CUDA Dedicated Servers for AI Training, Inference, and Deep Learning

NVIDIA H100

For teams training foundation models or running massive generative AI deployments.

• 80GB memory capacity per GPU.
• Massive memory bandwidth designed for the most demanding workloads.
• Available as dedicated, single-tenant servers.

8x NVIDIA A100 Clusters

Cut production-scale LLM training times from weeks to days.

• Up to 640GB of HBM2e memory across the cluster.
• Hold massive batch sizes entirely in memory.
• Perfect for models requiring extended context windows.

NVIDIA L40S

The perfect balance between cost and extreme performance.

• 48GB memory with high CUDA core counts.
• Equipped with advanced Tensor Cores.
• Ideal for fine-tuning smaller models (Llama-3, Mistral) and heavy 3D rendering alongside deep learning.

NVIDIA L4

High-performance inference built on Ada Lovelace.

• 24GB memory capacity.
• Optimized for Generative AI inference and mixed workloads.
• Cost-effective alternative to flagship enterprise cards without sacrificing modern architecture features.

GTX 1080 Ti

Priced for students, researchers, and early-stage startups.

• 3,584 CUDA Cores for dedicated parallel computing.
• Perfect for testing training scripts.
• Great for mastering CUDA-based programming.

Tesla M40

Affordable development server for early-stage work.

• 3,072 CUDA Cores.
• An excellent entry point for lightweight inference.
• Cost-effective alternative before scaling up to modern clusters.