TEAMCLOUD
GPU-NOW AS A SERVICE
TeamCloud GPU-Now as a Service for AI in Malaysia
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GPU as a Service (GPUaaS): Powered by OpenStack technology, GPU-Now offers on-demand access to high-performance GPUs like RTX 3090, RTX 4090, RTX 6000 Ada, and H200 NVL—without upfront costs or complex setups.
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Tailored for AI Development: Designed specifically for AI developers, researchers, and enterprises working with small-to-mid-sized AI models.
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Flexible Payment Options: Choose between pay-per-use or subscription models for efficient scaling of your AI projects.
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Fully Managed & Hosted in Malaysia: TeamCloud GPU-Now ensures data sovereignty compliance while making AI development more cost-efficient and scalable.
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Seamless AI Training and Deployment: Efficiently train, fine-tune, and deploy your AI models with minimal hassle.
The Challenges of AI: High Costs, Complex Infrastructure, and Data Risks
The high cost of GPUs presents a significant barrier for businesses and researchers looking to train complex models, run deep learning algorithms, perform natural language processing (NLP), or conduct scientific simulations. The expensive upfront investment required for high-performance GPUs can strain resources, especially during the trial-and-error phase of AI development, making it difficult to scale AI projects effectively and affordably.
AI/ML workloads demand specialized networking, storage, and compute resources, which can be complex to configure and maintain for optimal performance. Ensuring a reliable infrastructure for AI projects is crucial, as hardware failures and GPU degradation can lead to disruptions, causing delays and affecting the overall efficiency of AI model training and deployment. Proper infrastructure design and regular maintenance are key to preventing these issues.
For industries with stringent data regulations, running AI/ML projects across borders can be difficult due to concerns over data sovereignty and compliance. TeamCloud GPU-Now addresses these challenges by ensuring that your data remains securely stored within Malaysia, in full compliance with local laws. This eliminates risks associated with cross-border data transfers, providing a secure environment for your AI projects.
Protecting Your AI Data—Hourly, Daily, and Weekly
When developing AI models or processing real-time data, the last thing you should worry about is data loss. With TeamCloud GPU-Now, you can focus on your projects with peace of mind, knowing your data is safely protected through automated tiered backups.
Key Features of TeamCloud’s Automated Backups:
Hourly Backups: Retained for the last 15 hours, ensuring up-to-date protection.
Daily Backups: Retained for the last 7 days, offering quick recovery for recent changes.
Weekly Backups: Retained for the last 4 weeks, providing long-term protection and easy rollback.
Whether you’re recovering from system failures or safeguarding your evolving AI models, TeamCloud ensures your data is securely protected at every stage.
Benefits of TeamCloud GPU-Now
TeamCloud GPU-Now offers affordable, high-performance GPUs with flexible pay-per-use or subscription models, ensuring sustainable costs and predictable pricing. This makes it the ideal solution for long-term AI projects, where managing expenses is crucial while accessing the power of top-tier GPUs.
With TeamCloud GPU-Now, you can easily scale GPU resources up or down to match the evolving needs of your AI projects. Whether you’re working on small-to-mid-sized AI models or tackling complex deep learning tasks, our flexible scaling ensures that you optimize GPU usage and maximize your ROI.
With TeamCloud, you can focus on your core business while we handle your infrastructure. Enjoy 24/7 support and hosting in a secure, high-availability Tier III data center, ensuring your website and services are always online and protected.
With a 99.9% uptime guaranteed in our Service Level Agreement (SLA), TeamCloud GPU-Now ensures reliable service and uninterrupted performance for your AI projects. We back this up with data redundancy and automated backups, minimizing disruptions and safeguarding against data loss.
Access mid-to-high-end GPUs, including the NVIDIA H200 NVL, to significantly speed up AI training, fine-tuning, and real-time inference. With TeamCloud GPU-Now, reduce iteration time and accelerate the deployment of your AI models, ensuring faster results and improved performance.
