Top 15 Cloud GPU Providers For 2025

In the age of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL), the need for powerful computing has never been higher. Data-driven insights are now essential for innovation, but achieving this requires advanced tools. Enter Cloud GPUs—modern computing heroes that provide incredible processing power without expensive upfront costs. These GPUs make supercomputing accessible to everyone, enabling breakthroughs and technological advancements. This guide explores top cloud providers, their unique features, and how they can help you succeed in AI, ML, and DL projects.

Best 15 Cloud GPU Providers

Runpod

• GPU Options: Runpod offers various GPUs like NVIDIA RTX 3090, RTX 4090, A100, and V100, including community options like RTX A5000, priced competitively for high-performance workloads such as machine learning, gaming, and rendering.
• Pricing: Recent price reductions make Runpod highly affordable. Serverless GPUs now cost 40% less, while secure cloud instances are down by 18%. Rates start as low as $0.22/hour for pay-as-you-go models, with bulk discounts and lower hourly rates for long-term use.
• Free Tier: Runpod does not provide a free tier, but the affordability compensates with flexible pay-per-use options.
• Unique Features: Highlights include a pay-by-the-minute model, intuitive user interface, and pre-configured environments for popular AI frameworks like TensorFlow and PyTorch. The platform supports scalability for short or extended workloads.
• Best For: Ideal for budget-conscious users and mid-sized machine learning or rendering tasks, offering performance without unnecessary costs.

Click here to explore Runpod GPUs

Hyperstack

• GPU Options: Hyperstack offers a range of NVIDIA GPUs, including the NVIDIA H100 PCIe, NVIDIA H100 SXM, NVIDIA A100, NVIDIA L40 and NVIDIA RTX A6000, optimised for AI training, inference and large-scale data processing. Users can also opt for CPU-only configurations when required. 
• Pricing: Hyperstack provides competitive pricing with flexible billing options, including on-demand and reserved options. Their platform also offers hibernation features, which means users can pause workloads and reduce costs when not in use.
• Free Tier: Users can sign up for free and explore their console. With affordable GPU options and flexible pay-per-use pricing, spinning up a test VM is quick and hassle-free on Hyperstack.
• Unique Features: Hyperstack offers zero oversubscription for dedicated resources without performance degradation. It supports high-speed networking up to 350 Gbps for low latency and optimised storage options for fast data transfer. Hyperstack Kubernetes simplifies AI/ML orchestration, while NUMA-aware scheduling and CPU pinning optimise resource allocation. Hyperstack also provides DevOps tools like the Terraform Provider and LLM Inference Toolkit for seamless infrastructure management. They also offer 24/7 human support, transparent pricing with no hidden fees and zero egress/ingress charges.
• Best For: Hyperstack is ideal for AI researchers, data scientists and enterprises requiring high-performance GPUs with dedicated resources. It is best suited for AI training, fine-tuning, inference, deep learning, and high-performance computing workloads that demand low latency, high-speed networking and flexible storage solutions.

Click here to explore Hyperstack GPU.

Google Cloud Platform (GCP)

• GPU Options: Google Cloud Platform now offers the latest NVIDIA L4 GPUs, making it the first cloud provider to integrate this powerful hardware. These GPUs, ideal for generative AI, AI video, and other intensive tasks, are available in G2 VMs. Alongside the L4, GCP continues to provide GPUs like K80, P4, T4, P100, and V100 for various machine learning and high-performance computing needs​.
• Pricing: Pricing for GPUs remains based on minute-by-minute billing. The Tesla T4 starts around $0.35 per hour, while the V100 costs closer to $2.48 per hour. Newer L4 GPUs start at $0.71 per hour, offering a highly efficient solution for AI workloads. Additionally, users benefit from sustained use discounts up to 30% and can save up to 57% with longer-term commitments. Spot VMs offer further cost savings​.
• Free Tier: GCP provides a 31-day extended free tier, allowing users to test various services, including GPU configurations, which is ideal for initial testing or smaller projects​.
• Unique Features: GCP’s seamless integration with Google’s AI tools, such as Vertex AI and BigQuery, significantly boosts its value for developers working on data-driven AI projects. The introduction of the L4 GPUs alongside these tools enhances AI training, deployment, and inference capabilities​.

Click here to access GCP GPUs.

