Accelerated Cloud GPUs for AI, ML & Rendering Workloads
Unlock high-performance compute for inference, training, and graphics workloads using Onemind’s cloud-native GPU infrastructure. Choose from T4, L4, and L40 GPU instances—scalable on-demand through Taikun platform.
High-Performance GPU Compute, Delivered from the Cloud
Provision GPU-optimized infrastructure instantly through Taikun. Ideal for teams building AI applications, media pipelines, or 3D visualizations—no hardware maintenance, no scaling headaches.
Instant access to T4, L4, and L40 GPUs
Pay-as-you-go or reserved capacity options
Compatible with popular AI/ML frameworks
Launch via dashboard or infrastructure API
Encrypted, isolated, and scalable GPU workloads
Why Choose OneMind for Cloud GPUs
Fully managed GPU infrastructure with low-latency access
Scalable from single-GPU to multi-GPU configurations
Runs on Taikun — a powerful, flexible cloud platform
API-first design for seamless integration into pipelines
Dedicated support for performance tuning and cost optimization
GPU Profiles
T4
(Efficient, Versatile GPU)
GPU Memory
16GB GDDR6
FP32 Performance
8.1 TFLOPS
Max Power Draw
8.1 TFLOPS
Bandwidth
320 GB/s
Ideal For:
AI inference, analytics, interactive apps, and low-latency workloads
Performance Highlights:
Efficient for NLP, vision models, and video processing
L4
(Balanced Compute for AI & Media)
GPU Memory
24 GB GDDR6
FP32 Performance
30 TFLOPS
Max Power Draw
72W
Bandwidth
300 GB/s
Ideal For:
Balanced compute for AI, rendering, desktop apps
Performance Highlights:
Versatile for mixed AI, 2D/3D workloads, and media tasks.
L40
(High-End Performance for Deep Learning
GPU Memory
48 GB GDDR6
FP32 Performance
91.6 TFLOPS
Max Power Draw
300W
Bandwidth
900 GB/s
Ideal For:
Heavy-duty training, simulation, generative AI
Performance Highlights:
Optimal for deep learning, 3D workflows, and compute-intensive apps
GPU Pricing
*The hourly rate is determined by dividing the monthly rate by 730 hours . If your server is online for more than 730 hours in a calendar month, you will only be billed the monthly rate.
*Prices listed above are based on the service being utilized for the period specified.
*All Servers include one IPv4 Address. Additional IPs are available for $2.19/month ($0.003/hour)
*Unlimited inbound bandwidth. If free outbound bandwidth is exceeded, each additional GB is $0.02
*Optional Daily Backups are available for 20% of the server price. Minimum $1.00/month.
Have specific requirements? Contact our team for custom builds or enterprise pricing.
Use Cases
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Inference Serving : Run real-time vision or NLP models in production.
- •
Model Training : Build and train custom AI/ML models with flexible scaling.
- •
Generative AI Workloads : Handle compute-heavy image, video, and text generation.
- •
3D Rendering : Accelerate visualization, digital twin, or VFX workloads.
- •
Remote Workstations : Deliver virtual desktops with GPU acceleration for creatives.
- •
Video Analytics : Process streams for enhancement, detection, or classification.
Getting Started with GPU Workloads
1. Choose Your GPU Type (T4, L4, L40)
Pick the instance that matches your workload profile and performance needs.
2. Provision via Dashboard or API
Set up GPU resources in minutes through the Taikun dashboard or API interface.
3. Deploy Your Framework
Run workloads using your preferred stack: TensorFlow, PyTorch, CUDA, or other AI/ML tools.
4. Scale When Needed
Easily scale up or out with multi-GPU support or by switching to larger instance types.
5. Monitor Usage
Track GPU utilization, memory, and runtime performance through built-in monitoring dashboards.
6. Optimize Billing
Review live GPU usage data and optimize costs by switching to reserved pricing options where appropriate.
Frequently Asked Questions (FAQs)
T4, L4, and L40 cloud GPUs are currently offered for varied AI/ML and compute workloads.
AI/ML inference, training, video processing, 3D rendering, and virtual desktops are fully supported.
Yes. You can deploy containerized applications with GPU passthrough support for accelerated workloads.
Yes. Choose from pre-configured images or bring your own custom environment.
Yes. Multi-GPU configurations are supported for large-scale, parallel processing tasks.
Provisioning typically completes in under 2 minutes via the dashboard or API.
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