TeamCloud GPU-Now strikes the perfect balance between performance, cost, and scalability for small-to-mid-sized AI projects. Whether you’re working with LLMs, generative AI, or scientific simulations, our solution provides the ideal environment for efficient AI model training and deployment.
With TeamCloud GPU-Now, you can focus entirely on your AI projects while we handle all aspects of infrastructure management. From hardware failures and repairs to regular maintenance, we ensure your AI infrastructure runs smoothly and efficiently—giving you peace of mind.
TeamCloud GPU-Now ensures your data remains local, complying with Malaysia’s data sovereignty laws and global standards such as ISO27017 and PCI-DSS. Enjoy top-tier security and data protection for your AI projects, all while ensuring full compliance with local and international regulations.
Key Features of GPU
Dream Big, Compute Bigger!
On-demand GPUs for AI/ML. From MYR1.96/hour for RTX 3090, MYR19.09/hour for H200 NVL.
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26+ copies
Data Protection & Backup
TeamCloud GPU-Now ensures your data is always protected with automatic backups every hour, day, and week. In the event of cyberattacks or disasters, quick recovery is guaranteed to maintain uninterrupted AI development and deployment.
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Dedicated
NVIDIA GPUs
Get access to dedicated, high-performance NVIDIA GPUs, including RTX 3090, RTX 4090, and H200 NVL. These non-shared GPUs accelerate AI/ML training, fine-tuning, and real-time inference, efficiently handling complex workloads and deep learning tasks.
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Data Redundancy
& Availability
TeamCloud GPU-Now provides high availability and data security with automatic redundancy across multiple data centers, minimizing downtime and safeguarding your AI workloads from unexpected disruptions.
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Optimized for AI/ML
& HPC Workloads
Designed for demanding AI/ML and high-performance computing (HPC) tasks, TeamCloud GPU-Now ensures high-speed training, precise inference, and reliable performance for complex models and custom applications.
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Seamless
Model Fine-Tuning
Easily fine-tune your pre-trained models on TeamCloud GPU-Now, enhancing accuracy and performance for your AI applications in a secure and reliable local cloud environment.
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24/7
Support Assistance
Benefit from 24/7 support from our experienced engineers, ensuring your GPU instances run smoothly with quick issue resolution to maintain optimal performance for your AI projects.
Standard Features
- Spin Up GPU Instances: Quickly launch GPU instances tailored for AI workloads.
- Resize On-Demand: Scale resources seamlessly to fit your project’s needs.
- Manage Security Access: Control access to ensure secure operations and data protection.
- Billing & Transactions: Easily manage payments and view detailed billing information.
- Hybrid Cloud Ready: Integrate effortlessly with hybrid cloud environments, providing flexibility and scalability.
- SSD Storage: Benefit from fast, reliable SSD storage, ensuring rapid access and low-latency performance.
- HA Cloud Infrastructure: Achieve high availability with automated failover, ensuring uninterrupted service.
- No Vendor Lock-In: Enjoy the flexibility of no vendor restrictions, allowing you to choose and change providers as needed.
- Cloud Care: Access managed services for additional support, with charges based on the level of service required.
- Anti-DDoS Protection: Enjoy free 5Gbit/s protection against DDoS attacks, ensuring your website remains safe.
- Customizable Security Group: Easily configure firewall settings for enhanced protection.
- Key-based Authentication: Secure access with public and private keys, ensuring only authorized users have access.
- Tier III Data Center: Hosted in a compliant Tier III data center with ISO 27001, ISO 27017, and SOC 2 Type II certifications for top-tier security and compliance.
- Flexible Pricing Models: Choose between pay-per-use or subscription-based pricing, ensuring cost efficiency for your AI workloads.
- Supported OS: Currently supports Debian and Ubuntu, providing a stable and secure environment for your projects.
- Scalable On-Demand: Resize, rebuild, and scale your instance to meet the dynamic needs of your AI models.
- Optimization Features: Shelve, unshelve, stop, reboot, and manage multi-volume and multi-snapshot attachments for enhanced flexibility.
