Gigabyte ATAGB10-9000 AI TOP ATOM Personal AI Supercomputer,NVIDIA GB10 Blackwell,128GB LPDDR5X, 4TB M2 SSD,DGX OS,Black
GigabyteGIGABYTE AI TOP ATOM · NVIDIA GB10
Petaflop AI,
in one liter.
The NVIDIA GB10 Grace Blackwell Superchip and 128 GB of unified memory in GIGABYTE’s compact, energy-efficient one-liter chassis — petaflop-scale AI for local development, right at your desk.
- GB10 Grace Blackwell
- 128 GB unified memory
- 1 PetaFLOP FP4
- DGX OS
The silicon
GB10 Grace Blackwell Superchip
A 20-core Arm CPU and a Blackwell GPU share one pool of memory over NVLink-C2C — no PCIe bottleneck between them. It is the architecture NVIDIA ships in DGX systems, on your desk.
- 20-core Arm CPU
- Blackwell GPU
- NVLink-C2C
Capacity
Room to run — and to scale
128 GB unified memory
Fine-tune models in the 30–70B range and run inference up to ~200B parameters — one pool, addressed by CPU and GPU alike, nothing to copy or partition.
Cluster when you outgrow one
The built-in NVIDIA ConnectX-7 NIC direct-connects two units — and scales to a four-unit cluster — when a single box isn’t enough.
Who it's for
Built for teams doing real AI work
Owned, local compute for the people who were paying for it by the hour.
Developers & ML researchers
Prototype and fine-tune in the 30–70B range; trade per-run cloud cost for a fixed, owned asset.
Regulated industries
Healthcare, finance and government teams that need on-prem, air-gapped-capable processing.
Research & academia
Capex-budget compute for imaging, genomics, astrophysics and coursework — no recurring cloud bill.
Robotics & edge vision
A local target for NVIDIA Isaac, Metropolis and Holoscan, from sensor processing to assistive tech.
Specifications
Technical specifications
- Superchip
- NVIDIA GB10 Grace Blackwell
- CPU
- 20-core Arm (10× Cortex-X925 + 10× Cortex-A725)
- GPU
- NVIDIA Blackwell — 5th-gen Tensor Cores, FP4
- AI performance
- Up to 1 petaFLOP (FP4)
- Unified memory
- 128 GB LPDDR5X — 273 GB/s
- Storage
- 4 TB NVMe M.2 (PCIe 5.0)
- Networking
- NVIDIA ConnectX-7 (dual 200 Gbps QSFP) + 10 GbE
- Wireless
- Wi-Fi 7 (2×2) · Bluetooth 5.4
- Rear I/O
- 4× USB-C (USB 3.2, 20 Gbps) · HDMI 2.1a · Kensington Nano lock
- Power
- 240 W external adapter (USB-C power in)
- Operating system
- NVIDIA DGX OS (Ubuntu Linux)
- Dimensions
- 150 × 150 × 50.5 mm · 1.2 kg · 1 L chassis
Questions
Frequently asked questions
Who is the GIGABYTE AI TOP ATOM for?
AI developers, ML researchers, regulated-industry data scientists and research labs who want persistent, local AI compute — for fine-tuning in the 30–70B range and inference up to ~200B parameters.
Can it train large models from scratch?
It’s a fine-tuning and inference machine, not a from-scratch training cluster. For pretraining above ~70B parameters, look at NVIDIA DGX Station or a cloud cluster — we can advise on the right step up.
How does it compare to cloud GPUs on cost?
Cloud GPU sessions run roughly $2–$15 each and never stop. This turns that recurring opex into a fixed, owned asset — and keeps sensitive data on-prem.
What comes in the box?
The AI TOP ATOM itself — GB10 Superchip, 128 GB unified memory, 4 TB NVMe, the built-in ConnectX-7 NIC and NVIDIA DGX OS with the AI stack preloaded, plus the 240 W adapter. Ask us to confirm exact in-box contents.
How is it different from other DGX Spark systems?
Same NVIDIA GB10 platform, GIGABYTE build: a compact, energy-efficient one-liter chassis with Wi-Fi 7, Bluetooth 5.4 and a Kensington Nano lock. The core GB10 performance is shared across the DGX Spark family.
What AI applications does it support?
Generative AI (fine-tuning and running LLMs), computer vision (object detection and tracking), predictive analytics, and simulation and research — a versatile local AI machine across industries.