cloud-gpu-servers-services-providers

The Top Cloud GPUs Providers for AI, ML & Deep Learning

Your company’s GPU computing strategy is essential whether you engage in 3D visualization, machine learning, AI, or any other form of intensive computing.

There was a time when businesses had to wait for long periods of time while deep learning models were being trained and processed. Because it was time-consuming, costly, and created space and organization problems, it reduced their output.

This problem has been resolved in the most recent GPU designs. Because of their high parallel processing efficiency, they are well-suited for handling large calculations and speeding up the training of your AI models.

When it comes to deep learning, Cloud GPUs can speed up the training of neural networks by a factor of 250 compared to CPUs, and the latest generation of cloud GPUs is reshaping data science and other emerging technologies by delivering even greater performance at a lower cost and with the added benefits of easy scalability and rapid deployment.

This article will provide an overview of cloud GPUs, their applications in artificial intelligence, machine learning, and deep learning, and the top cloud GPU deployment platforms available today.

1. Liquid Web Cloud GPU

liquidwebcloudgpu

Liquid Web, a prominent provider of managed hosting and cloud solutions, has recently introduced its GPU hosting services to meet the escalating demands of high-performance computing (HPC) applications. This offering is tailored for tasks such as artificial intelligence (AI), machine learning (ML), and rendering workloads, providing businesses with the computational power necessary to handle data-intensive operations efficiently.

Overview of Liquid Web’s GPU Hosting Services

liquidweb2

Liquid Web’s Cloud GPU Hosting Services are designed to deliver exceptional performance for resource-intensive applications. By integrating NVIDIA’s advanced GPUs, including models like the L4 Ada 24GB, L40S Ada 48GB, and H100 NVL 94GB, these services cater to a wide range of computational needs. Each server configuration is optimized to ensure seamless operation for AI/ML tasks, large-scale data processing, and complex rendering projects.

Key Features

High-Performance Hardware: The servers are equipped with powerful NVIDIA GPUs and AMD EPYC CPUs, ensuring robust processing capabilities. For instance, the NVIDIA L4 Ada 24GB model comes with dual AMD EPYC 9124 CPUs, offering 32 cores and 64 threads at 3.0 GHz (Turbo 3.7 GHz), 128 GB DDR5 memory, and 1.92 TB NVMe RAID-1 storage.
Optimized Software Stack: The GPU stack includes the latest NVIDIA drivers, CUDA Toolkit, cuDNN for deep learning, and Docker with NVIDIA Container Toolkit, facilitating efficient deployment and management of AI/ML workloads.
Scalability: Liquid Web offers a range of server configurations to meet varying performance requirements, allowing businesses to scale resources as their computational needs evolve.
Compliance and Security: The hosting services adhere to strict compliance standards, including PCI and SOC compliance, and undergo HIPAA audits, ensuring the security and integrity of sensitive data.

Pricing

Liquid Web provides several GPU server configurations with corresponding pricing:

NVIDIA L4 Ada 24GB: Priced at $880 per month, this configuration includes dual AMD EPYC 9124 CPUs, 128 GB DDR5 memory, and 1.92 TB NVMe RAID-1 storage.
NVIDIA L40S Ada 48GB: Available for $1,580 per month, it features dual AMD EPYC 9124 CPUs, 256 GB DDR5 memory, and 3.84 TB NVMe RAID-1 storage.
NVIDIA H100 NVL 94GB: This premium option is offered at $3,780 per month, comprising dual AMD EPYC 9254 CPUs, 256 GB DDR5 memory, and 3.84 TB NVMe RAID-1 storage.
Dual NVIDIA H100 NVL 94GB: For intensive computational needs, this configuration is priced at $6,460 per month and includes dual AMD EPYC 9254 CPUs, 768 GB DDR5 memory, and 7.68 TB NVMe RAID-1 storage.

Due to high demand, delivery times for GPU servers range from 24 hours to two weeks.

Pros and Cons

Pros:

High Performance: Utilization of advanced NVIDIA GPUs ensures exceptional processing speeds suitable for AI/ML and rendering tasks.
Comprehensive Software Stack: Pre-configured with essential tools and frameworks, facilitating efficient deployment of AI/ML workloads.
Scalability: Flexible configurations allow businesses to adjust resources based on their evolving needs.
Compliance: Adherence to industry standards ensures data security and regulatory compliance.