GPUs Benchmark
Available TeamCloud GPU-Now Options
We offer a range of NVIDIA GPUs options to cater to your specific AI/ML needs:
The NVIDIA GeForce RTX 3090, powered by NVIDIA’s Ampere architecture, is a consumer GPU featuring 24GB of GDDR6X VRAM and 328 Tensor Cores. It offers solid performance for AI/ML workloads, content creation, and gaming, making it an excellent option for enthusiasts and solo developers tackling moderately demanding AI tasks.
✅ Training: Delivers solid speed improvements, around 5–15% faster than its predecessor, with 3rd-gen Tensor Cores providing basic support for deep learning.
✅ Fine-Tuning: Provides moderate performance gains, with improvements depending on the model size and task complexity.
✅ Inference: Handles real-time inference for small to medium AI tasks, though the 24GB VRAM may limit its capacity for larger projects.
The NVIDIA GeForce RTX 4090, built on NVIDIA’s Ada Lovelace architecture, is a high-end consumer GPU featuring 24GB of GDDR6X VRAM and 512 Tensor Cores. It significantly boosts compute performance for AI/ML workloads, gaming, and content creation, making it an ideal choice for users requiring both power and efficiency.
✅ Training: Offers up to 50–70% faster speeds than its predecessor, with 4th-gen Tensor Cores optimizing deep learning tasks and accelerating model training.
✅ Fine-Tuning: Provides substantial performance gains, with improvements depending on model complexity and the specific needs of the task.
✅ Inference: Handles real-time inference across a broad range of AI applications, enhanced by high bandwidth. However, the 24GB VRAM may limit the capacity for very large models.
The NVIDIA RTX 6000 Ada, a professional-grade GPU from NVIDIA’s Ada Lovelace lineup, features 48GB of GDDR6 VRAM and exceptional compute power. It’s designed for demanding tasks like AI, complex simulations, and 3D rendering, offering enhanced precision and capacity for advanced AI/ML users.
✅ Training: Up to 2x faster than its predecessor, with 4th-gen Tensor Cores driving robust deep learning performance and accelerated model training.
✅ Fine-Tuning: Delivers noticeable performance gains, depending on model size and task complexity, making it ideal for large-scale AI models.
✅ Inference: Excels in real-time inference for advanced AI applications, with extra VRAM supporting larger projects.
*Note: The NVIDIA RTX 6000 Ada is available only on Bare Metal GPU instances for top-tier performance.
The NVIDIA H200 NVL, based on NVIDIA’s Hopper architecture, is a datacenter GPU featuring an impressive 141GB of HBM3e VRAM and 528 Tensor Cores. Designed for next-generation AI/ML, high-performance computing (HPC), and enterprise workloads, it provides exceptional computational power and energy efficiency, with enhanced memory capacity and bandwidth.
AI Training: Achieves up to 5x faster training than its predecessors for large language models (LLMs), leveraging 4th-gen Tensor Cores and the Transformer Engine optimized for deep learning. Fine-tuning: Delivers significant performance gains, scaling efficiently with model complexity and task demands, thanks to a 1.5x memory increase over the H100 NVL. Inference: Excels in real-time inference for large-scale AI applications, providing up to 1.7x faster performance than the H100 NVL, driven by its 4.8TB/s memory bandwidth and NVLink connectivity.
TeamCloud GPU-Now Plans and Pricing
Explore TeamCloud GPU-Now plans tailored for your AI needs—accelerate machine learning, deep learning, and data processing with powerful NVIDIA GPUs like the RTX 3090, RTX 4090, and H200 NVL. Enjoy transparent pricing with no setup fees, no hidden charges, and most importantly, dedicated GPU cards (not shared) for maximum performance.
