TensorWave expands its AI cloud platform with AMD Helios rackscale solution, bringing enterprise-grade performance and open infrastructure to the next generation of AI workloads

TensorWave, the all-AMD AI cloud specializing in high-performance, memory-intensive workloads, today announced it has adopted the AMD Helios rackscale solution, powered by AMD Instinct™ MI455X GPUs, to advance its infrastructure for frontier-scale inference and training workloads. The 72-GPU AMD Helios rackscale solution integrates AMD Instinct GPUs, 6th Gen AMD EPYC™ CPUs, AMD Pensando™ networking, and AMD ROCm™ software into a unified, open rack-scale platform built for high-volume inference, frontier-model training, and fine-tuning at scale.

“AMD Helios rackscale solution brings the best of AMD compute and networking technology together into a single rack-scale building block, delivering leadership performance, performance per watt, and cost per token for the next wave of AI,” said Andrew Dieckmann, Corporate Vice President and General Manager, Data Center GPU Business Unit, AMD. “As demand accelerates for large-scale inference and frontier-model training, AMD Helios gives customers a clear path to scale from rack to cluster with the efficiency, economics, and openness needed to power the most demanding AI workloads.”

“We chose TensorWave because they understand AMD infrastructure at a level most clouds simply don’t,” said Eugene Cheah, CEO and Co-Founder, Featherless AI. “That expertise and relationship with AMD gives us confidence not just in what we’re running today, but in knowing they’ll be ready for whatever AMD ships next.”

At rack scale, AMD Helios delivers exaflop-class AI performance for large-scale inference and frontier-model development:

• Up to 2.9 exaFLOPS peak 4-bit (OCP MXFP4) and 1.4 exaFLOPS peak 8-bit (OCP MXFP8) at rack scale, with 31 TB of HBM4 memory and 1.7 PB/s of memory bandwidth.
• AMD Instinct™ MI455X GPUs deliver up to 40 PFLOPs peak 4-bit, 20 PFLOPs peak 8-bit, 432 GB HBM4, and 23.3 TB/s memory bandwidth per device.
• 18 ORW-aligned 4-GPU compute trays (72 total MI455X GPUs) form a unified platform that can be virtualized for consistent cluster-scale deployment and expansion.
• The AMD Pensando™ Vulcano 800 AI NIC™ provides the high-bandwidth, low-latency connectivity needed to support multi-trillion-parameter training and rapid hyperscale growth.

“At TensorWave, we believe the future of AI starts with better infrastructure,” said Jeff Tatarchuk, Chief Growth Officer and Co-Founder, TensorWave. “AMD Helios brings compute, memory, and networking together at rack scale, enabling our customers to build AI faster, more efficiently, and with better economics at scale.”

AMD Helios combines open scale-up and scale-out networking, using UALink™ over Ethernet (UALoE) within the rack and Ultra Ethernet Consortium (UEC)-aligned Ethernet across racks, with defense-in-depth security, including Confidential Computing, device-level attestation, and encrypted multi-GPU scaling. AMD ROCm™ software delivers unified, high-throughput inference and training across all 72 GPUs and beyond, with optimized support for PyTorch, TensorFlow, JAX, ONNX Runtime, vLLM, and SGLang.

Source: BUSINESS WIRE