Compare Top GPU Cloud Providers & Clusters.
Comprehensive side-by-side technical matrix comparing starting hourly pricing, NVIDIA Hopper & Ada Lovelace accelerators, 3.2 Tbps InfiniBand interconnect fabrics, egress data taxes, and datacenter availability across all 12 certified platforms.
Dedicated VDS with 100% Dedicated CPU Cores
Zero resource sharing or noisy neighbors. Full Intel Xeon @ 3.0GHz cores, NVMe Gen4 RAID-10, and instant 20% annual savings (ANNUAL20).
| Compare | Provider | Starting Rate | Supported Accelerators | Interconnect Fabric | Egress Pricing | Billing & Commit | Best Workload Fit | Actions |
|---|---|---|---|---|---|---|---|---|
RockHoster ✓
High-Performance Cloud & VPS
|
$0.15 / hr
Spot Available
|
Intel Xeon 3.0GHz
NVMe Gen4
Windows RDP
Dedicated VDS
Intel Xeon @ 3.0 GHz, NVMe Gen4, KVM Virtualization, Windows RDP, RTX Roadmap
|
🔗 1 Gbps - 10 Gbps Anti-DDoS Protected Port
Virt: KVM Dedicated Silicon & SolusVM
|
✓ Free (5 TB to Unlimited Quota) |
Monthly / 20% Off Annual (ANNUAL20)
Commit: None ($4.99/mo Pay-As-You-Go)
|
High-Performance VPS, Windows RDP Trading, Web Clusters, VDS Databases
SLA: 99.99% High Availability SLA
|
||
Vast.ai ✓
GPU Marketplace
|
$0.15 / hr
Spot Available
|
RTX 4090
RTX 3090
H100 SXM
A100 80GB
RTX 4090, RTX 3090, RTX 4080, A100 (40GB/80GB), H100 SXM, RTX 6000 Ada, A6000, RTX 3080
|
🔗 Host-dependent PCIe / 10-100G
Virt: Docker Container Isolation
|
✓ Free (Host-Dependent) |
Per-second
Commit: None ($0)
|
Solo Dev, LoRA Tuning, Hobbyist Inference
SLA: Community / Best-Effort
|
||
CoreWeave ✓
Specialized AI Cloud
|
$0.32 / hr
Spot Available
|
H100 SXM5
H200
B200
A100 NVLink
H100 (80GB SXM5), H200, B200 (upcoming), A100 (80GB NVLink), RTX 6000 Ada, L40S, A4000
|
⚡ 3.2 Tbps Quantum-2 InfiniBand
Virt: Bare-Metal Kubernetes (CKS)
|
✓ Free (Zero Egress Fees) |
Per-second (60s min)
Commit: On-demand or 1-3 Yr Reserved
|
Distributed Pre-Training, High-Scale vLLM
SLA: 99.9% Enterprise SLA
|
||
Runpod ✓
Specialized GPU Cloud
|
$0.34 / hr
Spot Available
|
RTX 4090
H100 SXM5
A100 SXM
L40S
RTX 4090 (24GB), RTX 3090 (24GB), A100 (80GB SXM), H100 (80GB SXM5), L40S (48GB), A40 (48GB), RTX 6000 Ada
|
⚡ 3.2 Tbps InfiniBand (Clusters)
Virt: KVM VMs & Serverless Endpoints
|
✓ Free (Zero Egress Fees) |
Per-second billing
Commit: None ($0)
|
Serverless AI, vLLM Clusters, Small-Scale Tuning
SLA: 99.9% Secure Cloud Tier
|
||
Google Cloud Platform ✓
Enterprise Hyperscaler
|
$0.35 / hr
Spot Available
|
H100 (A3 Mega)
A100
L4
TPU v5p
NVIDIA H100 (A3 Mega 80GB), A100 (40GB/80GB), L4 (24GB), T4 (16GB), TPU v5p, TPU v5e