GPU Model: NVIDIA GeForce RTX 3090
| RTX 3090 | |||||||
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| PU Count | GPU Memory | CPU | Processor | RAM | Bandwidth | Price/Hour | Price/Month |
| 1 GPU | 1 x 24 GB | 8 core | AMD EPYC™ 9124 | 120 GB | 1Gbps | RM1.96 | RM1,435.02 |
| 2 GPU | 2 x 24 GB | 16 core | AMD EPYC™ 9124 | 240 GB | 1Gbps | RM3.92 | RM2,870.05 |
| 4 GPU | 4 x 24 GB | 32 core | AMD EPYC™ 9124 | 480 GB | 1Gbps | RM7.84 | RM5,740.10 |
GPU Model: NVIDIA GeForce RTX 4090
| RTX 4090 | |||||||
|---|---|---|---|---|---|---|---|
| GPU Count | GPU Memory | CPU | Processor | RAM | Bandwidth | Price/Hour | Price/Month |
| 1 GPU | 1 x 24 GB | 8 core | AMD EPYC™ 9124 | 120 GB | 1Gbps | RM2.64 | RM1,934.98 |
| 1 GPU | 1 x 48 GB | 8 core | AMD EPYC™ 9124 | 120 GB | 1Gbps | RM3.60 | RM2,635.50 |
| 2 GPU | 2 x 24 GB | 16 core | AMD EPYC™ 9124 | 240 GB | 1Gbps | RM5.29 | RM3,869.96 |
| 2 GPU | 2 x 48 GB | 16 core | AMD EPYC™ 9124 | 240 GB | 1Gbps | RM7.20 | RM5,271.01 |
| 4 GPU | 4 x 24 GB | 32 core | AMD EPYC™ 9124 | 480 GB | 1Gbps | RM10.57 | RM7,739.92 |
| 4 GPU | 4 x 48 GB | 32 core | AMD EPYC™ 9124 | 480 GB | 1Gbps | RM14.40 | RM10,542.02 |
GPU Model: NVIDIA H200 NVL Tensor Core
| H200 NVL | |||||||
|---|---|---|---|---|---|---|---|
| U Count | GPU Memory | CPU | Processor | RAM | Bandwidth | Price/Hour | Price/Month |
| 1 GPU | 1 x 141 GB | 32 core | AMD EPYC™ 9354P | 240 GB | 1Gbps | RM19.09 | RM13,3972.33 |
| 2 GPU | 2 x 141 GB | 64 core | AMD EPYC™ 9354P | 480 GB | 1Gbps | RM38.18 | RM27,944.67 |
Upgrade Option
| IP Address | Price / Hour |
| One floating IP address associated with a running instance | Free |
| Additional floating IP address associated with a running instance | RM0.043 |
| One floating IP address not associated with a running instance | RM0.043 |
| One floating IP address remap | Unmetered |
| Data Transfer | Price / Hour / GiB |
| First 1 TiB (*Not applicable to China Premium Route) | Free |
| Up to 10TiB | RM0.44 |
| Next 40TiB | RM0.31 |
| 50TiB onward | RM0.30 |
| Storage | Price / GiB SSD |
| Provision of storage (Inclusive of IOPs) | RM0.60 |
| Licensing | Price / Hour |
| Window License | RM0.175 |
Use Cases for TeamCloud GPU-Now Servers
Common deployment scenarios for TeamCloud GPU-Now.
Industry: Cybersecurity
Challenge: Security engineers are overwhelmed by vast volumes of logs and alerts, struggling with false positives and slow threat detection due to data overload.
Solution: With TeamCloud GPU-Now, AI engineers can fine-tune AI models for anomaly detection, event classification, and real-time threat detection. GPU-accelerated processing helps security teams quickly filter out false positives, prioritize threats, and automate risk assessments, leading to faster and more efficient incident response.
Industry: Finance & Accounting
Challenge: Accountants waste hours manually extracting data from PDF invoices, scanned documents, and emails, making the process slow and prone to errors.
Solution: AI developers can leverage TeamCloud GPU-Now to train AI-powered invoice processing models that automate text extraction, validation, and data entry. With GPU-accelerated Optical Character Recognition (OCR) and Natural Language Processing (NLP), businesses can eliminate manual work, minimize errors, and speed up financial workflows.
