Looking for the best cloud GPU provider for your AI or ML workloads? With a growing number of platforms offering powerful GPUs for training, fine-tuning and inference, choosing the right one can be overwhelming. In this blog, we’ve handpicked the top 10 cloud GPU providers based on performance, pricing, features and flexibility. Whether you need NVIDIA A100s for large-scale models or budget-friendly options for smaller projects, we break down what each provider offers, so you can compare and choose the best fit for your needs.
Let's explore the top 10 cloud GPU providers in 2025.
| Provider | GPU Offerings | Starting Price per Hour | |
|---|---|---|---|
|
1 |
Hyperstack |
NVIDIA H100, NVIDIA A100, NVIDIA L40, NVIDIA RTX A6000/A40 |
NVIDIA A100: $ 1.35 per Hour NVIDIA H100 PCIe: $ 1.90 per Hour NVIDIA H100 SXM: $2.40 per Hour NVIDIA L40: $ 1.00 per Hour |
|
2 |
Lambda Labs |
NVIDIA H100 (PCIe), H200 |
H100 PCIe from $2.49/hour |
|
3 |
Paperspace (DigitalOcean) |
NVIDIA H100, RTX 6000, A6000 |
H100 at $2.24; A100 at $1.15 |
|
4 |
Nebius |
NVIDIA H100, A100, L40 with InfiniBand |
H100 from $2.00/hour |
|
5 |
Runpod |
NVIDIA RTX A4000, A100 PCIe, MI300X |
A4000 from $0.17; A100 PCIe $1.19; MI300X $3.49 |
|
6 |
Vast.ai |
Varied GPUs via real-time bidding |
Prices vary based on per-GPU bidding |
|
7 |
Genesis Cloud |
NVIDIA HGX H100, GB200 NVL72 |
HGX H100 from $2.00/hour |
|
8 |
Vultr |
NVIDIA GH200, H100, A100, L40 |
L40 at $1.671; H100 at $2.30 |
|
9 |
Gcore |
Various GPUs; pricing custom per requirements |
Custom pricing |
|
10 |
OVHcloud |
NVIDIA A100, NVIDIA V100 |
$2.99 per hour for NVIDIA H100 GPUs |
Here is a list of the best cloud GPU providers in 2025:
Hyperstack by NexGen Cloud offers a real cloud environment where you can build with AI and deploy market-ready products faster. With instant access to powerful GPUs like the NVIDIA H100, A100, L40 and RTX A6000/A40 and a developer-friendly dashboard, Hyperstack is designed to support every stage of your AI and ML workflow.
Key Features
NVLink support for A100 and H100 GPUs for scalable training and inference
High-speed networking up to 350Gbps for low-latency and high-throughput workloads
VM Hibernation to pause unused workloads and control costs
1-click deployment for fast and easy project setup
NVMe block storage for enhanced data access and performance
Green infrastructure, powered by 100% renewable energy
AI Studio: End-to-end Gen AI platform for LLM fine-tuning, evaluation and deployment
Pricing
Pay-as-you-go with minute-by-minute billing
Reservation options available for long-term savings
|
GPU Name |
On-Demand Price (hour) |
|
$1.35 |
|
|
$1.60 |
|
|
$1.90 |
|
|
$2.40 |
|
|
$3.50 |
|
|
$1.00 |
|
|
$0.50 |
Ideal Use Cases
AI training, fine-tuning & inference
Machine learning at scale
Lambda Labs provides high-end GPU instances like H100 and H200 with robust infrastructure tailored for deep learning and enterprise AI workflows.
Key Features
Lambda Stack with preinstalled ML libraries
One-click GPU cluster setup
Quantum-2 InfiniBand networking for low latency
Pricing
H100 PCIe: $2.49/hour
Ideal Use Cases
Lambda Labs is ideal for LLM training, enterprise-grade inference,and teams seeking scalable, preconfigured AI environments.
Paperspace delivers scalable GPU cloud infrastructure with fast-start templates and version control, making it ideal for dev teams building and deploying AI applications.
Key Features
Pre-configured templates
Auto versioning and experiment reproducibility
Flexible scaling and multi-GPU support
Pricing
H100: $2.24/hour
A100: $1.15/hour
Ideal Use Cases
Paperspace is ideal for model development, MLOps pipelines, experimentation, and scalable model deployment.
Nebius offers high-performance GPU compute with InfiniBand and advanced automation for developers and enterprises looking to scale AI infrastructure quickly.
Key Features
API, Terraform, and CLI access
Elastic scaling with custom configurations
InfiniBand-enabled networking
Pricing
H100: From $2.00/hour
Ideal Use Cases
Nebius is ideal for scalable AI/ML workloads, inference at scale, and multi-node distributed training.
