TEAMCLOUD
GPU-NOW AS A SERVICE
TeamCloud GPU-Now as a Service for AI in Malaysia
Accelerate your AI projects with TeamCloud’s GPU-Now —on-demand, cost-effective GPU as a Service (GPUaaS), tailored for small to mid-sized AI models, all without breaking the bank.
Sustaining AI projects can be challenging, especially when returns take 2-5 years to materialize. Investing in costly GPU hardware too early can drain resources—particularly during the trial-and-error phase of selecting the right GPU model. TeamCloud GPU-Now by TeamCloud bridges this gap by offering GPU as a Service (GPUaaS) powered by OpenStack technology, providing on-demand access to high-performance yet affordable dedicated GPUs—from RTX 3090 and RTX 4090 to RTX 6000 Ada and H200 NVL—without the burden of upfront costs, complex setups, or infrastructure management. Designed for AI developers, researchers, and enterprises working with small-to-mid-sized AI models, TeamCloud GPU-Now enables seamless training, fine-tuning, and deployment. With flexible pay-per-use or subscription options, you can scale your AI projects efficiently. Fully managed and hosted in Malaysia, it ensures data sovereignty compliance while making AI development cost-efficient, scalable, and hassle-free.
The Challenges of AI: High Costs, Complex Infrastructure, and Data Risks
High Cost of GPUs
Training complex models, running deep learning, natural language processing (NLP), or scientific simulations all require GPUs—an expensive upfront investment that creates a major barrier.
Infrastructure Design and Maintenance
AI/ML workloads require specialized networking, storage, and compute resources, which can be challenging to configure optimally. Hardware failures and GPU degradation can disrupt operations.
Data Sovereignty and Compliance
For industries with strict data regulations, running AI/ML projects across borders is challenging. TeamCloud GPU-Now keeps your data in Malaysia, ensuring compliance with local laws and protection from cross-border risks.
Protecting Your AI Data—Hourly, Daily, and Weekly
When you’re focused on developing AI models or processing real-time data, worrying about data loss should be the last thing on your mind. With GPU, you can have peace of mind with automated tiered backups:
✅ Hourly backups: Retained for the last 15 hours
✅ Daily backups: Retained for the last 7 days
✅ Weekly backups: Retained for the last 4 weeks
Whether you’re recovering from unexpected system failures or safeguarding your evolving AI models, your data is protected at every stage.
Benefits of TeamCloud GPU-Now
Cost-Effective GPUaaS
GPU provides affordable, high-performance GPUs with flexible pay-per-use or subscription models, ensuring sustainable costs and predictable pricing—perfect for long-term AI projects.
Scalable On-Demand
Easily scale GPU resources up or down to match your project needs, from small-to-mid-sized AI models to complex deep learning tasks, optimizing GPU usage and maximizing ROI.
Peace of Mind
Enjoy 24/7 support and hosting in a secure, high-availability Tier III data center so you can focus on your core business while we handle your infrastructure.
Business Continuity
With 99.9% uptime guaranteed in our SLA, TeamCloud GPU-Now ensures reliable service, backed by data redundancy and automated backups, minimizing disruptions and data loss.
Accelerate AI Deployment
Access mid-to-high-end GPUs, including the NVIDIA H200 NVL, to speed up AI training, fine-tuning, and real-time inference—reducing iteration time and accelerating deployment.
Optimized for AI Workloads
TeamCloud GPU-Now balances performance, cost, and scalability for small-to-mid-sized AI projects, supporting diverse applications, from LLMs and generative AI to scientific simulations.
Fully Managed AI Infrastructure
With TeamCloud GPU-Now, we handle hardware failures, repairs, and maintenance, freeing you from infrastructure management and allowing you to focus entirely on your AI projects.
Safe and Secure Domestic Cloud
TeamCloud GPU-Now ensures your data stays local, complying with Malaysia’s data sovereignty laws and global standards like ISO27017 and PCI-DSS, offering top-tier security and protection.
