MEMORY-INTENSIVE AI
H200 Servers
Explore H200 server configurations for larger models and memory-intensive AI workloads.
Memory-intensive AI
Give larger models room to work.
Model size, numerical precision and concurrency influence the memory required by an AI workload. Fine-tuning and inference should be considered alongside data preparation and storage.
Discuss H200 servers for larger-model inference and fine-tuning. Bring your model and software requirements so NGT can review a configuration and rental term with you.
WORKLOAD & CONFIGURATION
Match the server
to the workload.
Share your model size, precision, concurrency and workload duration so NGT can discuss a suitable configuration.
Workloads to discuss
- Model fine-tuning
- Large-model inference
- Memory-intensive experimentation
- Model fit
- Model size, numerical precision, framework and accelerator memory.
- System resources
- CPU, system memory and data preparation requirements.
- Data access
- Dataset storage, networking and expected data movement.
- Rental plan
- U.S. location, target start date, monthly or annual term.
Product images are references. Exact GPU variant, complete server configuration, location availability and commercial terms are confirmed in your proposal.
Useful details to share
- Your model, software stack and workload duration
- Memory, storage and connectivity requirements
- Preferred U.S. location and rental term