GPU cloud comparison · April 2026
Best GPU Cloud Hosting — 10 Providers Compared
We tested and priced 10 GPU cloud providers so you don't overpay. From $0.10/h community GPUs to enterprise H100 clusters at $4+/h.
Pick by need
What matters most to you?
Click a category — we'll filter the table to the right shortlist.
All 10 providers
GPU Cloud Comparison Table
Filter by region or feature, then sort by what matters to you.
No providers match this filter.
| Provider | Rating | Starting Price | Top GPUs | Highlights | Action |
|---|---|---|---|---|---|
| RunPod Editor's Choice | ★★★★★ | from $0.20/h ≈ $20/mo @100h Verified Apr 27 | RTX 3090, RTX 4090 ≤80GB |
| |
| Lambda Labs Editor's Choice | ★★★★★ | from $1.10/h ≈ $110/mo @100h Verified Apr 27 | A100 40GB, A100 80GB ≤80GB |
| |
| CoreWeave | ★★★★☆ | from $2.06/h ≈ $206/mo @100h Verified Apr 26 | H100 SXM, A100 SXM ≤80GB |
| |
| Paperspace | ★★★★☆ | from $0.45/h ≈ $45/mo @100h Verified Apr 25 | A100, A6000 ≤80GB |
| |
| Google Cloud GPU | ★★★★☆ | from $2.48/h ≈ $248/mo @100h Verified Apr 23 | A100 40GB, A100 80GB ≤80GB |
| |
| Hetzner GPU | ★★★★☆ | from €0.35/h ≈ $38/mo @100h Verified Apr 25 | A100 PCIe, GTX 1080 ≤80GB |
| |
| AWS GPU (EC2) | ★★★★☆ | from $3.06/h ≈ $306/mo @100h Verified Apr 22 | A100, H100 ≤80GB |
| |
| Vast.ai Editor's Choice | ★★★★☆ | from $0.10/h ≈ $10/mo @100h Verified Apr 27 | RTX 3090, RTX 4090 ≤80GB |
| |
| Azure GPU (NCv3/NDA) | ★★★★☆ | from $2.94/h ≈ $294/mo @100h Verified Apr 21 | A100, H100 ≤80GB |
| |
| OVH GPU | ★★★★☆ | from €0.54/h ≈ $58/mo @100h Verified Apr 24 | T4, V100 ≤80GB |
|
Side-by-side comparison
Detailed Provider Reviews
In-depth analysis of each GPU cloud with pros, cons, and best-fit scenarios.
RunPod Editor's Choice
Best value GPU cloud — huge selection, community + secure cloud
- Cheapest community GPUs from $0.20/h
- Massive GPU variety including H100
- Serverless endpoints for inference APIs
- Great UI and pod management
- Community cloud less reliable than dedicated
- Storage costs add up over time
- Support can be slow on free tier
Lambda Labs Editor's Choice
On-demand H100 clusters — developer-favourite for serious ML
- Reliable on-demand H100 availability
- No complex setup — SSH ready in seconds
- Lambda Stack saves setup time
- Competitive pricing vs hyperscalers
- Limited GPU types vs RunPod
- Fewer EU datacenter options
- No serverless endpoints
Vast.ai Editor's Choice
Cheapest GPU cloud — peer-to-peer marketplace for budget training
- Absolute cheapest GPU compute available
- Widest GPU variety including consumer cards
- Good for fault-tolerant batch jobs
- Marketplace competition drives prices down
- Hosts can take instances offline anytime
- Variable reliability across providers
- Less suitable for time-sensitive inference
Paperspace
Gradient notebooks + GPU VMs — great for ML teams
- Best notebook experience of any cloud GPU
- Team collaboration features built-in
- Free tier with limited GPU hours
- Good documentation and tutorials
- Pricier than RunPod for raw compute
- Limited GPU types vs competitors
- Gradient platform has occasional issues
CoreWeave
Enterprise H100 clusters — Kubernetes-native GPU cloud
- Best multi-node GPU cluster performance
- High-speed InfiniBand interconnects
- Purpose-built for AI workloads
- Strong enterprise support
- Expensive — not for hobbyists
- Requires Kubernetes knowledge
- Sales-led process for large clusters
Hetzner GPU
Affordable EU GPU servers — A100 at European prices
- Best GPU pricing in Europe
- GDPR and EU data residency compliant
- Excellent API and automation support
- Trusted Hetzner infrastructure
- Limited GPU types — mainly A100
- No H100 availability yet
- Fewer GPU locations than US providers
OVH GPU
European GPU cloud with NVIDIA T4 and V100 options
- Strong EU data sovereignty guarantees
- Established cloud provider with SLA
- Multi-region EU availability
- Good for government/regulated industries
- Older GPU lineup (V100 still prominent)
- More complex setup vs RunPod
- Higher prices than Hetzner for GPU
Google Cloud GPU
TPU + GPU powerhouse — best ecosystem for TensorFlow
- Best TPU availability for TF workloads
- Deep Vertex AI + BigQuery integration
- Global infrastructure and reliability
- Preemptible instances cut costs significantly
- Expensive on-demand pricing
- Complex billing — easy to overspend
- Steep learning curve for GCP newcomers
AWS GPU (EC2)
Largest GPU fleet worldwide — P4/P5 instances for enterprise
- Most comprehensive ML toolchain (SageMaker)
- Spot instances for massive cost savings
- Best compliance certifications globally
- Inferentia for cost-effective inference
- Most expensive on-demand GPU pricing
- Complex pricing model
- Not beginner-friendly for pure GPU rental
Azure GPU (NCv3/NDA)
Microsoft's GPU cloud — best for Azure ML and enterprise AI
- Deep OpenAI / Azure OpenAI integration
- Best choice for Microsoft-stack enterprises
- Strong compliance and government certifications
- Azure ML Studio for no-code ML
- High on-demand pricing
- Complex portal and billing
- Vendor lock-in with Azure ecosystem
Frequently Asked Questions
What is the cheapest GPU cloud in 2026?
Vast.ai is the cheapest GPU cloud starting from $0.10/h for community-hosted RTX 3090 instances. RunPod is the best balance of price and reliability from $0.20/h.
Is RunPod reliable enough for production?
RunPod's Secure Cloud is reliable for production with dedicated datacenter hardware. Community Cloud is cheaper but hosts can take instances offline. For always-on inference, use Secure Cloud or Lambda Labs.
Which GPU cloud has H100s available?
Lambda Labs, CoreWeave, RunPod, AWS (p5), and Google Cloud all offer H100 access. CoreWeave has the largest H100 cluster inventory. Prices range from ~$2/h (Lambda) to $4+/h (AWS on-demand).
Should I use AWS/GCP/Azure or a specialist GPU cloud?
For pure GPU compute, specialist clouds (RunPod, Lambda, Vast.ai) are 2–5× cheaper than hyperscalers. Use AWS/GCP/Azure only if you need tight ML service integration (SageMaker, Vertex AI) or strict enterprise compliance.
What GPU do I need for fine-tuning Llama 3 70B?
You need at least an A100 80GB, or 2× A100 40GB in NVLink. For Llama 3 8B, a 24GB RTX 3090/4090 is sufficient. RunPod is the best value option for both.