Key Features of GPU
01
26+ copies
Data Protection & Backup
TeamCloud GPU-Now protects your data with automatic backups every hour, day, and week, ensuring quick recovery in case of cyberattacks or disasters to maintain uninterrupted AI development and deployment.
02
Dedicated
NVIDIA GPUs
With TeamCloud GPU-Now, you get dedicated, high-performance NVIDIA GPUs—not shared cards—including the RTX 3090, RTX 4090, and H200 NVL. Accelerate AI/ML training, fine-tuning, and real-time inference while efficiently handling complex workloads and deep learning tasks.
03
Data Redundancy
& Availability
TeamCloud GPU-Now ensures high availability and data security with automatic redundancy across multiple data centers, minimizing downtime and safeguarding AI workloads from unexpected disruptions.
04
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.
05
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, reliable local cloud environment.
06
24/7
Support Assistance
Benefit from around-the-clock support from our experienced engineers, ensuring your GPU instances run smoothly, with quick issue resolution to maintain optimal performance.
Standard Features
Platform Ease of Use
- Spin up GPU instances: Quickly launch GPU instances for AI workloads.
- Resize on-demand: Scale resources to fit project needs.
- Manage security access: Control access for secure operations.
- Billing & Transactions: Easily manage payments and view billing details.
Infrastructure and Performance
- Hybrid Cloud Ready: Seamlessly integrate with hybrid cloud environments.
- SSD Storage: Benefit from fast and reliable SSD storage.
- HA Cloud Infrastructure: High availability with automated failover.
- No Vendor Lock-in: Enjoy flexibility with no vendor restrictions.
- NovaCloud Care: Managed service with additional charges.
Security and Protection
- Anti-DDoS Protection: Free 5Gbit/s protection against DDoS attacks.
- Customizable Security Group: Easily configure firewall settings.
- Key-based Authentication: Secure access with public and private keys.
- Tier III Data Center: Hosted in a compliant Tier III data center with ISO 27001, ISO 27017, and SOC 2 Type II.
Instance Management
- Flexible Pricing Models: Choose pay-per-use or subscription-based options.
- Supported OS: Currently supporting Debian and Ubuntu.
- Scalable On-Demand: Resize, rebuild, and scale your instance as needed.
- Optimization Features: Shelve, unshelve, stop, reboot, and manage multi-volume and multi-snapshot attachments.
GPUs Benchmark
GPU Compute Performance
AI Processing Power: TOPS vs TPS
Available TeamCloud GPU-Now Options
We offer a range of NVIDIA GPUs options to cater to your specific AI/ML needs:
The RTX 3090, based on NVIDIA’s Ampere architecture, is a consumer GPU with 24GB of GDDR6X VRAM and 328 Tensor Cores. It provides adequate performance for AI/ML workloads, content creation, and gaming, serving as a reasonable option for enthusiasts and solo developers working on moderately demanding tasks.
✅ Training: Delivers decent speeds, roughly 5–15% faster than its predecessor depending on model and workload, with 3rd-gen Tensor Cores offering basic deep learning support.
✅ Fine-Tuning: Shows modest gains, with improvements varying by model size and task complexity.
✅ Inference: Handles real-time inference for small to medium AI tasks, though its 24GB VRAM can limit larger projects.
The RTX 4090, built on NVIDIA’s Ada Lovelace architecture, is a high-end consumer GPU with 24GB of GDDR6X VRAM and 512 Tensor Cores. It steps up compute performance for AI/ML workloads, gaming, and content creation, making it a solid choice for users needing more power and efficiency.
✅ Training: Up to 50–70% faster than its predecessor, depending on model and workload, with 4th-gen Tensor Cores enhancing deep learning tasks.
✅ Fine-Tuning: Delivers noticeable improvements, with performance varying by model complexity and task needs.
✅ Inference: Supports real-time inference across a range of AI applications, boosted by high bandwidth, though 24GB VRAM may cap larger models.
The H200 NVL, NVIDIA’s advanced Hopper-based datacenter GPU, boasts 141GB of HBM3e VRAM and 528 Tensor Cores. Engineered for next-generation AI/ML, high-performance computing (HPC), and enterprise workloads, it offers exceptional computational power and energy efficiency with its enhanced memory capacity and bandwidth.