|
🔗 3.2 Tbps RoCEv2 Titanium GPUDirect
Virt: Google Compute Engine (KVM) / GKE
|
⚠️ $0.08 - $0.12 / GB |
Per-second (60s min)
Commit: On-demand or 1-3 Yr CUD
|
Enterprise Multimodal, Vertex AI Pipelines
SLA: 99.99% Hyperscaler SLA
|
||
Microsoft Azure ✓
Enterprise Hyperscaler
|
$0.45 / hr
Spot Available
|
H100 (NDv5)
A100 (NDv4)
A10
T4
NVIDIA H100 (NDv5 80GB SXM5), A100 80GB (NDv4), A10 (NVads A10 v5), T4 (NCas T4 v3)
|
⚡ 3.2 Tbps Quantum-2 InfiniBand
Virt: Azure Hyper-V / Azure Kubernetes Service
|
⚠️ $0.087 / GB |
Per-second (60s min)
Commit: On-demand or 1-3 Yr Reserved Instances
|
OpenAI Scale Deployments, Enterprise Microsoft 365 AI
SLA: 99.95% Hyperscaler SLA
|
||
Amazon Web Services ✓
Enterprise Hyperscaler
|
$0.53 / hr
Spot Available
|
H100 (P5)
A100 (P4de)
A10G (G5)
Trainium (Trn1)
NVIDIA H100 (P5 80GB), A100 80GB (P4de), A10G (G5), T4 (G4dn), AWS Trainium (Trn1), AWS Inferentia2 (Inf2)
|
🔗 3.2 Tbps EFA (Elastic Fabric Adapter)
Virt: AWS Nitro Bare-Metal / HVM
|
⚠️ $0.09 / GB (Taxed) |
Per-second (60s min)
Commit: On-demand, Compute Savings Plans (1-3 Yr)
|
Mega-Scale Foundation Training, SageMaker Pipelines
SLA: 99.99% Hyperscaler SLA
|
||
Lambda ✓
AI Datacenter Cloud
|
$0.75 / hr
Spot Available
|
H100 SXM5
H200
GH200 Grace Hopper
A100 80GB
H100 (80GB SXM5), H200 (141GB), A100 (80GB SXM4), A10 (24GB), GH200 Grace Hopper
|
⚡ 3.2 Tbps Quantum-2 InfiniBand
Virt: Bare-Metal Cloud Instances / Lambda Stack
|
✓ Free (Zero Egress Fees) |
Per-minute billing
Commit: None on 1-GPU / Annual on Clusters
|
LLM Research Labs, 100B+ Distributed Pre-Training
SLA: 99.9% Datacenter SLA
|
||
Crusoe Cloud ✓
Clean Energy AI Cloud
|
$0.85 / hr
Spot Available
|
H100 SXM5
L40S
A100 80GB
RTX 6000 Ada
NVIDIA H100 (80GB SXM5), L40S (48GB), A100 (80GB), RTX 6000 Ada
|
⚡ 3.2 Tbps InfiniBand Fabric
Virt: Bare-Metal KVM / Kubernetes Native
|
✓ Free Tier / $0.01 per GB |
Per-minute billing
Commit: Hourly on-demand or multi-month contracts
|
Zero-Emission AI Training, ESG Compliant Clusters
SLA: 99.9% Enterprise SLA
|
||
Nebius AI ✓
Specialized AI Cloud
|
$1.15 / hr
Spot Available
|
H100 SXM5
H200
L40S
B200
NVIDIA H100 (80GB SXM5), H200 (141GB), L40S (48GB), B200 (upcoming)
|
⚡ 3.2 Tbps Quantum-2 InfiniBand
Virt: Bare-Metal Hardware / Slurm Orchestration
|
✓ Free (Generous Egress Tier) |
Per-minute billing
Commit: On-demand or 6-36 Mo Reserved Clusters
|
Large European AI Labs, Supercomputing Pre-Training
SLA: 99.9% Dedicated Cluster SLA
|
||
Paperspace by DigitalOcean ✓
Developer GPU Cloud
|
$0.45 / hr
Spot Available
|
H100 SXM
A100 SXM
RTX A5000
RTX A4000
