High-Performance
GPU Cloud Nodes for AI & HPC

Instant access to bare-metal and virtualized GPU instances. Optimized for LLM training, GenAI inference, and large-scale rendering workloads.

Spin Up Instance View API Docs

99.99%

Uptime SLA

< 15s

Spin-up Time

100 Gbps

InfiniBand Network

Global

Tier-4 Data Centers

On-Demand GPU Instances

Transparent hourly billing. No long-term commitments required.

AI Enterprise Choice

LLM & Deep Learning

NVIDIA RTX 5080

$2.49 / GPU / hr

80GB SXM5 VRAM
3.35 TB/s Memory Bandwidth
PCIe 5.0 & NVLink Support
Dedicated 100G Interconnect

Model Fine-Tuning

NVIDIA RTX 5060

$1.29 / GPU / hr

80GB High-Speed HBM2e
2.0 TB/s Memory Bandwidth
Multi-Instance GPU (MIG)
High-Speed NVLink

Inference & Rendering

NVIDIA RTX 4090

$0.49 / GPU / hr

24GB GDDR6X VRAM
1,008 GB/s Bandwidth
DLSS 3 & Ray Tracing
Ideal for Stable Diffusion

DEVELOPER FIRST

Programmatic GPU Orchestration via API

Spin up, scale, or terminate GPU nodes automatically using our REST API or Python SDK. Pre-configured with PyTorch, CUDA, Docker, and Jupyter.

One-Line Container Launch

Custom Docker templates ready for instant LLM deployment.

deploy_node.py

Python 3.10

import igpunode

# Initialize iGpuNode Client
client = igpunode.Client(api_key="ign_live_8f93a1...")

# Deploy a High-Performance RTX 5080 Instance
instance = client.nodes.create(
    gpu_type="NVIDIA-H100-80GB",
    gpu_count=8,
    image="pytorch/2.1.0-cuda12.1",
    region="us-east-datacenter"
)

print(f"Node Online: {instance.ip_address}")