Runpod enables rapid deployment of GPU resources with a focus on developer speed, flexibility, and serverless AI environments.
Key Features
Serverless GPU compute
Real-time analytics and logs
Support for custom containers and volume mounting
Pricing
A4000: $0.17/hour
A100 PCIe: $1.19/hour
MI300X: $3.49/hour
Ideal Use Cases
Runpod is ideal for real-time model iteration, containerised AI workflows, and serverless LLM deployments.
Vast.ai is a decentralised GPU marketplace offering cost-effective compute through real-time bidding, ideal for budget-conscious developers.
Key Features
Auction-based GPU pricing
Instant deployment via Docker
Simple web interface and CLI
Pricing
Variable, based on bidding
Ideal Use Cases
Vast.ai is ideal for low-cost model training, experiment-heavy projects, and developers needing flexibility in budget.
Genesis Cloud provides EU-sovereign infrastructure and powerful GPU clusters, including HGX H100 and GB200 NVL72, optimised for GenAI and LLM workloads.
Key Features
EU-compliant, sovereign cloud infrastructure
GB200 NVL72 support for next-gen AI compute
Efficient multi-node training at scale
Pricing
HGX H100: $2.00/hour
Ideal Use Cases
Genesis Cloud is ideal for training LLMs and running Gen AI platforms.
Vultr delivers global access to high-performance GPUs through its network of 32 data centres, enabling distributed AI training and inference workloads.
Key Features
Broad data centre coverage
On-demand and reserved GPU instances
Competitive GPU pricing
Pricing
L40: $1.671/hour
H100: $2.30/hour
Ideal Use Cases
Vultr is ideal for distributed deep learning, inference at edge locations, and multi-region model deployment.
Gcore offers enterprise-grade GPU solutions with a strong global presence, CDNs, and infrastructure security for regulated workloads.
Key Features
180+ CDN locations
Enterprise-level DDoS protection
Infrastructure planning for custom AI needs
Pricing
Custom
Ideal Use Cases
Gcore is ideal for enterprise AI, edge inference with CDN integration, and secure distributed AI pipelines.
OVHcloud offers hybrid and on-premises-ready GPU solutions with ISO and SOC compliance, ideal for regulated industries and large organisations.
Key Features
Hybrid integration: on-prem + cloud
ISO/SOC-certified environments
Dedicated high-performance GPU nodes
Pricing
H100: $2.99/hour
Ideal Use Cases
OVHcloud is ideal for AI in regulated sectors like healthcare or finance, hybrid cloud deployments and long-term enterprise projects.
Here are the best cloud GPU providers for AI in 2025:
Hyperstack is a high-performance GPU cloud platform tailored for AI development. It offers NVIDIA H100, A100, and L40 GPUs with NVLink support and high-speed networking up to 350 Gbps. Features like VM hibernation, minute-level billing, and real-time GPU availability help users optimise both performance and cost. Hyperstack also includes AI Studio—a no-code/low-code environment for managing GenAI workflows end-to-end.
Why it’s ideal for AI:
Built for AI-specific tasks like training, fine-tuning and inference
NVLink options in H100 and A100 GPUs
Minute-level billing and hibernation reduce idle cost
AI Studio simplifies model prototyping and deployment
Real-time GPU availability improves planning for dynamic workloads
Lambda Labs delivers enterprise-level GPU instances using NVIDIA H100 and H200, combined with Quantum-2 InfiniBand networking for ultra-low latency. Its Lambda Stack includes pre-installed ML frameworks, making it easier to deploy AI workflows. Users can launch 1-click clusters and choose between on-demand or reserved pricing models.
Why it’s ideal for AI:
H100 and H200 GPUs support large model training and inference
InfiniBand networking ensures fast, low-latency communication
Pre-configured Lambda Stack accelerates development setup
Cluster deployment supports scale-out workloads
Ideal for enterprise-grade AI applications and research
Paperspace, now part of DigitalOcean, is a developer-focused GPU platform offering H100, A6000, and RTX 6000 GPUs. It includes pre-configured environments, version control, and collaboration tools for streamlined AI and ML workflows. Flexible pricing supports short-term and long-term projects.
Why it’s ideal for AI:
Pre-built environments for fast prototyping and reproducibility
Suitable for full ML lifecycle—training, testing, and deployment
Affordable for startups and individuals experimenting with AI
Built-in collaboration tools support team workflows
Easy-to-use UI lowers the entry barrier for new AI developers
Nebius offers scalable GPU infrastructure powered by NVIDIA H100, A100, and L40, along with InfiniBand networking. It provides API, CLI, and Terraform-based control for complete customisation, and supports both hourly and reserved billing.
