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STACKIT Compute Engine GPU - GPU Instances

STACKIT Compute Engine GPU: NVIDIA A100 and T4 from German data centers. AI training and inference GDPR-compliant.

Compute Engine
Pricing Model Pay-per-use (hourly billing)
Availability Germany (select regions)
Data Sovereignty 100% German data centers
Reliability 99.9% availability SLA

What is STACKIT Compute Engine GPU?

STACKIT Compute Engine GPU provides high-performance GPU-accelerated virtual machines for AI training, ML inference, and high-performance computing. Instances are equipped with NVIDIA enterprise GPUs: T4 for cost-effective inference and A100 for training large models. All GPU instances run in German data centers without US CLOUD Act risk.

Core Features

  • NVIDIA T4 (16GB) and A100 (40/80GB VRAM)
  • Multi-GPU instances with up to 8 GPUs
  • NVLink on A100 for high-bandwidth training
  • CUDA 11.x/12.x and TensorRT support
  • PyTorch, TensorFlow, and JAX compatible

Typical Use Cases

AI model training: Fine-tuning LLMs like LLaMA, Mistral, or GPT-J on proprietary data with multi-GPU setups.

ML inference: Production deployments of recommendation engines and computer vision on cost-effective T4 GPUs.

3D rendering: CUDA-accelerated rendering workloads with Blender, DaVinci Resolve, and other tools.

Benefits

  • Training data remains GDPR-compliant in Germany
  • No data exposure through US CLOUD Act
  • Flexible pay-per-use billing hourly
  • Mixed precision training with Tensor Cores

Integration with innFactory

As an official STACKIT partner, innFactory supports you with GPU Computing: architecture, migration, operations, and cost optimization.

Available Tiers & Options

NVIDIA T4

Strengths
  • Cost-effective
  • Good for inference
  • Lower power consumption
Considerations
  • Limited memory for large models

Typical Use Cases

AI model training and fine-tuning
Machine learning inference
3D rendering and video transcoding
Scientific simulations

Technical Specifications

Cuda support CUDA 11.x, 12.x
Frameworks TensorFlow, PyTorch, JAX
Gpu types NVIDIA T4 (16GB), A100 (40GB/80GB)
Multi gpu Up to 8 GPUs per instance
Nvlink NVLink support on A100

Frequently Asked Questions

What GPU models are available?

NVIDIA T4 (16GB) for inference and A100 (40/80GB) for training. T4 is cost-effective, A100 offers maximum performance.

Can I use multiple GPUs?

Yes. Multi-GPU instances with up to 8 GPUs available. A100 with NVLink for 600 GB/s inter-GPU bandwidth.

Is CUDA pre-installed?

NVIDIA drivers available as pre-configured images. CUDA Toolkit installable depending on framework version.

What compliance applies to AI training?

100% German data centers. Training data never leaves the EU. No US CLOUD Act access.

STACKIT Partner

innFactory is an official STACKIT Partner. We provide consulting, implementation, and managed services for the sovereign cloud.

STACKIT Official Partner

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