Amazon Web Services (AWS)

• GPU Options: AWS offers a diverse selection of GPUs for various workloads. Current options include NVIDIA A10, A100, and H100 GPUs, tailored for tasks like machine learning and high-performance computing. Instances like p5.48xlarge feature up to 8 H100 GPUs with 80 GB each, providing substantial processing power.
• Pricing: AWS pricing depends on the GPU instance type and usage model. On-demand instances can cost around $1.21 per hour for A10 GPUs, $3.21 per hour for A100 GPUs, and $4.20 per hour for H100 GPUs. Reserved Instances and Spot Instances offer cost savings, with Spot Instances being approximately one-third the cost of on-demand rates, though with potential interruptions.
• Free Tier: AWS provides a ‘Free Tier’ for beginners, which includes certain amounts of compute time per month for up to 12 months.
• Unique Features: AWS stands out for its expansive ecosystem, offering services such as machine learning integrations (e.g., SageMaker), global low-latency infrastructure, and advanced autoscaling capabilities. Additional innovations like fractional GPUs and cost optimization tools improve resource utilization and budget management​.
• Best for: AWS is best suited for enterprises and developers seeking scalable, globally available solutions for machine learning, AI, and other compute-intensive workloads. It supports both experimental projects and large-scale deployments​.

Click here to explore AWS GPU.

Microsoft Azure

• GPU Options: Azure continues to provide a robust lineup, including NVIDIA Tesla T4, A100, V100, and M60 GPUs, as well as AMD’s Radeon Instinct MI25. The latest additions feature the NC A100 v4 series, offering up to 8 NVIDIA A100 Tensor Core GPUs, delivering advanced performance for machine learning and high-performance computing tasks. Azure also supports specialized GPUs for graphics-intensive workloads, such as the NVadsA10 v5 series with NVIDIA A10 GPUs.
• Pricing: The NC series with the Tesla K80 GPU has been retired as of 2023, but current offerings like the NCv3 series with Tesla V100 GPUs remain popular, priced around $3.06 per hour. The newer A100-powered VMs, such as the ND A100 v4 series, are priced higher but provide unparalleled performance for deep learning and AI tasks. Azure also offers cost-effective options through spot pricing and discounts for reserved instances. Updated pricing calculators are available to estimate costs accurately.
• Free Tier: Azure’s free tier now includes a 31-day trial for GPU-accelerated services, ideal for users exploring its capabilities. This is a slight extension compared to earlier free tier offerings.
• Unique Features: Azure maintains its edge with seamless integration into Microsoft’s ecosystem, including Office 365 and Azure Active Directory. New enhancements in Azure Machine Learning and AI frameworks streamline workflows for data scientists and developers, providing cutting-edge tools for training and deployment.
• Best For: With its evolving portfolio, Azure excels in handling AI, deep learning, and high-performance computing workloads. It is especially suited for industries requiring scalability and enterprise-grade reliability, such as scientific research and financial modeling

Click here to explore Microsoft Azure GPUs.

Vast.ai

• GPU Options: Vast.ai has expanded its offerings, adding support for ARM64 platforms and NVIDIA’s Grace Hopper superchips (GH200). These upgrades complement their high-end lineup, including RTX 3090s, A100s, and A6000s, providing more flexibility for demanding workloads in AI and scientific research.
• Pricing: The dynamic marketplace pricing continues, with GPUs like the RTX 3080 starting at $0.30/hour. High-performance models, such as A100s, now range from $1.50 to over $5/hour, depending on demand and location. Automated bidding ensures users secure competitive prices for long-term and large-scale projects.
• Free Tier: The free tier remains a helpful entry point for testing and small-scale projects, allowing users to explore the platform without financial commitment.
• Unique Features: Vast.ai now supports real-time benchmarking, enhanced template management, and better API functionality. Recent updates have improved user experience, from faster template search to added support for NVIDIA RAPIDS environments.
• Best For: Vast.ai continues to be a prime choice for those with large-scale AI, graphics, or data-intensive workloads, offering affordable scalability and cutting-edge GPU options.

Click here to access Vast.ai GPUs.

Paperspace

• GPU Options: Paperspace now features a robust selection of GPUs, including NVIDIA’s A100 in both 40 GB and 80 GB configurations. These GPUs are available in multi-GPU setups (up to 8-way configurations). Additionally, A4000 and A6000 GPUs have been rolled out for users in specific regions, broadening the platform’s versatility.
• Pricing: The A100 GPUs are priced at $3.09 per hour for the 40 GB variant and $3.18 for the 80 GB model. Multi-GPU configurations are scaled proportionally, such as $6.36 per hour for two A100 80 GB GPUs. Lower-cost options like the M4000 remain at $0.45 per hour. Monthly subscription tiers cater to varied user needs, with pricing starting at $8 for individuals and scaling up for teams.
• Free Tier: A limited free tier continues to be available, offering entry-level access for new users and small-scale projects.
• Unique Features: Paperspace has enhanced its offerings with advanced Ampere GPUs and expanded machine learning capabilities via Gradient. Improvements in networking and multi-GPU setups ensure faster and more efficient workflows, particularly for AI and deep learning.
• Best for: With its competitive pricing and a focus on accessibility, Paperspace remains a top choice for individuals, startups, and teams seeking a reliable and adaptable GPU cloud platform. The addition of Ampere GPUs and advanced configurations solidifies its position in the market.