✅ AI Training: Achieves up to 5x faster training than its predecessors for large language models, leveraging 4th-gen Tensor Cores and the Transformer Engine optimized for deep learning.
✅ Fine-tuning: Delivers substantial performance gains, scaling efficiently with model complexity and task demands, thanks to its 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 | |||||||
|---|---|---|---|---|---|---|---|
| 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 analyze vast volumes of logs and alerts daily, often struggling with false positives and slow threat detection due to data overload.
Solution: AI engineers can use TeamCloud GPU-Now to fine-tune AI models that detect anomalies, classify security events, and enhance real-time threat detection. With GPU-accelerated processing, security teams can quickly filter false positives, prioritize threats, and automate risk assessments for faster and more effective incident response.
Industry: Finance & Accounting
Challenge: Accountants spend hours manually extracting data from PDF invoices, scanned documents, and emails, then inputting it into accounting systems, making the process slow and error-prone.
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 accelerate financial workflows.
Industry: AI Chatbot Development
Challenge: Traditional chatbots rely on pre-scripted responses and struggle to retrieve real-time information, often leading to generic or outdated replies.
Solution: AI developers can use TeamCloud GPU-Now to develop Retrieval-Augmented Generation (RAG)-enhanced chatbots that combine real-time data retrieval with generative AI. With 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 by TeamCloud is a fully managed GPU as a Service (GPUaaS) solution that provides on-demand access to dedicated, high-performance NVIDIA GPUs, including the RTX 3090, RTX 4090, and H200 NVL. Designed for AI, machine learning, deep learning, and high-performance computing (HPC), TeamCloud GPU-Now offers a scalable, secure, cost-effective alternative to owning physical GPU hardware.
With flexible pay-per-use or subscription plans, users benefit from dedicated (not shared) GPU cards, 99.9% SLA-backed uptime, automated snapshot backups, high-availability setups, and 24/7 local support. TeamCloud GPU-Now also ensures robust data security while complying with Malaysia’s data sovereignty laws and international standards.
Ideal for developers, researchers, and enterprises running long-term AI projects, TeamCloud GPU-Now simplifies launching GPU instances, scaling on demand, and deleting resources anytime. This flexibility helps sustain project costs, making it easier and more affordable to start and maintain AI projects.
What is GPU as a Service (GPUaaS)?
GPU as a Service (GPUaaS) is a cloud-based platform that provides on-demand access to high-performance GPUs, eliminating the need for physical hardware. It enables businesses to run AI training, machine learning, and deep learning tasks without upfront costs or infrastructure management. TeamCloud GPU-Now offers flexible, cost-effective GPU instances that can be scaled to meet project demands. Simply sign up, select a plan, and start leveraging powerful GPUs instantly for your AI workloads.
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. Once subscribed, users can easily spin up instances, scale resources, and pay only for what they use. This model eliminates the need for physical infrastructure, offering flexibility, performance, and accessibility for AI/ML workloads, data analytics, and simulations. With TeamCloud GPU-Now, you can select from various GPU models, the number of GPU cards, storage sizes, and more—all through a secure, managed platform, enabling you to focus on your AI projects.
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 the key difference is how they are managed and accessed:
Cloud GPU: Refers to a GPU hosted in the cloud, but it often requires manual management, configuration, and scaling, which can add complexity.
GPUaaS: A fully managed service where the cloud provider handles infrastructure and maintenance, offering users a more flexible and streamlined experience. With TeamCloud GPU-Now, you get on-demand scaling, easy GPU instance management, and 24/7 support, specifically designed for AI and ML enthusiasts who prefer to focus on their projects without the hassle of managing infrastructure.
GPU as a Service vs. Dedicated Bare Metal GPU: Which is Better?
Both GPUaaS and dedicated bare metal GPUs offer powerful computing resources, but they differ in flexibility, cost, and management:
GPUaaS: Provides on-demand, scalable GPU access with no long-term commitment, making it ideal for projects with fluctuating GPU needs. It offers lower costs and comes with managed services for hassle-free operation.