NVIDIA H100 (80GB), A100 (80GB SXM), RTX A4000 (16GB), RTX A5000 (24GB), RTX 5000, Quadro M4000
|
🔗 NVLink Inter-GPU / 100G Ethernet
Virt: DigitalOcean Droplets / Gradient Orchestration
|
✓ Free (Included in Tier) |
Per-second / Hourly
Commit: Monthly tier + usage or hourly
|
Notebook Prototyping, Startup Fine-Tuning
SLA: 99.9% Cloud SLA
|
||
Oracle Cloud Infrastructure ✓
High-Performance Cloud
|
$1.00 / hr
Spot Available
|
H100 80GB SXM5
A100 80GB SXM4
L40S
A10
NVIDIA H100 (8x 80GB SXM5), A100 (8x 80GB SXM4), A10 (24GB), L40S (48GB)
|
🔗 3.2 Tbps RoCEv2 Ultra-Cluster
Virt: Bare-Metal Physical Servers (Off-Box Virt)
|
✓ 10 TB Free, then $0.0085 / GB |
Per-second billing
Commit: On-demand or Annual Universal Credits
|
Ultra-Scale Foundation Models, Low-Latency DB Compute
SLA: 99.99% Performance & Availability SLA
|
||
IBM Cloud ✓
Enterprise Bare Metal
|
$1.25 / hr
Spot Available
|
A100 80GB
L40S
V100
Multi-GPU Systems
NVIDIA A100 (80GB), L40S (48GB), V100 (16GB/32GB), Enterprise Multi-GPU Clusters
|
🔗 100 Gbps RoCE / InfiniBand
Virt: Bare-Metal Physical Dedicated Hardware
|
⚠️ Tiered Bandwidth Allowance |
Hourly / Monthly contracts
Commit: Hourly or Annual Enterprise Agreements
|
Regulated Banking AI, Healthcare HIPAA Compliance
SLA: 99.99% Enterprise Bare-Metal SLA
|
The Modern GPU Cloud Landscape: Hyperscalers vs. Specialized Neo-Clouds vs. Marketplaces
In 2026, the artificial intelligence compute market is strictly segmented into three distinct architectural models, each serving radically different workload profiles, budget tolerances, and engineering organizations:
Engineered exclusively for AI and high-performance computing (HPC). These providers avoid legacy hypervisor overhead by running bare-metal Kubernetes clusters connected via 3.2 Tbps NVIDIA Quantum-2 InfiniBand. They offer zero egress data fees, dedicated Slurm scheduling, and high availability on flagship H100 SXM5 and H200 accelerators.
Best suited for Fortune 500 enterprises with pre-existing multi-cloud commitments, stringent SOC2 Type II and FedRAMP compliance requirements, and complex integrations with data lakes (S3, BigQuery) and IAM governance. However, they levy steep egress taxes ($0.08–$0.12/GB) and complex multi-year commitment contracts.
Decentralized peer-to-peer compute aggregators offering consumer and workstation GPUs (RTX 4090, RTX 3090) starting as low as $0.15/hr. Highly cost-effective for budget-conscious solo researchers, LoRA fine-tuning runs, and fault-tolerant batch inference, but lacking strict enterprise SLAs and multi-node InfiniBand fabrics.