Cons:

Cost: The premium hardware and services come at a higher price point, which may be a consideration for smaller businesses.
Availability: High demand may lead to longer delivery times for certain configurations.

Use Cases

AI and Machine Learning: Accelerating training and inference of deep learning models, deploying real-time AI services, and hosting pre-trained large language models.
Data Analytics: Speeding up big data processing and real-time analytics using GPU-optimized frameworks.
Content Creation: Handling large-scale rendering and video editing tasks efficiently.
Healthcare and Medical Imaging: Enhancing diagnostics, image analysis, and simulations requiring high computational power.
High-Performance Computing: Supporting scientific research, climate modeling, genomics, and complex engineering simulations.

Conclusion

Liquid Web’s GPU hosting services offer a robust solution for businesses seeking high-performance computing capabilities. With advanced hardware configurations, a comprehensive software stack, and adherence to compliance standards, these services are well-suited for a variety of data-intensive applications.

While the cost may be a consideration for some, the performance and scalability provided make it a compelling option for organizations aiming to leverage GPU-accelerated computing.

#2. Atlantic.net

Atlantic.net breaks performance barriers with enterprise-class GPU cloud infrastructure, delivering NVIDIA L40S and H100 NVL accelerators with unmatched flexibility and regulatory compliance

Harness unprecedented computational power with Atlantic.net’s enterprise-focused GPU cloud platform, purpose-built for next-generation AI development, scientific research, and analytics workloads.

atlantic.net gpu cloud solutions

In the rapidly evolving landscape of accelerated computing, Atlantic.net has established itself as a key player by introducing enterprise-grade GPU cloud solutions targeting the most computationally demanding applications in artificial intelligence, deep learning, and data science. This technical evaluation examines Atlantic.net’s GPU product portfolio, architectural design, performance metrics, implementation flexibility, and industry-specific applications to provide organizations with a comprehensive understanding of these accelerated computing resources.

Strategic Market Positioning and Technical Foundation

Joining the elite ranks of NVIDIA’s Partner Network Cloud Service Partner (NCP) program in May 2024, Atlantic.net has leveraged its 30-year heritage in cloud infrastructure to create a differentiated GPU offering. Unlike hyperscale providers who treat GPU instances as simply another SKU in their vast service catalogs, Atlantic.net has developed a purpose-built environment specifically optimized for GPU workloads.

The company’s technical approach emphasizes architectural purity—delivering true bare-metal GPU resources rather than the virtualized environments common among competitors. This philosophy eliminates the hypervisor overhead that typically reduces computational efficiency in virtualized GPU deployments, ensuring customers receive maximum performance from each accelerator. Their implementation of NVIDIA NVLink technology further enhances this advantage by enabling sophisticated resource allocation and inter-GPU communication at near-native speeds.

Atlantic.net’s infrastructure spans a distributed network of eight strategically positioned data centers across North America (New York, Dallas, Ashburn, Orlando), Europe (London), Asia Pacific (Singapore), and additional locations, creating a global footprint that addresses latency concerns and regional data sovereignty requirements. The company’s partnership with Supermicro enables them to deploy high-performance server platforms specifically engineered for GPU acceleration workloads.

Technical Architecture and Accelerator Specifications

The Atlantic.net GPU portfolio centers around two flagship NVIDIA accelerator platforms, each targeting different performance tiers and workload profiles:

NVIDIA L40S Platform: Balanced Performance Architecture

The L40S represents NVIDIA’s versatile mainstream accelerator based on the Ada Lovelace architecture, balancing computational density with cost-effectiveness for a wide range of AI, visualization, and computational workloads.

Core Technical Specifications:

Pricing Structure: Base rate of $1.57 per hour with on-demand billing
Contract Options: Significant cost optimization with 12-month (approximately 20% savings) and 36-month (approximately 35% savings) commitment terms
Graphics Processing: Ada Lovelace architecture with 18,176 CUDA processing cores
Memory Subsystem: 48GB GDDR6 with ECC protection and 864 GB/s bandwidth
AI Acceleration: 568 specialized Tensor cores for matrix operations
Visualization Acceleration: 1,420 dedicated RT cores for ray-tracing operations
Numerical Precision: Full spectrum FP8/FP16/FP32/FP64 computation support
AI Optimization: Native TensorFloat-32 (TF32) acceleration for deep learning frameworks
System Interface: PCIe 4.0 x16 connectivity with 64 GB/s bi-directional bandwidth
Power Envelope: Optimized thermal and electrical characteristics for data center environments
Host System Configurations:
- CPU Architecture: Latest-generation x86-64 processing options from Intel and AMD
- Memory Capacity: Configurable system RAM from 32GB to 768GB DDR5
- Storage Architecture: NVMe primary storage with enterprise SSD options
- Software Environment: Broad OS support including major Linux distributions and Windows Server platforms

