Lower TCO + Higher Performance

AMD Instinct™ MI300X

Supercharge your AI inference workloads with an impressive 192GB HBM3E of memory per GPU.

AMD Instinct MI300X GPU

MI300X Specs

Our AMD Instinct™ MI300X nodes are built for high-performance AI inference workloads with zero lock-in for faster, frictionless deployment.

AMD Instinct MI355X GPU

MI300X Server Configuration

TensorWave's AMD Instinct MI300X servers include ultra-high memory bandwidth and blazing fast networking powered by RoCEv2 interconnects.

Whether you're fine-tuning models or scaling inference, TensorWave’s AMD MI300X cluster delivers high memory per GPU and ultra-low TCO. Built for inference, it provides a cost-efficient path from development to production.

Media

Standard Node Config

Bare Metal

with optional managed Kubernetes & Slurm

Accelerators

8x AMD Instinct MI300X

CPUs

2x AMD Genoa 9654

Memory

2.3 TB DDR5 4800 MT/s

Local Storage

4x 3.84TB NVMe Drives + 2x 960GB m.2

Node Interconnects

3.2Tb/s

Peak Network Storage

50PB
Media

MI300X Server Configuration

TensorWave's AMD Instinct MI300X servers include ultra-high memory bandwidth and blazing fast networking powered by RoCEv2 interconnects.

Standard Node Config

Bare Metal

with optional managed Kubernetes & Slurm

Accelerators

8x AMD Instinct MI300X

CPUs

2x AMD Genoa 9654

Memory

2.3 TB DDR5 4800 MT/s

Local Storage

4x 3.84TB NVMe Drives + 2x 960GB m.2

Node Interconnects

3.2Tb/s

Peak Network Storage

50PB

Whether you're fine-tuning models or scaling inference, TensorWave’s AMD MI300X cluster delivers high memory per GPU and ultra-low TCO. Built for inference, it provides a cost-efficient path from development to production.

AMD Instinct MI300X

Dual AMD Genoa 9654 CPUs, 2.3TB DDR5, 3.2 Tb/s RoCEv2 (2x400Gb/s front-end + storage)

AIR COOLED

Starting at
$1.71/GPU HR
Node Spec Summary
Memory: 192 GB HBM3E
Memory Bandwidth: 5.3Tb/s
Infinity Fabric™ Bandwidth Links: 8 x 128 GB/s
FP16: 1.3 PFLOPs | 2.61 PFLOPs with sparsity
INT8: 2.6 POPs | 5.22 POPs with sparsity

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