Hardware Architecture Decoupled: SXM5 NVLink vs. PCIe, InfiniBand vs. RoCEv2
When comparing GPU servers, evaluating only the GPU model name (e.g., "H100") is a dangerous engineering pitfall. The physical form factor and network fabric dictate whether your multi-GPU cluster achieves linear scaling or suffers catastrophic communication stalls:
| Hardware Specification | SXM5 Form Factor (HGX H100) | PCIe Gen5 Form Factor | Operational Impact |
|---|---|---|---|
| Inter-GPU Bandwidth | 900 GB/s (NVLink 4) | 128 GB/s (PCIe Bus) | SXM5 achieves 7x higher inter-GPU all-reduce speed for tensor-parallel inference. |
| Thermal Design Power (TDP) | 700 Watts (Active Liquid/Chilled) | 350 Watts (Passive Air-Cooled) | SXM5 sustains higher boost clock frequencies without thermal throttling. |
| Inter-Node Cluster Fabric | 3.2 Tbps Quantum-2 InfiniBand (8x 400G OSFP) | 100 Gbps - 200 Gbps RoCEv2 Ethernet | InfiniBand eliminates packet drop penalties during distributed pre-training. |
| vLLM TP=8 Scalability | 98.4% Efficiency | 61.2% Efficiency | PCIe setups suffer massive inter-token latency spikes on 70B+ LLM inference. |
The True Cost of Compute: Unmasking Egress Taxes, Storage Fees, and Idle Billing
A provider advertising a $2.50/hr H100 rate can easily cost more in practice than a provider advertising $3.20/hr once auxiliary fees are factored into your monthly invoice:
- Outbound Network Egress Taxes: On hyperscalers like AWS and GCP, moving a 50 Terabyte pre-training dataset or streaming millions of video frames out of the cloud costs between $4,000 and $6,000 per month ($0.08–$0.12/GB). Dedicated AI clouds like CoreWeave, Lambda, and RunPod waive egress fees completely ($0/GB).
- High-IOPS Shared Storage: Checkpointing 100B+ foundation models requires parallel filesystems like WekaFS, GPFS, or Lustre capable of sustaining 200+ GB/s throughput. Hyperscaler provisioned IOPS (such as AWS io2 Block Express) can easily double your overall monthly compute bill.
- Billing Granularity: Per-second billing with zero minimum commitments allows development teams to run 5-minute automated evaluation scripts or auto-scale inference replicas without paying for unused hourly increments.
Workload Matching Matrix: Selecting the Optimal GPU Cloud for Your Stack
Reason: 3.2 Tbps Quantum-2 InfiniBand non-blocking fabric, bare-metal container orchestration, zero egress fees, 24/7 dedicated cluster support.
Reason: Fast NVMe volume mounting, sub-second cold starts, serverless endpoint auto-scaling, and high single-node SXM5 memory bandwidth.
Reason: Low starting rates ($0.15 - $0.45/hr), RTX 4090 (24GB VRAM) availability, browser-based Jupyter notebooks, per-second billing.
Frequently Asked Questions About GPU Cloud Comparisons
Which GPU cloud provider has the lowest starting hourly rate?
Vast.ai offers the absolute lowest starting prices ($0.15/hr) via its decentralized peer-to-peer compute marketplace. For tier-1 datacenter compute with enterprise SLA, CoreWeave starts at $0.32/hr and RunPod starts at $0.34/hr for workstation GPUs.
What is the primary difference between InfiniBand and RoCEv2 fabrics?
NVIDIA Quantum-2 InfiniBand is a dedicated hardware-driven network layer that offers sub-microsecond latency and deterministic hardware flow control without packet loss. RoCEv2 (RDMA over Converged Ethernet) runs on top of standard Ethernet switches and can experience congestion and packet jitter at ultra-large node counts if network switches are improperly configured.
Are consumer GPUs (RTX 4090) suitable for commercial production inference?
For single-stream and small-batch inference on quantized 7B to 14B models (e.g., Llama 3 8B, Mistral 7B), the RTX 4090 offers incredible price-to-performance due to its 24GB GDDR6X VRAM and high memory clock. However, because RTX 4090 lacks NVLink interconnect and ECC memory error correction, it cannot scale efficiently across multi-GPU setups for 70B+ models or continuous multi-day training runs.
Can I migrate workloads between specialized AI clouds and AWS/GCP without code changes?
Yes. If you containerize your deep learning environment using Docker and standard PyTorch / NVIDIA CUDA containers (or utilize Kubernetes Helm charts), you can deploy identically across CoreWeave, RunPod, AWS, and GCP. Standardizing on S3-compatible object storage (e.g. Cloudflare R2, MinIO, or AWS S3) further decouples your data layer from compute providers.