Performance Characteristics and Workload Affinities:

AI Model Development: Complete pipeline acceleration from data preparation through deployment
Machine Learning Operations: Enhanced efficiency ratio for training and inference tasks
Deep Learning Frameworks: Optimized execution paths for TensorFlow, PyTorch, and other frameworks
Visual Computing: Superior performance for rendering, video encoding, and visualization tasks
Software Ecosystem: Pre-optimized environments for CUDA, cuDNN, and AI frameworks

NVIDIA H100 NVL Platform: Maximum Performance Architecture

The H100 NVL represents NVIDIA’s flagship data center GPU based on the Hopper architecture, designed specifically for the most demanding AI training, inference, and high-performance computing workloads.

Core Technical Specifications:

Pricing Structure: Base rate of $3.94 per hour with on-demand billing
Contract Options: Significant cost optimization with 12-month and 36-month commitment terms
Graphics Processing: Hopper architecture with 14,592 CUDA processing cores
Memory Subsystem: 94GB HBM3 with 3.9 TB/s bandwidth
AI Acceleration: 456 fourth-generation Tensor cores
Neural Network Optimization: Dedicated Transformer Engine for large language model operations
Inter-GPU Communication: NVLink bridges with up to 900 GB/s device-to-device bandwidth
System Interface: PCIe 5.0 with 128 GB/s bi-directional bandwidth
Computational Efficiency: Superior performance-per-watt metrics
Host System Configurations:
- CPU Architecture: High-core-count server processors (AMD EPYC/Intel Xeon)
- Memory Capacity: Scaling to 1.5TB DDR5 system memory
- Storage Architecture: High-performance NVMe arrays with RAID protection
- Software Environment: Optimized Linux and Windows server platforms

Performance Characteristics and Workload Affinities:

Large Language Models: Specialized architecture for transformer-based AI systems
AI Research Computing: Enables experimentation with cutting-edge model architectures
Scientific Simulation: Superior performance for mathematical modeling applications
Large Dataset Processing: Efficient handling of terabyte-scale training datasets
Multi-Tenant Processing: Optional workload isolation through Multi-Instance GPU technology

Deployment Architecture and Resource Customization

Atlantic.net’s platform offers extensive configuration flexibility across both accelerator families:

Resource Allocation Methodologies:
- Partial GPU Provisioning: Cost-optimized model providing fractional GPU resources
- Dedicated GPU Assignment: Maximum performance through exclusive hardware access
- Multi-GPU Environments: Scaled deployments supporting up to 8 coordinated accelerators
System Resource Customization:
- Compute Allocation: Tailored vCPU provisioning based on application requirements
- Memory Sizing: Optimized system RAM allocation for different workload characteristics
- Storage Architecture:
  - Performance-optimized NVMe for I/O-intensive applications
  - Enterprise-grade SSD for general workloads
  - Expandable capacity for data-heavy processing requirements
- Network Configuration: High-throughput, low-latency connectivity options
Commercial Models:
- Consumption-Based Pricing: Hourly billing starting at $1.57/hour (L40S) and $3.94/hour (H100 NVL)
- Intermediate Commitments: Reduced rates with 12-month service agreements
- Long-Term Allocation: Maximum cost efficiency with 36-month contracts
- Financial Terms:
  - Monthly billing cap (after 730 hours)
  - Transparent usage accounting
  - All-inclusive pricing without hidden fees

Platform Architecture and Operational Capabilities

Infrastructure Design and Performance Optimization

Native Hardware Access: Atlantic.net’s architectural approach prioritizes direct GPU access without virtualization layers that typically reduce performance, delivering bare-metal accelerator performance.
Dynamic Resource Orchestration: The platform incorporates sophisticated allocation mechanisms supporting both fractional and dedicated GPU provisioning through NVIDIA NVLink technology, optimized for different VRAM requirements and workload patterns.
Accelerator Clustering: The infrastructure supports high-density GPU environments with optimized inter-device communication channels, enabling efficient parallel processing across multiple coordinated accelerators.
Network Foundation: The underlying network architecture provides high-bandwidth, low-latency connectivity with up to 100 Gbps throughput, eliminating data transfer bottlenecks between system components.
Geographic Distribution: The platform’s multi-region deployment across three continents addresses both performance requirements (latency minimization) and compliance needs (data residency).
Enterprise Storage Systems: The storage infrastructure incorporates enterprise-grade solutions with RAID protection, utilizing NVMe technology for maximum throughput with configurations scaling to 7.68 TB capacity.

