Rent GPUs
By the Hour
Access the latest NVIDIA GPUs on demand. No long-term commitments, no hardware to manage. Deploy in minutes, pay only for what you use.
Cloud GPU Rental: Access AI Compute On Demand
SLYD's Compute Marketplace offers GPU instances by the hour with no long-term commitments. Access NVIDIA H100, H200, A100, RTX 6000 Blackwell Pro, and other accelerators for AI training, inference, and development. Deploy in minutes, scale instantly, and pay only for what you use.
What's Available
Our cloud GPU inventory includes the latest accelerators at competitive hourly rates:
H200 SXM
141GB HBM3e, 4.8 TB/s bandwidth, ideal for large model training and inference workloads
H100 SXM
80GB HBM3, 3.35 TB/s bandwidth, the standard for AI training workloads and fine-tuning
A100
40GB or 80GB HBM2e, proven performance for training and inference at lower cost
RTX 6000 Blackwell Pro
Professional GPU optimized for inference, visualization, and professional workloads
L4 and A10
Cost-effective inference GPUs for production deployment and budget-conscious workloads
[compass] Selection Guide
Choose GPU types based on your workload requirements and budget constraints.
For Training
H100 and H200 provide the highest throughput for large model training. Multi-GPU configurations with NVLink are available for distributed training across 8+ GPUs.
For Inference
A100, L4, and RTX 6000 offer excellent inference performance at lower cost per query. vLLM and TensorRT-LLM templates are pre-configured for optimal throughput.
For Development
Any GPU type works for prototyping and experimentation. Start with lower-cost options and scale to production hardware when ready.
For Scaling
Go from 1 GPU to 1,000+ in minutes. Multi-node clusters available for distributed workloads with high-speed interconnects.
[tags] Pricing Options
Flexible pricing models to match your workload patterns and budget:
Hourly
Pay only for active compute time, billed per second with no minimum commitment
Reserved
Commit to capacity for discounted rates on predictable, long-running workloads
Spot
Access unused capacity at additional savings for fault-tolerant and flexible jobs
Why SLYD Cloud
Cloud GPU rental through SLYD includes:
- Instant — Deploy instances in 2-5 minutes with pre-configured environments
- Flexible — No minimum commitments, scale from 1 to 1,000+ GPUs
- Equipped — CUDA, PyTorch, TensorFlow, and ML frameworks pre-installed
- Supported — 24/7 infrastructure support for enterprise plans
- Sovereign — Keep data on your terms—private networking and dedicated instances
Need More Control?
For consistent 24/7 utilization, purchasing hardware may offer better long-term economics.
Browse HardwareAvailable Servers
Real-time availability with instant deployment. All servers include CUDA, drivers, and popular ML frameworks.
1x NVIDIA GeForce RTX 4090
Gaming & Consumer AI
1x RTX A6000
Professional Workstation
1x RTX A6000
Professional Workstation
1x RTX A6000
Professional Workstation
1x RTX 6000 ADA
AI Inference & Visualization
1x L40
General Purpose GPU
1x RTX A6000
Professional Workstation
1x RTX A6000
Professional Workstation
1x RTX A6000
Professional Workstation
8x Tesla V100-PCIE-16GB
General Purpose GPU
8x NVIDIA TITAN V
General Purpose GPU
1x A100
Training & Inference
Focus on AI, Not Infrastructure
Pay Only for What You Use
No upfront costs, no depreciation, no maintenance. Hourly billing means you only pay when you're actually using compute.
Deploy in Minutes
Launch GPU instances with pre-configured CUDA, PyTorch, TensorFlow, and other ML frameworks. No setup required.
Scale Instantly
Go from 1 GPU to 1,000+ in minutes. Scale up for training runs, scale down when done. No capacity planning.
Enterprise Security
Enterprise-grade security controls. Private networking, encrypted storage, and dedicated instances available.
Expert Support
Our infrastructure team is available 24/7. Get help with deployments, optimization, and troubleshooting.
Pre-Built Apps
One-click deploy vLLM, JupyterHub, PyTorch, and 50+ other AI tools from our app marketplace.
Built for Every AI Workload
Model Training
Train foundation models, fine-tune LLMs, or run hyperparameter sweeps across multi-GPU clusters with high-speed NVLink interconnects.
- Multi-node distributed training
- NVLink for GPU-to-GPU communication
- Persistent storage for checkpoints
Inference at Scale
Deploy production inference endpoints with auto-scaling, load balancing, and optimized serving frameworks like vLLM and TensorRT.
- Auto-scaling based on demand
- Low-latency inference
- Cost-optimized GPU selection
Development & Experimentation
Spin up Jupyter notebooks or VS Code environments with GPU access for prototyping, research, and experimentation.
- Pre-configured ML environments
- Persistent workspaces
- Git integration
Data Processing
Accelerate data preprocessing, feature engineering, and ETL pipelines with GPU-accelerated tools like RAPIDS and Spark.
- GPU-accelerated DataFrames
- Fast data loading
- Integration with data lakes
When to Rent Cloud GPUs
Rent Cloud GPUs
- Variable or unpredictable workloads
- Short-term projects or experiments
- Need to scale up/down quickly
- Avoid upfront capital expenditure
- Access latest GPU generations
- No IT staff for hardware management
Buy Hardware
- Consistent 24/7 workloads
- Multi-year projects
- Data sovereignty requirements
- Predictable capacity needs
- On-premises requirements
- Lower long-term TCO
Not sure which option is right for you? Talk to our team for a personalized recommendation.
Frequently Asked Questions
How quickly can I deploy a GPU instance?
Most GPU instances are available within 2-5 minutes. You can choose from pre-built images with CUDA, PyTorch, TensorFlow, and other frameworks already installed, or bring your own Docker container.
What's the minimum rental period?
There is no minimum rental period. You're billed by the hour (or per second for some instance types), so you can spin up an instance for a quick experiment and shut it down when you're done.
Can I reserve GPUs in advance?
Yes. For predictable workloads, you can reserve capacity at discounted rates. Contact our sales team for reserved instance pricing and availability.
Do you offer multi-GPU and multi-node clusters?
Yes. We offer 8-GPU nodes with NVLink for high-bandwidth GPU-to-GPU communication, and can provision multi-node clusters for distributed training workloads.
Is my data secure?
Yes. All instances run on isolated infrastructure. Data is encrypted at rest and in transit. We implement enterprise-grade security controls and offer private networking and dedicated instances for additional security.
Can I bring my own software/containers?
Absolutely. You can deploy custom Docker containers, install any software you need, and configure the environment to your requirements. We also offer persistent storage so your setup is preserved.
Ready to Start Training?
Sign up now and deploy your first GPU instance in under 5 minutes. No credit card required to explore.