Start AI Development Now with NVIDIA TITAN RTX
Exclusive Education Pricing
AMAX’s DL-E TITAN RTX based GPU workstations powered by NVIDIA Turing™, the world’s most advanced GPU architecture, are now available at exclusive pricing for research and educational institutions.
Compact Deep Learning Workstation
Ultra-compact high-end Deep Learning development workstation, perfect for AI startups and labs. This ultra-quiet micro ATX workstation features NVIDIA Titan RTX, Quadro GV100, Quadro RTX series GPUs, on-board dual 1G/10G Ethernet and enterprise-grade motherboard.
High-Performance Deep Learning DevBox
Our best-selling Deep Learning workstation for Deep Learning development! This ultra-quiet compact workstation featuring NVIDIA Titan RTX, Quadro GV100, Quadro RTX series GPUs, on-board dual 1G/10G Ethernet and enterprise-grade motherboard.
Ideal for for AI researchers, university labs, data scientists and content creators, the DL-E200/400 features NVIDIA® TITAN RTX™with 576 multi-precision Turing Tensor Cores can deliver up to 130 teraFLOPS (TFLOPS) for deep learning training; 72 Turing RT Cores that provide up to 11 GigaRays per second for maximum real-time ray tracing performance; and 24 GB of GDDR6 memory (or 48 GB with NVLink) for training higher batch sizes, processing larger datasets and simulation models, and managing the most demanding workflows.
Spring into action with AMAX’s DL-E GPU workstations today! Powered by the NVIDIA® TITAN RTX GPU:
- Twice the memory of previous-generation, for working with higher batch sizes and larger datasets.
- 100 GB/s NVIDIA NVLink™, so you can pair two TITANs to scale memory and compute.
- Accelerate model development with CUDA-X AI support for all popular frameworks, freely available via NGC.
- Supported by NVIDIA’s CUDA-X AI SDK, including cuDNN, TensorRT and more than 15 other libraries. Works with all popular deep learning frameworks and compatible with NVIDIA GPU Cloud (NGC).
- With TITAN RTX and NGC software, AI researchers and developers can start developing in minutes dramatically shortening their time to productivity.