Administrative Framework and Operational Efficiency

Provisioning Velocity: The platform enables rapid resource deployment with standard instances available within minutes and pre-configured environments deployable in under 30 seconds, supporting agile development methodologies.
Management Interface: A comprehensive control interface facilitates efficient resource administration through an intuitive web console featuring detailed monitoring and analytics capabilities.
System Administration: The environment provides unrestricted administrative access (root/administrator) to GPU servers, enabling custom software deployment, driver optimization, and complete environment customization.
Automation Capabilities: Extensive API functionality enables programmatic resource management, supporting integration with DevOps workflows, CI/CD pipelines, and orchestration platforms.
Access Control Framework: The security model implements comprehensive authentication mechanisms including SSH key management, multi-factor authentication, and role-based access controls.

Security Architecture and Compliance Framework

Enterprise Security Implementation: The platform incorporates multi-layered security controls including DDoS mitigation, next-generation firewall protection, and advanced intrusion detection systems.
Regulatory Certification: Atlantic.net maintains comprehensive compliance with HIPAA, PCI-DSS, SOC 2/3, and GDPR requirements, validated through independent third-party audits and certifications.
Data Protection Methodology: The security framework includes comprehensive encryption for data at rest and in transit, with advanced key management capabilities for sensitive workloads in regulated industries.
Physical Security Controls: All data center facilities implement enterprise-grade physical protection including biometric access controls, continuous video monitoring, and multi-layered entry systems.

Reliability Engineering and Technical Support

Service Level Commitment: Atlantic.net provides one of the industry’s most aggressive availability guarantees with a 100% uptime SLA, ensuring continuous access to GPU resources for production workloads.
Resilient Infrastructure: The underlying platform incorporates redundant power distribution, cooling systems, and network connectivity to eliminate single points of failure.
Technical Support Operations: The company maintains 24x7x365 US-based technical support with GPU specialization, ensuring immediate access to expert assistance for complex accelerated computing issues.
Enterprise Account Management: Business clients receive dedicated account management resources providing personalized support and strategic guidance for GPU infrastructure planning.

Development Ecosystem and AI Framework Support

Pre-configured Environments: The platform offers ready-to-deploy GPU servers with optimized AI and ML development stacks, eliminating complex environment setup processes.
CUDA Development Support: Comprehensive support for NVIDIA’s CUDA platform enables efficient development of GPU-accelerated applications leveraging parallel processing architectures.
Deep Learning Optimization: The environment includes support for essential GPU-accelerated libraries like cuDNN, optimized for maximum neural network performance.
Containerization Integration: Seamless compatibility with Docker and NVIDIA Container Toolkit simplifies deployment of GPU-accelerated applications across development and production environments.
Model Repository Access: Direct integration with NVIDIA’s NGC catalog provides access to pre-trained models, optimized frameworks, and development tools.
Environment Standardization: Support for custom machine images enables consistent development environments across distributed teams and projects.

Vertical Market Applications and Implementation Scenarios

Atlantic.net’s GPU infrastructure delivers exceptional value across diverse sectors. The following sections explore specific implementation scenarios demonstrating how various industries leverage their accelerated computing platform:

Artificial Intelligence and Computational Learning

Foundation Model Development and Deployment:
- Customize and fine-tune large language models and transformer architectures
- Deploy production-grade inference endpoints with optimized scaling
- Enhance response performance through hardware-accelerated inference
- Implementation example: AI research organizations can leverage the H100 NVL’s extensive 94GB memory to accommodate larger model architectures than typically possible with standard cloud offerings
Computer Vision Engineering:
- Develop manufacturing quality control systems using advanced object detection
- Create sophisticated security applications with biometric capabilities
- Build medical diagnostic tools with radiological analysis capabilities
- Process real-time video from infrastructure monitoring systems
- Technical advantage: The L40S GPU’s specialized architecture provides exceptional performance for parallel image processing operations
Autonomous Systems Development:
- Create self-directing robotic systems for industrial environments
- Build comprehensive simulation environments for reinforcement learning
- Develop advanced control systems for operational efficiency
- Development methodology: Robotics firms can execute thousands of parallel simulations on dedicated GPU hardware, dramatically reducing training cycles