Dedicated Bare Metal GPU: Offers 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.
With TeamCloud GPU-Now, you enjoy the flexibility of GPUaaS—high-performance GPUs on demand with no management burden.
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 high computational power these tasks require. Unlike traditional CPUs, GPUs are built to handle complex algorithms and process large datasets in parallel, significantly speeding up tasks like model training, fine-tuning, and inference.
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 like the RTX 6000 Ada and NVIDIA H200 NVL. Key benefits include:
- Scalable GPU Resources: Easily spin up and scale your GPU instances as needed, supporting both short-term and long-term AI workloads.
- 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 with a subscription—ideal for sustaining prolonged AI projects without breaking the bank.
- Optimized for AI: Perfect for training, fine-tuning, and running small-to-mid-sized AI models, including inference, helping you get the most from your AI initiatives.
- Fully Managed: No need to manage infrastructure—TeamCloud handles everything, freeing up your resources to focus on innovation.
- Local Cloud Hosting: Hosted in a secure local cloud environment, ensuring data sovereignty compliance, which is crucial for businesses with strict data privacy requirements.
- Maximized ROI: With flexible pricing, scalability, and high-performance GPUs, TeamCloud GPU-Now ensures that your investment in AI technologies remains cost-effective, delivering strong ROI even for long-term projects.
What are the use cases of TeamCloud GPU-Now—GPU as a Service by TeamCloud?
TeamCloud GPU-Now is ideal for tasks requiring moderate computational power, particularly for AI, machine learning (ML), and deep learning applications. Key use cases include:
- AI Model Training & Fine-Tuning: Ideal for training and fine-tuning small-to-mid-sized AI models, TeamCloud GPU-Now helps accelerate processing without the need for expensive hardware.
- AI Inference: Run inference tasks on trained models efficiently, making real-time predictions or classifications for a wide range of applications.
- Data Processing & Analytics: Handle medium-scale data processing tasks and analytics with TeamCloud GPU-Now, providing faster results for your AI-driven projects.
- Small to Mid-Sized Simulations: Run computationally intensive simulations, such as those used in research or product development, at a fraction of the cost of more powerful alternatives.
With TeamCloud GPU-Now, you get an on-demand, cost-effective, and secure GPU solution tailored to support your small-to-mid-sized AI and ML projects, maximizing performance without overcommitting resources.
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 tasks like training, fine-tuning, and inference of AI models. Whether you are working on small-to-mid-sized AI models or data processing, TeamCloud GPU-Now delivers high performance at an affordable cost. It’s a perfect fit for developers, researchers, and businesses looking to accelerate their AI and ML workflows without investing in expensive infrastructure.
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 workload on TeamCloud GPU-Now depends on your project’s size, complexity, and budget. At IP ServerOne, we offer both bare metal GPUs and GPU as a Service through TeamCloud GPU-Now, tailored for different AI/ML applications. Here’s a 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 starting out in AI.
- RTX 4090: A powerful and efficient choice for handling larger models and datasets. Great for solo developers or growing projects needing strong computing power.
- RTX 6000 Ada: A professional-grade GPU with extra memory and stability, perfect for businesses and professionals running advanced AI applications.
- H200 NVL: The top-tier GPU for large-scale AI research, enterprise-level projects, and demanding workloads, providing unmatched processing power for high-end AI 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. Key security features include:
- End-to-End Encryption: All data is encrypted during transmission and storage to ensure secure handling.
- 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 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 safeguard your data from unexpected loss.
- DDoS Protection: Built-in DDoS protection protects your resources from external attacks, ensuring continuous operation.
- High Availability Architecture: TeamCloud GPU-Now is hosted on a high-availability, spine-leaf architecture, providing fault tolerance and near-zero downtime.
- User-Controlled Security: You can configure your own security rules to meet your specific requirements and safeguard your data.
- Data Sovereignty: Hosted locally in Malaysia, TeamCloud GPU-Now fully complies with data sovereignty regulations.
With TeamCloud GPU-Now, your sensitive AI projects are securely managed within a robust and reliable cloud environment.