Why it’s ideal for AI:
InfiniBand enables high-throughput, multi-node model training
Full infrastructure control via API, CLI, and Terraform
Ideal for DevOps-integrated AI workflows
Flexible pricing adapts to prototyping and production phases
Supports large-scale ML and AI pipeline deployment
Genesis Cloud is a privacy-first AI infrastructure provider offering top-tier GPUs like HGX H100 and GB200 NVL72 in GDPR-compliant EU data centres. It's designed for high-scale LLM training and GenAI workloads, with multi-node support for distributed compute.
Why it’s ideal for AI:
Supports high-volume training with GB200 and HGX H100 setups
Delivers up to 35x performance boost on large models
Multi-node configurations enable horizontal scaling
Compliant with EU data protection regulations (GDPR)
Best suited for enterprise AI with strong data privacy needs
Here are the best cloud GPU providers for deep learning in 2025:
Hyperstack delivers high-performance cloud infrastructure for deep learning with fast networking and NVLink-powered GPUs, ideal for large-scale training and multi-GPU setups.
NVLink-enabled H100 & A100
350 Gbps high-speed networking
NVMe block storage
Runpod enables rapid deployment of deep learning containers with low-latency access to high-end GPUs, ideal for experimentation and real-time model updates.
Instant GPU launch
Auto-scaling for DL pipelines
Usage analytics for tuning
Vast.ai offers budget-friendly deep learning compute with real-time bidding, enabling low-cost experimentation on powerful GPUs.
A100 & V100 support
Docker-based training setup
Interruptible pricing options
Vultr supports scalable, global deep learning deployments with high-performance GPUs in 30+ regions, ideal for distributed model training.
GH200, H100, A100 GPUs
Global data centres
Regional scalability
OVHcloud is built for secure deep learning in regulated industries, with certified infrastructure and dedicated high-end GPUs.
ISO/SOC-certified GPU servers
H100 & A100 options
Hybrid cloud/on-prem support
Choosing the right cloud GPU server providers depends on your needs, budget, and performance requirements. Each cloud provider offers distinct advantages, whether cost-effective solutions for small-scale projects or powerful GPUs designed for AI and ML workloads. Our balanced approach to providing advanced GPUs with high-performing features ensures you deploy your workloads at their level best.
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A cloud GPU provider is a service that offers access to high-performance GPUs located in the cloud. These processors are engineered to manage complex graphical and parallel processing tasks, including rendering, AI, and machine learning workloads.
Yes, GPU cloud services are well-suited for training and deploying large language models. Providers like Hyperstack offer high-performance GPUs such as the NVIDIA A100, NVIDIA H100 SXM and NVIDIA H100 PCIe, which are ideal for handling the compute and memory demands of LLMs. For more advanced large models, multi-GPU setups or distributed computing support is essential to ensure scalability and performance. On Hyperstack, you can choose NVIDIA H100 with NVLink and NVIDIA A100 with NVLink for seamless scaling.
The best cloud GPU provider for AI depends on your specific workload, budget, and location requirements. Providers like Hyperstack, Lambda Labs, and Runpod offer access to high-performance GPUs such as the NVIDIA A100 and H100 series, which are widely used for training and deploying AI models.
Several cloud platforms offer dedicated GPU-powered virtual machines for tasks like AI training, deep learning and inference. Popular options include Hyperstack, Lambda Labs, Vultr, and Runpod, each offering different GPU models and configurations.
Cloud GPUs for demanding tasks such as large-scale training, scientific computing, or data analysis can be rented from platforms like Hyperstack, Vast.ai or Genesis Cloud, which provide access to a variety of GPU types at different performance and price points.
Most reputable cloud GPU providers implement industry-standard security measures such as data encryption, access controls, and compliance with certifications like ISO 27001 or SOC 2 to ensure the protection of user data and workloads.
Deep learning workloads benefit from providers that offer a range of GPU models, fast storage, and networking options. Platforms such as Hyperstack are commonly used depending on workload needs.
The cost of a cloud GPU can differ greatly based on the GPU model, the cloud provider and the instance setup, but typically begins at $0.95 per hour for the NVIDIA A100 GPU on Hyperstack.
GPUs like the NVIDIA A100 and NVIDIA H100 are widely regarded as the most suitable for LLM workloads due to their high memory bandwidth, tensor performance, and scalability. The right choice depends on model size, training duration, and parallelisation needs.