1336/mo | Sesterce | 80 GB | Rent → |
| H100 NVL | $1.9500/hr | $1424/mo | Sesterce | 94 GB | Rent → |
| H200 SXM | $2.0900/hr | $1526/mo | Sesterce | 141 GB | Rent → |
| B200 SXM | $4.1688/hr | $3043/mo | Vast.ai | 179 GB | Rent → |
| HGX B300 | $7.3900/hr | $5395/mo | RunPod | 288 GB | Rent → |
Prices shown are on-demand (guaranteed). See all 108 listings →
GPU Cloud Provider Comparison
All 11 providers tracked by GPUHawk, ranked by cheapest available GPU. Each provider has different strengths — some focus on consumer GPUs at low prices, others specialize in enterprise H100/A100 clusters.
| Provider | GPU Models | Cheapest GPU | Total Listings | Available GPUs |
|---|---|---|---|---|
| TensorDock | 7 | $0.0700/hr | 7 | RTX A4000, RTX A5000 |
| Salad Cloud | 5 | $0.1000/hr | 5 | RTX 3090, RTX 4090, L40S |
| Vast.ai | 12 | $0.1222/hr | 12 | RTX A6000, A100 SXM, A100 PCIe, B200 SXM |
| RunPod | 15 | $0.2500/hr | 17 | L40, HGX B300 |
| FluidStack | 5 | $0.3200/hr | 5 | H100 PCIe |
| Hyperstack | 5 | $0.5000/hr | 5 | — |
| Verda | 4 | $0.5500/hr | 4 | — |
| Sesterce | 9 | $0.7200/hr | 9 | Gaudi 2, GH200, H100 SXM, H100 NVL, H200 SXM |
| CoreWeave | 7 | $0.7700/hr | 7 | — |
| Lambda Labs | 5 | $0.9900/hr | 5 | — |
| Vultr | 2 | $2.0100/hr | 2 | — |
Need a specific GPU? Filter by model, provider, and price type →
How Prices Change: Spot vs On-Demand
On-demand instances are guaranteed — you keep them as long as you're paying. Spot (interruptible) instances are cheaper because the provider can reclaim them when demand spikes. The savings can be massive:
| GPU Model | On-Demand | Spot | Savings |
|---|---|---|---|
| A100 PCIe | $0.6951/hr | $0.5618/hr | 19% cheaper |
| A100 SXM | $0.6563/hr | $0.1535/hr | 77% cheaper |
| B200 SXM | $4.1688/hr | $3.8483/hr | 8% cheaper |
| H100 NVL | $1.9500/hr | $2.5900/hr | -33% cheaper |
| H100 PCIe | $1.8000/hr | $1.9900/hr | -11% cheaper |
| H100 SXM | $1.8300/hr | $1.4422/hr | 21% cheaper |
| H200 SXM | $2.0900/hr | $0.5000/hr | 76% cheaper |
| HGX B300 | $7.3900/hr | $2.0044/hr | 73% cheaper |
| L40 | $0.8200/hr | $0.6900/hr | 16% cheaper |
| L40S | $0.6000/hr | $0.4704/hr | 22% cheaper |
| RTX 3090 | $0.1000/hr | $0.1342/hr | -34% cheaper |
| RTX 4090 | $0.1600/hr | $0.1950/hr | -22% cheaper |
| RTX A4000 | $0.0700/hr | $0.1089/hr | -56% cheaper |
| RTX A5000 | $0.2100/hr | $0.1600/hr | 24% cheaper |
| RTX A6000 | $0.4022/hr | $0.1356/hr | 66% cheaper |
When to use spot instances
- Training runs with checkpointing — save progress every N steps, resume if interrupted
- Batch inference — process a large dataset where partial completion is OK
- Hyperparameter sweeps — run many short experiments in parallel
When to use on-demand
- Production serving — API endpoints that need to stay up
- Interactive development — Jupyter notebooks and debugging sessions
- Critical deadlines — can't afford an interruption mid-job
Why checking regularly matters
GPU cloud pricing is not static. Providers adjust prices based on supply and demand, new hardware launches shift the market, and promotional pricing comes and goes. A provider that was cheapest last month may not be cheapest today. GPUHawk tracks all 11 providers automatically so you always see the current best deal.
How to Choose the Right Cloud GPU
RTX 3090 / RTX 4090
24 GB VRAM. Best price-to-performance for inference, Stable Diffusion, and fine-tuning models up to ~13B parameters. The RTX 4090 is the default choice for cost-conscious ML work.
RTX 4090 pricing →A100 40GB / L40S
40-48 GB VRAM. Handles medium models, multi-GPU training, and production inference. The A100 is the industry standard; the L40S is newer with better efficiency.
A100 40GB pricing →A100 80GB / H100
80 GB VRAM. Required for training models above 30B parameters and running large models at full precision. The H100 is 2-3× faster than A100 for transformer workloads.
H100 SXM pricing →Frequently Asked Questions
What is the cheapest GPU cloud in 2026?
It depends on the GPU model you need. Based on live pricing data from 11 providers, the cheapest option changes frequently as providers adjust prices. Check current prices on our compare page, which updates every 6 hours.
How much does a cloud GPU cost per hour?
Cloud GPU pricing ranges from under $0.20/hr for consumer GPUs (RTX 3090, RTX 4090) to $2-4/hr for enterprise GPUs (H100, H200). The average across all 108 listings is $1.71/hr. Monthly costs at 24/7 usage range from ~$150 to $3,000+.
What is the difference between spot and on-demand GPU pricing?
Spot (interruptible) instances can be 30-70% cheaper than on-demand, but the provider can reclaim them at any time. On-demand instances cost more but are guaranteed. Use spot for fault-tolerant batch jobs; on-demand for production serving and interactive work.
Which cloud GPU is best for deep learning?
For training large models: H100 SXM or A100 80GB. For inference and fine-tuning: RTX 4090 offers exceptional price-to-performance. For production serving: L40S or A10G. See our GPU model pages for detailed specs and pricing per model.
How often are GPUHawk prices updated?
Prices are scraped from all 11 providers every 6 hours. The data on this page is cached for 5 minutes to keep page loads fast while staying current.
Compare All 108 GPU Listings
Filter by GPU model, provider, pricing tier, and VRAM. Find the cheapest option for your specific workload.
Open Full Comparison →