Medical Technology and Genomic Research

Clinical Imaging Analysis:
- Optimize diagnostic workflows for radiological imaging (MRI, CT, X-ray)
- Develop early detection systems for oncology and other conditions
- Create surgical planning tools using 3D reconstruction from medical imaging
- Operational impact: Healthcare facilities can reduce analysis latency from hours to minutes using GPU-accelerated processing
Genomic Analysis and Drug Development:
- Process whole-genome sequencing data to identify disease markers
- Accelerate protein structure prediction and molecular dynamics
- Enable in silico screening of potential therapeutic compounds
- Performance enhancement: The H100 NVL’s extraordinary memory bandwidth (3.9 TB/s) allows processing of complete genomic datasets without I/O limitations
Precision Medicine Applications:
- Develop predictive models for individual treatment outcomes
- Analyze comprehensive patient records to optimize care protocols
- Create computational models for treatment response simulation
- Compliance advantage: Atlantic.net’s comprehensive HIPAA certification enables secure processing of protected health information

Financial Technology and Risk Management

Portfolio Risk Assessment:
- Execute advanced Monte Carlo simulations for investment risk quantification
- Test algorithmic trading strategies against historical market data
- Develop credit risk and default prediction models
- Implementation methodology: Financial analysts can utilize massive GPU parallelism to evaluate thousands of market scenarios simultaneously
Transaction Security and Fraud Prevention:
- Analyze payment streams for anomalous transaction patterns
- Implement neural network-based fraud detection systems
- Develop anti-money laundering compliance monitoring systems
- Architectural advantage: The L40S GPU platform provides optimal balance between computational capability and operational costs for continuous monitoring applications
Quantitative Finance Applications:
- Accelerate options pricing and derivative valuation
- Optimize algorithmic trading system performance
- Develop market prediction models using deep learning techniques
- Performance impact: Financial institutions gain critical microsecond advantages through GPU acceleration of trading algorithms

Scientific Computing and Engineering Simulation

Climate Science and Meteorology:
- Execute high-resolution climate modeling to assess environmental changes
- Improve forecasting accuracy through enhanced atmospheric models
- Process environmental monitoring data from satellite and sensor networks
- Economic advantage: Atlantic.net’s consumption-based pricing enables researchers to execute intensive simulations without permanent infrastructure investment
Computational Fluid Dynamics:
- Simulate aerodynamic performance for vehicle and aircraft design
- Model complex fluid behavior for industrial process optimization
- Improve energy efficiency through detailed thermal simulation
- Performance enhancement: Engineering teams typically achieve 10-20x acceleration compared to CPU-only simulations
Molecular Modeling and Materials Science:
- Simulate biological macromolecules and drug interactions
- Investigate material properties at atomic resolution
- Develop advanced catalysts for industrial applications
- Technical capability: The H100 NVL’s massive parallel architecture enables simultaneous simulation of millions of atomic interactions

Media Production and Visual Computing

Visualization and Rendering Systems:
- Accelerate rendering processes for entertainment production
- Enable interactive visualization for architectural and product design
- Reduce production timelines for animation studios
- Productivity impact: Visual effects studios can render complex scenes in minutes rather than hours using GPU acceleration
Video Processing Infrastructure:
- Transcode media assets for multi-platform distribution
- Apply AI-enhanced visual improvement to legacy content
- Implement content moderation and metadata extraction systems
- Hardware advantage: The L40S GPU includes specialized video encoding/decoding units for optimized media processing
Extended Reality Development:
- Build immersive virtual environments with physics simulation
- Create mixed reality applications with environmental understanding
- Enable cloud rendering services for lightweight XR devices
- Connectivity benefit: Atlantic.net’s high-performance network infrastructure ensures smooth delivery of rendered content

