GPU CAPACITY
8GPUs
Capacity aligned to your model
Eight GPUs per HGX node support the demands of your training or inference workload.
THE AI FACTORY FOR YOUR NEXT LEAP
Train ambitious models, generate and use AI tokens, and run inference in production. TensorBay AIFactory brings NVIDIA GPU systems, high-speed networking, and storage together to support that work.
Start with 8 GPUs from $19.50/hr · yearly reservation

The infrastructure behind AI token generation and use
From model to production, every layer has a role.



02The TensorBay advantage
Every layer of your cluster is designed to give your team more control, more predictability, and more room to build.
Run directly on dedicated hardware, with the machine’s capacity focused on your workload. Take control of performance at every stage of your project.
Dedicated nodes, networking, and storage give your team an exclusive foundation to train, experiment, and put AI to work.
Before delivery, the cluster is tested under load across memory, network, and thermal behavior. Review the results and approve the handover with evidence in hand.
Your drivers, your kernels, your tools. Work with Slurm, Kubernetes, or SSH and shape the environment around your model’s needs.
Spare nodes in the same rack help limit disruption when hardware needs attention.
Published rates, per-minute metering within your reservation, and 20 TB of outbound data included per node each month. Plan with the costs in view.
BUILT FOR THE WORK
TensorBay AIFactory brings compute, networking, storage, power, cooling, and operations together around the work, supporting the full cycle from model training through token generation and use to production inference.
TENSORBAY AIFACTORYCompute is reserved around your model, data path, and delivery window. Networking, storage, and operations are planned alongside the GPU systems.
Network, storage, and acceptance testing are planned together so your team has a clear path from first run to production capacity.
03The Token Factory at work
TensorBay AIFactory brings power, cooling, GPUs, and networking together to support the full AI workload cycle, from model training through token generation and use to production inference.
PUE 1.12
Direct-to-chip liquid cooling in 130 kW racks, designed for intensive AI workloads.
24,000+ GPUs
Capacity expands in six-week cycles, with readiness checks before each handover.
97.4%
Cluster goodput over the last 90 days measures how much capacity became useful work.
INSIDE TENSORBAY AIFACTORY
NEVER BUILD ALONE
Bring your model, capacity goals, and timeline. TensorBay’s team can help shape the configuration and next steps.
Talk to sales
TESTED BEFORE HANDOVER
Every cluster receives load, memory, network, and thermal acceptance tests. Your team reviews the results before approving delivery.
Load · memory · network · thermal checks
AI WORKLOADS
EXPLORE THE AI FACTORY
Go beyond the GPU. Explore how token economics, infrastructure, and the path from model to production fit together.
TOKENOMICS
See how model choices, compute utilization, and application demand interact through generation and use.
What shapes token economics in production?
AI FACTORY
See how GPU compute, power, cooling, networking, storage, and operations come together around your workload.
One system behind every production workload.DATA PATH
Plan high-speed networking and storage around the data path your training and inference workloads depend on.
Keep models and data moving together.08Give your idea room to grow
Bring us your challenge. Our team will help define your GPUs, capacity, and timeline. Get a proposal within 48 hours to launch your project or take it further.