Industry: AI Chatbot Development
Challenge: Traditional chatbots rely on pre-scripted responses and often fail to retrieve real-time information, providing outdated or generic answers.
Solution: AI developers can utilize TeamCloud GPU-Now to build Retrieval-Augmented Generation (RAG)-enhanced chatbots that combine real-time data retrieval with generative AI. By leveraging GPU-accelerated processing, these chatbots can understand complex queries, fetch up-to-date information, and deliver contextually relevant responses at scale.
FAQ Frequently Asked Questions
What is TeamCloud GPU-Now?
TeamCloud GPU-Now is a fully managed GPU as a Service (GPUaaS) solution by TeamCloud that provides on-demand access to dedicated, high-performance NVIDIA GPUs, including RTX 3090, RTX 4090, and H200 NVL. It is specifically designed for AI, machine learning (ML), deep learning, and high-performance computing (HPC) workloads.
With flexible pay-per-use or subscription plans, users can access dedicated (not shared) GPUs with 99.9% SLA-backed uptime, automated snapshot backups, high-availability setups, and 24/7 local support. TeamCloud GPU-Now ensures robust data security and compliance with Malaysia’s data sovereignty laws and international standards, giving users peace of mind about their data’s safety.
Key Benefits:
On-Demand Access: Scale GPU instances up or down as needed, only paying for what you use.
High-Performance GPUs: Access top-tier GPUs like the RTX 3090, RTX 4090, and H200 NVL to power demanding AI/ML tasks.
Cost-Effective: No upfront costs for hardware—pay for GPU usage with flexible pricing plans.
99.9% Uptime Guarantee: Reliable service with SLA-backed uptime and automatic backups.
24/7 Support: Get local, round-the-clock assistance for any technical issues or inquiries.
Data Security & Compliance: Your data stays local, adhering to data sovereignty and security standards, including ISO 27001.
TeamCloud GPU-Now is ideal for developers, researchers, and enterprises running long-term AI projects that need high-performance GPUs but prefer the flexibility and cost savings of cloud-based solutions. It simplifies the process of launching GPU instances, scaling on-demand, and managing resources effectively, making it an affordable and scalable solution for AI/ML development.
What is GPU as a Service (GPUaaS)?
GPU as a Service (GPUaaS) is a cloud-based platform that offers on-demand access to high-performance GPUs, eliminating the need for costly physical hardware and infrastructure management. GPUaaS allows businesses to efficiently run AI training, machine learning, and deep learning tasks without upfront costs or complex hardware setups.
With TeamCloud GPU-Now, you can access flexible, cost-effective GPU instances that can be easily scaled to meet your project demands. Simply sign up, select a plan, and instantly start leveraging powerful GPUs to accelerate your AI workloads.
Key Benefits of GPUaaS with TeamCloud GPU-Now:
On-Demand Access: Start using high-performance GPUs as soon as you need them, with the flexibility to scale resources up or down based on your requirements.
Cost-Efficiency: No need to invest in expensive hardware—pay only for what you use with flexible pricing plans.
Scalable Performance: Easily adjust GPU resources to match the size and complexity of your AI projects.
Seamless Integration: Get up and running quickly without worrying about hardware management or setup.
TeamCloud GPU-Now makes it easy to access the computational power of top-tier GPUs, helping you accelerate AI model training and tackle complex machine learning tasks without the financial burden of owning hardware.
How does GPU as a Service work?
GPU as a Service (GPUaaS) allows users to rent GPU instances on-demand through cloud providers like IP ServerOne. After subscribing, users can easily spin up instances, scale resources, and pay only for what they use, removing the need for owning or managing physical infrastructure.
This cloud-based model provides flexibility, high-performance computing, and accessibility for a wide range of tasks such as AI/ML workloads, data analytics, and scientific simulations. With TeamCloud GPU-Now, you can choose from a variety of GPU models, the number of GPU cards, storage sizes, and more—all within a secure, managed platform.