Business Analytics and Enterprise Intelligence

Enterprise Data Processing:
- Accelerate data transformation for analytics platforms
- Enable real-time analysis of operational data streams
- Visualize comprehensive business datasets for executive decision-making
- Performance metrics: GPU-accelerated analytics typically deliver 5-10x performance improvement over traditional CPU-based systems
Predictive Business Modeling:
- Develop advanced revenue forecasting systems
- Create customer behavior and retention prediction models
- Optimize operational efficiency through predictive modeling
- Implementation example: Retail enterprises can process years of transaction data in minutes to identify emerging market patterns
Natural Language Processing for Business Intelligence:
- Analyze customer communications and social media sentiment
- Extract actionable insights from unstructured textual data
- Implement automated document classification and processing
- Architecture advantage: Atlantic.net’s GPU infrastructure enables parallel processing of millions of documents simultaneously

Performance Evaluation and Market Comparison

Performance Analysis and Benchmarking

Atlantic.net’s GPU offerings demonstrate exceptional technical capabilities that position them competitively in the accelerated computing market:

L40S Performance Characteristics:
- AI inference tasks show approximately 30% improvement over previous generation accelerators
- FP8 precision operations deliver 2-5x throughput enhancement for transformer models
- Mixed precision training demonstrates 30-40% greater efficiency than consumer-grade hardware
- Media processing capabilities support 8K resolution content at 60 frames per second
H100 NVL Performance Profile:
- Demonstrates up to 12x performance improvement for large language models compared to previous generations
- The specialized Transformer Engine with FP8 support reduces memory consumption by approximately 60%
- HBM3 memory architecture with 3.9 TB/s bandwidth eliminates data transfer bottlenecks
- Multi-accelerator configurations demonstrate near-linear scaling for distributed workloads

Competitive Landscape Analysis

Within the GPU cloud service ecosystem, Atlantic.net offers several distinctive advantages:

Economic Value Proposition: While not positioned as the lowest-cost provider, Atlantic.net delivers better price/performance compared to major cloud platforms (AWS, Azure, GCP) with starting rates of $1.57/hour for L40S and $3.94/hour for H100 NVL, representing substantial cost advantages versus comparable offerings from larger providers.
Architectural Differentiation: Atlantic.net provides access to current-generation NVIDIA accelerators in both dedicated and shared configurations, with more direct hardware access than many competitors who primarily offer virtualized solutions with associated performance overhead.
Compliance Leadership: The combination of high-performance GPU infrastructure with comprehensive regulatory certifications (HIPAA, PCI, SOC 2/3, GDPR) creates a compelling advantage for organizations in regulated industries that require both maximum computational capability and strict security controls.
Support Excellence: The company’s 24/7/365 US-based technical support represents a significant advantage over many cloud GPU providers that offer limited or tiered support models, particularly valuable for production AI/ML operations.
Solution Focus: As a provider with specialized emphasis on GPU computing rather than offering GPU services as one component in a massive service catalog, Atlantic.net delivers more focused expertise specifically for accelerated computing applications.

Strategic Evaluation and Implementation Guidance

Atlantic.net’s GPU cloud platform delivers a sophisticated and flexible computing environment for organizations requiring advanced processing capabilities. With competitive pricing beginning at $1.57/hour for the L40S and $3.94/hour for the H100 NVL, along with substantial discounts for term commitments, they present exceptional value for organizations of all sizes, particularly when compared with major cloud providers charging premium rates for similar GPU resources.

The combination of cutting-edge NVIDIA accelerators (L40S and H100 NVL), extensive system customization options, enterprise-grade security with comprehensive compliance certifications, and continuous expert support positions Atlantic.net as an excellent choice for demanding AI/ML implementations, analytics workloads, and other GPU-accelerated applications. Their guaranteed 100% operational uptime further enhances the platform’s suitability for mission-critical computational workloads.

Optimal Organizational Profiles:

AI development organizations requiring enterprise-grade GPU infrastructure without capital expenditure
Healthcare technology companies conducting imaging analysis under strict regulatory requirements
Financial service operations implementing advanced risk models and security systems
Research institutions conducting complex simulations and large-scale data analysis
Media production companies requiring rendering and content processing capabilities
Enterprise analytics teams developing and deploying machine learning at scale

Implementation Considerations:

Organizations with large-scale requirements (hundreds of accelerators) should engage Atlantic.net’s solution architects for custom infrastructure planning
While Atlantic.net maintains a global presence, organizations with specific geographic requirements should verify capacity availability in target regions
Customers should evaluate the financial implications of consumption-based versus reserved instances based on anticipated utilization patterns

In summary, Atlantic.net’s GPU cloud platform delivers an impressive combination of computational capability, implementation flexibility, security compliance, and economic efficiency that effectively addresses modern AI and high-performance computing requirements across diverse industries and application scenarios.

