MSI EdgeXpert13S AI Supercomputer Mini Desktop,ARM 20-core ,128 GB ,4TB ,WiFi 7 ,NVIDIA Blackwell Graphics,DGX OS - Black
MSIMSI EdgeXpert MS-C931 · NVIDIA GB10
The desk-side
AI supercomputer.
Built on the NVIDIA GB10 Grace Blackwell Superchip — the same silicon at the core of NVIDIA DGX Spark — with 128 GB of unified memory. Petaflop-scale local AI in a compact, desktop-ready form.
- 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
- GPU
- NVIDIA Blackwell — 5th-gen Tensor Cores, FP4
- AI performance
- Up to 1 petaFLOP FP4 (1000 AI TOPS)
- Unified memory
- 128 GB LPDDR5X — 273 GB/s
- Storage
- 4 TB NVMe M.2, self-encrypting
- Networking
- NVIDIA ConnectX-7 + 10 GbE RJ-45
- Wireless
- Wi-Fi 7 · Bluetooth 5.3
- Rear I/O
- 4× USB-C (USB 3.2) · HDMI 2.1a
- Operating system
- NVIDIA DGX OS (Ubuntu Linux)
- Dimensions
- 151 × 151 × 52 mm · 1.2 kg
Questions
Frequently asked questions
Who is the MSI EdgeXpert for?
Developers, AI researchers and data scientists 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 EdgeXpert itself — GB10 Superchip, 128 GB unified memory, 4 TB NVMe, ConnectX-7 and NVIDIA DGX OS with the AI stack preloaded. Ask us to confirm exact in-box contents.
How is it different from other DGX Spark systems?
Same NVIDIA GB10 platform — the same silicon at the core of NVIDIA DGX Spark — in MSI’s EdgeXpert desktop build (151 × 151 × 52 mm, Wi-Fi 7). Core GB10 performance is shared across the family.
What AI applications does it support?
Generative AI (fine-tuning and running LLMs), computer vision, predictive analytics, and simulation and research — a versatile local AI machine across industries.