By leveraging GPUaaS with TeamCloud GPU-Now, you can focus solely on advancing your AI projects, without the complexities and costs associated with managing physical hardware.
Key Benefits of TeamCloud GPU-Now for GPUaaS:
On-Demand GPU Access: Quickly launch and manage GPU instances based on your project needs.
Scalable Resources: Scale your resources seamlessly to meet the growing demands of your AI/ML models.
Cost-Efficiency: Only pay for what you use—no upfront hardware costs or maintenance fees.
Managed Platform: Enjoy a fully managed platform with secure access, making it easier to focus on your AI/ML development.
What’s the difference between cloud GPU and GPU as a Service?
Both Cloud GPUs and GPU as a Service (GPUaaS) provide access to GPU resources, but they differ in how they are managed and accessed:
Cloud GPU: Refers to a GPU hosted in the cloud, but often requires manual management, configuration, and scaling. This can introduce complexity, as users need to handle infrastructure-related tasks themselves.
GPUaaS: A fully managed service where the cloud provider takes care of infrastructure, maintenance, and scaling. This provides users with a more flexible and streamlined experience. With TeamCloud GPU-Now, you get on-demand scaling, easy GPU instance management, and 24/7 support—ideal for AI/ML enthusiasts who prefer to focus on their projects without the burden of managing complex infrastructure.
Key Benefits of TeamCloud GPU-Now:
Fully Managed Service: No need to handle infrastructure yourself—just focus on your AI/ML tasks.
On-Demand Scaling: Easily scale GPU resources based on the size and demands of your project.
24/7 Support: Receive continuous support from our experienced team to ensure your GPU instances run smoothly.
Tailored for AI/ML: Designed specifically for AI and machine learning workflows, providing the perfect environment for your projects.
GPU as a Service vs. Dedicated Bare Metal GPU: Which is Better?
Both GPU as a Service (GPUaaS) and dedicated bare metal GPUs provide powerful GPU computing resources, but they differ significantly in terms of flexibility, cost, and management:
GPUaaS: Offers on-demand, scalable GPU access with no long-term commitment, making it ideal for projects with fluctuating GPU needs. It comes with managed services for hassle-free operation, offering lower costs and the ability to scale resources as needed, making it perfect for AI/ML projects that may require flexibility.
Dedicated Bare Metal GPU: Provides exclusive access to a physical GPU on a dedicated server, delivering maximum performance for consistent workloads. However, it often comes with higher costs, limited scalability, and more management overhead since users are responsible for infrastructure management.
With TeamCloud GPU-Now, you get the flexibility of GPUaaS, enjoying high-performance GPUs on demand without the burden of managing infrastructure, making it an ideal choice for projects that need both scalability and cost-efficiency.
Key Benefits of TeamCloud GPU-Now:
On-Demand GPU Access: Get instant access to high-performance GPUs without the need for long-term commitments.
Scalability: Scale your GPU resources easily based on project requirements, whether for AI/ML tasks, simulations, or data analytics.
Cost-Efficiency: GPUaaS offers lower upfront costs, helping you optimize project budgets.
Managed Service: Focus on your AI projects while we handle infrastructure management for you.
Why is GPU as a Service ideal for AI, LLMs, and deep learning?
GPU as a Service (GPUaaS) is the ideal solution for AI, large language models (LLMs), and deep learning due to the immense computational power required for these tasks. Unlike traditional CPUs, GPUs are specifically designed to handle complex algorithms and process large datasets in parallel, making them much more efficient for tasks such as model training, fine-tuning, and inference.
With TeamCloud GPU-Now, you gain on-demand access to high-performance GPUs, providing the necessary processing power to accelerate AI development and improve the performance of your AI models and LLMs. This scalable and cost-effective solution ensures that your deep learning projects can be completed faster, with the ability to scale resources as your models grow.
Key Benefits of GPUaaS for AI, LLMs, and Deep Learning:
Parallel Processing: GPUs excel at handling multiple calculations simultaneously, speeding up the training and fine-tuning of AI models.