Cloud GPU Providers - RANKED!

Cloud GPU Provider	Website	Pricing	Free Trial / Free Credits
Liquid Web Cloud GPU	Link	Premium	No
Atlantic.net	Link	Premium	No
Google Colaboratory :heart:	https://colab.research.google.com	FREE	FREE FOREVER*
Hyperstack.Cloud	Link	Premium	No
Kaggle Kernels	https://www.kaggle.com	FREE	FREE FOREVER*
Activeloop	https://www.activeloop.ai	-	-
Alibaba cloud	https://alibabacloud.com	Pay as you go	$300 credits
AWS Sagemaker	https://aws.amazon.com/sagemaker/	pricing :label:	Free plans
Azure	https://azure.microsoft.com/en-in/services/machine-learning-studio/	pricing :label:	$200 credits
Cirrascale	http://www.cirrascale.com	pricing :label:	-
Cloudalize	https://www.cloudalize.com	pricing :label:	-
Crestle	https://crestle.ai	pricing :label:	-
DataCrunch	https://datacrunch.io	V100 at $0.69/h	Fast.ai Special Discount
Dataiku	https://www.dataiku.com	-	Free Plans
Deep Cognition	https://deepcognition.ai	pricing :label:	Desktop version free to use
Deepnote	https://www.deepnote.com/	Currently in Beta	-
Examesh.de	https://examesh.de/en/	-	15min of NVIDIA Tesla V100 32 GB
Exoscale	https://www.exoscale.com/gpu/	pricing :label:	-
Genesis Cloud	https://www.genesiscloud.com/	1080Ti at $0.30/hour	166 free GPU hours
Golem	https://golem.network	-	-
Google Cloud Platform	https://cloud.google.com/gpu/	pricing :label:	$300 credits
GPUeater	https://gpueater.com	pricing :label:	-
GPULab	https://gpulab.io	pricing :label:	-
Hostkey	https://hostkey.com/dedicated-servers/gpu/	GPU from 90 euros/month	Free trials available
IBM Cloud	https://www.ibm.com/cloud/gpu	Pay as you go	$200 credits
Jarvis Labs	https://jarvislabs.ai/	RTX 5000 at $0.49/hr	Fast.ai Special Discount
Lambda Labs	https://lambdalabs.com/service/gpu-cloud	4x Pascals start at $1.50/hr	Reserved Instance Discounts
Leadergpu	https://www.leadergpu.com	pricing :label:	-
Nimblebox	https://nimblebox.ai	pricing :label:	Free $10 worth of cloud credits
Nvidia cloud	Nvidia Cloud GPU	-	-
One Stop System	https://www.onestopsystems.com	-	-
Paperspace	https://www.paperspace.com	pricing :label:	Referal Program Available
puzl.ee	https://puzl.ee/gpu-cloud	Rent a fraction of A100 for 0.40EUR/h	Free cloud Kubernetes API, up to 10 GPUs per pod
Q Blocks	https://qblocks.cloud/	$20 package ~ 100 GPU hours	Free 20 Compute Hours for Early access
Rapid Switch	https://www.rapidswitch.com	pricing :label:	-
Spell	https://spell.run/developers	pricing :label:	$10 GPU credit on signup
TensorDock	https://tensordock.com	pricing :label: pricing :label:	Discounts to FOOS, students and researchers
Vast.ai	https://vast.ai	pricing :label:	-
vscaler	https://www.vscaler.com	On Request	-

So, What are Cloud GPUs?

Let’s start with GPUs to get a better grasp on cloud GPUs.

Graphics processing units (GPUs) are specialized electronic circuitry that can rapidly alter and manipulate memory to expedite the generation of images and graphics.

Modern graphics processing units are more effective at image and computer graphics manipulation than conventional central processing units (CPUs) due to their parallel structure (CPUs). The central processing unit (CPU) die, the PC’s video card, or the motherboard could all house a GPU.

Massive artificial intelligence (AI) and deep learning tasks can be executed in the cloud using cloud graphics processing units (GPUs). In order to use this function, a GPU is not required.

