GPU Hosting
High-performance GPU infrastructure for AI training and inference workloads.
Available Hardware
NVIDIA H100
Top-tier performance for large language model training and high-throughput inference.
80GB HBM3 · 3.2TB/s Memory Bandwidth
NVIDIA A100
Proven workhorse for training and inference with excellent cost-performance ratio.
40GB/80GB · 1.6TB/s Memory Bandwidth
NVIDIA L4
Optimized for inference workloads with excellent power efficiency.
24GB GDDR6 · Real-Time Inference
Custom Clusters
Multi-GPU configurations with NVLink and high-speed networking for distributed training.
4x, 8x, 16x GPU Nodes Available
Infrastructure Features
Optimized Containers
Pre-configured Docker images with CUDA, PyTorch, TensorFlow, and popular ML frameworks.
Instant Provisioning
Spin up GPU instances in under 60 seconds with API-driven orchestration.
Real-Time Monitoring
Track GPU utilization, memory, temperature, and power consumption in real-time.
Attached Storage
High-speed NVMe storage with snapshot backups and data persistence.
Common Use Cases
LLM Training & Fine-Tuning
Train or fine-tune large language models with multi-GPU distributed training.
Real-Time Inference APIs
Deploy production inference endpoints with auto-scaling and load balancing.
Computer Vision Pipelines
Process images and video at scale with GPU-accelerated inference.
Research & Experimentation
On-demand GPU access for research, prototyping, and benchmarking.