Click here to access Paperspace GPUs.

Oracle Cloud Infrastructure (OCI)

• GPU Options: OCI now offers a broader range of GPU options, including the newly added AMD MI300X and NVIDIA L40S. These GPUs complement existing choices like the H100, A100, and A10, catering to diverse workloads from AI training to gaming and high-performance computing.
• Pricing: On-demand prices start at around $1.27/hour for NVIDIA P100 and can go up to $3.05/hour for the high-performance H100 GPUs. Reserved instances continue to provide up to 70% savings, and OCI’s flexible pricing model includes discounts on unused resources, enhancing cost efficiency.
• Free Tier: The free tier remains an excellent starting point for newcomers, offering limited but useful resources for small-scale projects or experimentation.
• Unique Features: OCI continues to emphasize flexibility with its bare-metal offerings and updates like better network interconnects, multi-GPU configurations, and NVMe storage, making it particularly suited for demanding AI and data-driven applications.
• Best for: OCI is a top choice for businesses needing high-performance GPUs for complex workloads, especially where cost-effectiveness and flexible configurations are essential.

Click here to access OCI GPUs.

IBM Cloud

• GPU Options: IBM Cloud offers an extensive lineup of GPUs, including NVIDIA V100, A100, H100, and the recently introduced L4, L40s, and AMD Instinct MI300X accelerators. These cater to diverse workloads, from AI training and inferencing to high-performance computing. This expansion underscores IBM’s commitment to enabling scalable solutions for AI and enterprise applications​.
• Pricing: The base pricing starts at approximately $2.50/hour for V100 GPUs, with customized pricing available for enterprise solutions. The introduction of AMD MI300X accelerators and NVIDIA H100 GPUs offers potential cost reductions by supporting larger models with fewer GPUs​.
• Free Tier: IBM continues to provide a limited free tier, encouraging users to explore its robust cloud ecosystem.
• Unique Features: IBM integrates tools like watsonx for AI model development, enhanced security protocols, and AI lifecycle management. The new hardware aligns with Red Hat OpenShift for containerized workloads, enabling rapid deployment of AI applications with enterprise-grade compliance and governance​.
• Best For: Ideal for businesses prioritizing hybrid cloud setups, regulated industry compliance, and cutting-edge AI capabilities, IBM Cloud delivers flexible and secure solutions for evolving workloads​

Click here to access IBM Cloud GPUs.

Jarvis Labs

• GPU Options: Jarvis Labs supports a wide range of GPUs including H100, A100, A6000, RTX 6000 Ada, and 5000 series GPUs. These are optimized for machine learning, deep learning, and high-performance computing workloads.
• Pricing: The RTX 6000 Ada is priced at approximately $1.14 per hour. Flexible pricing models include hourly and monthly plans, suitable for diverse project requirements. On-demand H100 GPU options have been introduced for scalability and advanced tasks​.
• Free Tier: No free tier is available, but the robust features and developer-friendly environment justify the cost.
• Unique Features: Jarvis Labs provides developer-centric tools, personalized consultations, and resources designed specifically for machine learning. Their infrastructure emphasizes optimizing workflows and resource efficiency​.
• Best For: Ideal for developers, small businesses, and individuals seeking advanced computing capabilities for AI, machine learning, and related fields.

Click here to access Jarvis Labs GPUs.

CoreWeave

• GPU Options: CoreWeave provides access to over 11 NVIDIA GPU models. Available options include the A100 NVLINK , H100 PCIe , HGX H100 , and more budget-friendly models like the RTX A5000  and Quadro RTX 4000 . These GPUs support a variety of VRAM capacities, from 8GB to 80GB, to cater to diverse workloads.
• Pricing: Pricing is competitive and based on GPU selection. High-performance GPUs, such as the HGX H100, are priced at $4.76 per hour, while economical options like the Quadro RTX 4000 are $0.24 per hour.
• Free Tier: CoreWeave does not offer a free tier, but its pricing remains attractive for users with large-scale needs.
• Unique Features: The platform’s Kubernetes-native design allows rapid scaling and supports high-speed networking. CoreWeave eliminates charges for many extras, such as data egress, enhancing cost efficiency.
• Best for: Designed for AI training, machine learning, and high-performance computing, with robust infrastructure tailored for demanding workloads.

Click here to access CoreWeave GPUs.