Efficient Model Training: Handle complex deep learning tasks more efficiently than traditional CPUs, reducing time to deployment.
Cost-Efficiency: Pay for only the GPU resources you need, avoiding the high upfront costs of purchasing dedicated hardware.
Scalability: Easily scale your GPU resources based on your project demands, ensuring flexibility as AI models evolve.
TeamCloud GPU-Now simplifies AI and deep learning workflows by providing the computing power necessary to push the boundaries of large language models and deep learning applications.
How can TeamCloud GPU-Now—GPU as a Service by IP ServerOne benefit my business?
TeamCloud GPU-Now provides on-demand, high-performance GPUs ranging from mid-tier options like the RTX 3090 and RTX 4090 to top-tier models such as the RTX 6000 Ada and NVIDIA H200 NVL. This GPU as a Service (GPUaaS) solution offers a range of benefits for businesses looking to enhance their AI, machine learning, and deep learning capabilities:
Key Benefits of TeamCloud GPU-Now:
Scalable GPU Resources: Easily spin up and scale GPU instances to meet the demands of both short-term and long-term AI workloads, ensuring flexibility as your projects evolve.
Flexible Pricing: Choose between pay-per-hour or subscription-based models, allowing you to pay only for what you use or secure long-term cost savings—ideal for businesses running prolonged AI projects without exceeding budgets.
Optimized for AI: Specifically designed for training, fine-tuning, and running small-to-mid-sized AI models, including inference, maximizing the impact of your AI initiatives.
Fully Managed: No need to manage infrastructure—TeamCloud handles everything, allowing your team to focus on innovation rather than maintaining hardware.
Local Cloud Hosting: Hosted in a secure local cloud environment, ensuring data sovereignty compliance—critical for businesses with strict data privacy requirements.
Maximized ROI: With flexible pricing, scalable resources, and high-performance GPUs, TeamCloud GPU-Now ensures that your investment in AI technologies is cost-effective and delivers strong ROI, even for long-term projects.
TeamCloud GPU-Now is the perfect solution for businesses that want to leverage GPU power without the need for heavy upfront investments or infrastructure management. It enables you to accelerate AI projects, improve productivity, and achieve faster results.
What are the use cases of TeamCloud GPU-Now—GPU as a Service by TeamCloud?
TeamCloud GPU-Now is an ideal solution for tasks requiring moderate computational power, particularly in the fields of AI, machine learning (ML), and deep learning. Here are some key use cases where TeamCloud GPU-Now excels:
AI Model Training & Fine-Tuning: Perfect for training and fine-tuning small-to-mid-sized AI models, TeamCloud GPU-Now accelerates processing without the need for expensive hardware, making it easier to scale AI projects.
AI Inference: Run inference tasks on trained models efficiently, enabling real-time predictions or classifications for a variety of applications such as customer service, automation, and more.
Data Processing & Analytics: Handle medium-scale data processing and analytics tasks with ease, providing faster insights and results for your AI-driven projects.
Small to Mid-Sized Simulations: Run computationally intensive simulations, often used in research or product development, at a fraction of the cost of more powerful alternatives.
With TeamCloud GPU-Now, you get a cost-effective, on-demand, and secure GPU solution tailored to support your small-to-mid-sized AI and ML projects, delivering optimal performance without overcommitting resources.
Why Choose TeamCloud GPU-Now?
Flexible & Scalable: Easily scale GPU resources based on project needs.
Cost-Efficient: No upfront costs for hardware—only pay for what you use.
Fully Managed: Let TeamCloud handle the infrastructure while you focus on your projects.
High-Performance GPUs: Access powerful NVIDIA GPUs optimized for AI and ML tasks.
Can I use TeamCloud GPU-Now for machine learning and AI projects?
Yes, TeamCloud GPU-Now is specifically designed to support machine learning (ML) and AI projects. With its on-demand, scalable GPU instances, TeamCloud GPU-Now provides the computational power needed for critical tasks such as training, fine-tuning, and inference of AI models.