Popular GPU manufacturers include AMD, NVIDIA, Radeon, and GeForce.

Deploy your model as a Web app

Have an idea and want to serve to world 🌎 , create a Webapp and deploy it as a flask , Django etc

Vendor	Website	Pricing	Free Trial / Free Credits
Deta	https://www.deta.sh/	pricing :label:	Free plan available
Digital Ocean	https://www.digitalocean.com	Pay as you go	Free $100 credits with github student pack
Glitch	https://glitch.com	-	-
Heroku	https://www.heroku.com	pricing :label:	Free plan (model<500MB)
PythonAnywhere	https://www.pythonanywhere.com/	pricing :label:	Free Beginner Account Available
Render	https://render.com	pricing :label:	-
Streamlit For Teams	https://www.streamlit.io/	pricing :label:	Currently in Beta ( Streamlit Cloud Tool )
Zeit	https://zeit.co	pricing :label:	Free plan available

MLOps Platforms

A Beautiful marriage :ring: between Machine Learning and DevOps ( A Match Made in Heaven )

Working on Serious Enterprise Level projects that has potential to serve millions of people and make :moneybag: , leave it to the power :zap: of DevOps to manage your Machine Learning LifeCycle

Project / Platform	Website	Pricing	Free Trial / Free Credits
Akira.ai	https://www.akira.ai/mlops-platform/	pricing :label:	-
Algo	https://www.algomox.com/aiops	-	Free Edition Available
Algorithmia	https://algorithmia.com/	pricing :label:	-
Allegro	https://www.allegro.ai/	pricing :label: - for enterprise	Open Source & Enterprise Version
Amazon Sagemaker	https://aws.amazon.com/sagemaker/	pricing :label:	Available for free as part of AWS Free Tier
Arrikto	https://arrikto.com/	-	-
ClearML	https://clear.ml	pricing :label:	Free plan available
Cnvrg	https://cnvrg.io/platform/mlops/	pricing :label:	-
DataRobot	https://www.datarobot.com/platform/mlops/	-	$500 of free usage credits across products
Flyte	https://flyte.org/	-	Open Source :octocat: Link
Google Cloud AI Platform	https://cloud.google.com/ai-platform/	pricing :label:	-
Gradient from Paperspace	https://gradient.paperspace.com/	pricing :label:	Free GPUs by Gradient
Grid.ai	https://grid.ai/	pricing :label:	$25 free credits + special promo for researchers!
HPE - Ezmeral	Solution from HP	-
HPE - GreenLake	Solution from HP	-
Iguazio	https://iguazio.com/mlops/	-	14 Day Free Trial
KubeFlow ( for k8s )	https://www.kubeflow.org/	-	Open Source :octocat: Link
MLFlow	https://mlflow.org/	-	Open Source :octocat:
Neptune.ai	https://neptune.ai/	pricing :label:	Freemium
Neu.ro	https://neu.ro/	-	-
Seldon Core	https://seldon.io/tech/products/core/	-	-
Valohai	https://valohai.com	pricing :label:	-

Perks and offers

If you are a student or researcher you can get extra credts , contact the provider

Examesh supports Public Research for free and gives special discount to long-term bookings.
Paperspace provides $10 of free Gradient° credit fast.ai link
Do you have a GPU lying around rent your machine to Earn money using Vast.ai*
Test Drive Nvidia GPU link
AWS Cloud Credits for Research -link
Nvidia GPU Grant Program- link
If you are a Startup then google has you covered wth Startup Program giving you credits from $1000 to $100000 - link
Google giving cluster of 1000 TPUs to researcher In total, this cluster delivers a total of more than 180 petaflops of raw compute power! techcrunch link - application link
Google cloud Education Grant - link
Github Education pack - along with many offers has upto $110 credits for AWS - link
Watch out on fast.ai Forums to get coupon code for free credits
Want to use a Super Computer but don’t have one, go for Golem - Golem is a decentralized marketplace for computing power. It enables CPUs and GPUs to connect in a peer-to-peer network, enabling both application owners and individual users to rent resources from other users machines, so turbo charge your next model training.
Hostkey provides grants for research, startups and competition winners link

* Notes

Google colab and Kaggle kernels have limited session time
Most of the gpu providers run on top of AWS , GCP etc so may have more or less same pricing as the latter
Information given above is best to my searching ability , you may recheck with the provider for pricing and other info