Train Foundational Models Without Limits
An AI cloud with a definitive architectural advantage for large-scale, distributed training.
The Architectural Advantage for Large-Scale Training
Training a foundational model requires a purpose-built architecture. Our platform is engineered with key advantages that solve the core bottlenecks of legacy clouds, ensuring your training jobs run faster and more efficiently.
Sustain Peak Performance with Zero Throttling
Our Direct Liquid Cooling architecture eliminates thermal throttling, ensuring your GPUs run at 100% of their capability for the entire duration of your long training runs. You get the uncompromised performance you pay for.
Eliminate Network Bottlenecks at Scale
Our RDMA fabric and Spine and Leaf network allow thousands of GPUs to communicate directly at breathtaking speed, bypassing CPU bottlenecks. This is essential for efficient distributed training at supercomputer scale.
Train Bigger Models on Fewer GPUs
Our AMD Instinct™ GPUs provide 1.5x the memory of competing chips. This allows you to train larger models with bigger batch sizes, fundamentally lowering your Total Cost of Ownership (TCO).
Bill Nye
The Science Guy
"We trained our foundation model 20% faster on TensorWave—and didn’t have to rework a single line of code."