Whether you’re working on small-to-mid-sized AI models or handling data processing for larger AI applications, TeamCloud GPU-Now delivers high performance at an affordable cost. This makes it the perfect solution for developers, researchers, and businesses looking to accelerate their AI and ML workflows without the need for costly infrastructure investments.
Key Benefits of TeamCloud GPU-Now for AI/ML Projects:
Scalable GPU Resources: Access on-demand GPU instances that scale according to your project needs.
Affordable Pricing: Only pay for the GPU resources you use, making it cost-effective for long-term AI/ML projects.
Optimized for AI and ML: Specifically designed for tasks like model training, fine-tuning, and real-time inference.
Fully Managed Service: Let TeamCloud handle infrastructure and management, allowing you to focus on developing AI models.
TeamCloud GPU-Now ensures that your AI and ML projects are executed efficiently, with access to top-tier GPU performance at a fraction of the cost of physical hardware.
How do I choose the right GPU instance for my specific AI/ML workload on TeamCloud GPU-Now?
Choosing the right GPU instance for your AI/ML workload on TeamCloud GPU-Now depends on several factors, including your project’s size, complexity, and budget. At IP ServerOne, we offer both bare metal GPUs and GPU as a Service (GPUaaS) through TeamCloud GPU-Now, tailored to suit different AI/ML applications. Here’s a quick guide to help you select the ideal GPU:
RTX 3090: A budget-friendly option for smaller AI projects like image recognition and basic models. Ideal for beginners or small teams just starting out in AI.
RTX 4090: A powerful and efficient choice for handling larger models and datasets. Great for solo developers or growing projects that require strong computing power and efficiency.
RTX 6000 Ada: A professional-grade GPU with extra memory and enhanced stability, making it the perfect option for businesses and professionals working on advanced AI applications.
H200 NVL: The top-tier GPU designed for large-scale AI research, enterprise-level projects, and demanding workloads, offering unmatched processing power for high-end AI development.
By choosing the right GPU instance on TeamCloud GPU-Now, you can optimize performance and cost-efficiency for your specific AI/ML projects.
Key Benefits of TeamCloud GPU-Now:
Tailored GPU Options: Select from mid-range to high-end GPUs, depending on your project needs.
Scalability: Easily scale your GPU resources as your project grows.
Managed Service: No need to manage infrastructure—TeamCloud handles it all, letting you focus on AI model development.
How secure is my data on TeamCloud GPU-Now?
Security is a top priority for TeamCloud GPU-Now. We implement multiple layers of protection to ensure the safety and confidentiality of your data and workloads. Here are some of the key security features that TeamCloud GPU-Now offers:
End-to-End Encryption: All data is encrypted during transmission and storage, ensuring secure handling throughout the process.
ISO & Compliance Standards: TeamCloud GPU-Now is hosted in an environment compliant with ISO 27001, ISO 27017, PCI-DSS, and SOC 2 Type II standards, ensuring adherence to the highest industry security protocols.
Data Redundancy: Your data is replicated across multiple data centers in Malaysia, enhancing reliability and minimizing the risk of data loss.
Snapshot Backups: Automatic hourly, daily, and weekly snapshot backups ensure your data is safe from unexpected loss.
DDoS Protection: Built-in DDoS protection safeguards your resources from external threats, ensuring continuous operation.
High Availability Architecture: Hosted on a high-availability, spine-leaf architecture, TeamCloud GPU-Now provides fault tolerance and near-zero downtime.
User-Controlled Security: You can configure your own security rules to meet your specific requirements, ensuring your data is always protected according to your needs.
Data Sovereignty: Hosted locally in Malaysia, TeamCloud GPU-Now fully complies with data sovereignty regulations, ensuring your data remains within national borders.
With TeamCloud GPU-Now, your sensitive AI projects are securely managed in a robust and reliable cloud environment, providing you with peace of mind while you focus on advancing your AI/ML workloads.