Lambda Labs

• GPU Options: Offers a variety of NVIDIA GPUs, including RTX 6000, A100, and V100, optimized for high-performance deep learning and AI workloads.
• Pricing: Transparent pricing model with hourly rates depending on GPU type. For example, an A100 instance starts at approximately $1.10 per hour, while RTX 6000 options are more affordable.
• Free Tier: No free tier, but its pricing is competitive compared to major cloud providers.
• Unique Features: Pre-configured environments tailored for deep learning workflows, offering plug-and-play simplicity. Lambda Labs also provides on-premises GPU hardware, ensuring flexibility for businesses scaling across both cloud and local environments.
• Best for: Ideal for machine learning, AI model training, inferencing, and research requiring consistent performance and efficient scaling.

Genesis Cloud

• GPU Options: Provides access to NVIDIA GPUs such as the A100, V100, and RTX 3080, suitable for high-performance AI and rendering workloads.
• Pricing: Offers competitive hourly rates designed for flexibility. For instance, the RTX 3080 starts at around $0.49 per hour, and higher-end options like the A100 are priced approximately $2.40 per hour. Discounts available for longer-term usage.
• Free Tier: No free tier, but cost efficiency is a hallmark, with pricing tailored to suit both individuals and enterprises.
• Unique Features: Known for eco-friendly data centers powered by renewable energy, making it a sustainable choice. Genesis Cloud also offers customizable configurations for varied workload requirements, ensuring maximum resource utilization.
• Best for: Perfect for AI training, machine learning, 3D rendering, and workloads needing scalability and environmental sustainability.

Click here to access Genesis cloud

LeaderGPU

• GPU Options: A wide range of NVIDIA GPUs, including RTX 4090, A100, V100, and Tesla GPUs, designed for demanding tasks like AI model training and rendering.
• Pricing: Hourly rates vary by GPU model, starting from around $0.45 per hour for lower-end GPUs like the Tesla P100, up to $2.50 per hour for premium models such as the A100. Discounts are available for longer-term commitments.
• Free Tier: No free tier, but the competitive pricing structure appeals to startups and researchers needing high-performance GPUs without high upfront costs.
• Unique Features: Offers dedicated GPU servers for maximum performance and reliability. Users can customize configurations, ensuring optimal resource allocation for specific workloads. Global data centers provide low-latency options.
• Best for: AI training, deep learning, neural network development, and graphics rendering for industries like gaming, animation, and simulation.

Click here to access LeaderGPU

iRender

• GPU Options: Provides access to high-performance GPUs, including NVIDIA RTX 3090, RTX 4090, and Quadro RTX 6000, optimized for rendering and AI workloads.
• Pricing: Pricing starts at $3.80 per hour for RTX 3090 instances and scales based on GPU power. Offers flexible plans, including hourly, daily, and monthly options, which are cost-effective for long-term projects.
• Free Tier: No free tier, but a pay-as-you-go model and competitive rates make it accessible for both individuals and businesses.
• Unique Features: Tailored for creative professionals with pre-installed software support for popular rendering engines like Blender, Cinema 4D, and Octane Render. Users can access multiple GPUs in parallel for accelerated performance. iRender also supports remote desktop workflows for seamless project execution.
• Best for: Ideal for 3D rendering, architectural visualization, VFX, and AI/ML model training, especially for professionals needing high GPU performance with software flexibility.

Click here to access iRender

GPU Eater

• GPU Options: Offers a range of NVIDIA GPUs, including RTX 3090, A100, V100, and T4, catering to both budget-conscious users and high-performance workloads.
• Pricing: Hourly rates vary by GPU type, starting from around $0.20 per hour for entry-level options like the T4 and up to $2.00 per hour for premium GPUs like the A100. Transparent pricing with no hidden fees.
• Free Tier: No free tier, but low entry-level costs make it a viable option for individuals and smaller teams.
• Unique Features: GPU Eater provides a streamlined user interface for quickly deploying GPU instances. Known for its focus on budget-friendly GPU access, it is especially suited for small-scale AI/ML tasks and rendering. Flexible plans allow users to scale resources based on workload.
• Best for: AI model training, deep learning, and graphics rendering for freelancers, startups, and small-scale projects needing cost-effective GPU solutions.

Click here to access GPU Eater

Conclusion

Choosing the right cloud GPU provider is a pivotal step in advancing your AI, machine learning, or deep learning initiatives. To make the best decision, carefully assess your project’s specific needs, your technical expertise, and your budget limitations. Look beyond cost alone, considering unique features and the quality of service each provider offers. This guide is designed to help you make an informed decision, empowering you to fully harness the potential of cloud GPUs for your AI, ML, and DL endeavors.

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Himanshi Singh

I’m a data lover who enjoys finding hidden patterns and turning them into useful insights. As the Manager - Content and Growth at Analytics Vidhya, I help data enthusiasts learn, share, and grow together. 

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