Services

Hardware and installation

We deliver servers and GPU systems, set them up and put the model into service at your site. Fine-tuning and operation run preferably on your hardware.

Procurement and installation

Servers and GPU systems, from compact devices to made-to-measure HPC GPU servers
Installation with commissioning: setting up the model on your hardware
You can also use your own hardware

Recommended hardware

The following NVIDIA systems serve as a guide for operation on your own hardware. You choose the hardware freely, or we plan and deliver your server, from these systems to individually designed HPC GPU servers.

Recommended

NVIDIA DGX Spark

GB10 Grace Blackwell Superchip

Our recommendation for most: compact as a book, quiet, sits on a shelf and carries your fine-tuned model with headroom.

AI performance: up to 1 petaFLOP (FP4)
Memory: 128 GB unified (CPU + GPU, LPDDR5X)
Processor: 20 Arm cores (GB10)
Concurrent users: small teams, approx. 5–15 active chats smoothly
Storage: 4 TB NVMe
Networking: 10 GbE, Wi-Fi 7, ConnectX-7 (200 Gb/s)
Multi-user: one shared instance
Form factor: 150 × 150 × 50.5 mm, approx. 1.1 litres

More compute

NVIDIA DGX Station

GB300 Grace Blackwell Ultra Superchip

For substantially more compute: several teams, larger models, one device. Data-centre class in a tower under the desk.

AI performance: up to 20 petaFLOPS (FP4)
Memory: 748 GB coherent (incl. HBM3e GPU memory)
Processor: 72-core NVIDIA Grace
Concurrent users: entire departments, 100+ active chats smoothly
Storage: NVMe SSD, configuration-dependent
Networking: ConnectX-8, up to 800 Gb/s
Multi-user: up to 7 isolated instances (MIG)
Form factor: tower, liquid-cooled

User figures: concurrently active chats at our model sizes (9B–27B), conservatively estimated. The systems serve as a guide.

XX? We deliver it fully set up. Hardware from IonKon

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Memory requirements and machine classes in detail