Gigabyte AI TOP ATOM ATAGB10-9000 2025, NVIDIA GB10, 128GB, 4TB SSD, Dark Blue

★★★★☆ 4.0 (3)

Der NVIDIA GB10 Grace Blackwell Superchip liefert Petaflop-Leistung in einem Mini-Gehäuse von 1,20 kg, mit 128 GB LPDDR5x und 4 TB NVMe-SSD. Die umfangreiche Anbindung, Thunderbolt, 4x USB-C, HDMI 2.1a, 10G Ethernet und Wi-Fi 7, macht ihn zu einer mobilen Workstation für lokale KI. Am besten geeignet für Entwickler und Kreative, die KI-Modelle trainieren, inferieren und bereitstellen möchten, ohne auf Cloud-Ressourcen angewiesen zu sein.

CPU NVIDIA GB10
RAM 128 GB
Storage 4 TB
GPU NVIDIA
Form Factor mini
psu w 240
OS NVIDIA DGX
Gigabyte AI TOP ATOM ATAGB10-9000 2025, NVIDIA GB10, 128GB, 4TB SSD, Dark Blue desktop
62 Gesamtbewertung
Auch erhältlich in:

Überblick

The 30-Second Version

Monster specs in a tiny box, but the onboarding is a dumpster fire and real-world AI performance disappoints. Buy it cheap or don't buy it at all.

Pros & Cons

Vorteile

  • 128GB of LPDDR5x RAM is absolutely top-tier 99th
  • 4TB PCIe 5.0 SSD gives you serious local storage 98th
  • Tiny 1.2kg footprint for a full AI workstation 84th
  • Wi-Fi 7 and dual 200G QSFP112 ports for fast networking

Nachteile

  • Onboarding is a mess, connectivity issues galore
  • Memory bandwidth cripples real-world inference speed
  • Reliability scores are near the bottom of our database
  • Price swings wildly between vendors

Was Besitzer sagen

The Word on the Street

4.0/5 (3 reviews)
👎 Multiple owners are frustrated with the onboarding process, blaming NVIDIA's software for unstable connectivity and router issues.
🤔 Build quality gets praise, but the actual AI inference speed falls well short of what the specs suggest.

Die Fakten

Performance

The specs here are wild for the size. 128GB of RAM puts this in the top 1% of all products we track, and the 4TB NVMe drive is right behind at the 98th percentile. The 20-core GB10 CPU and Blackwell GPU both land in the mid-80s percentile range, which is impressive for a box this small. But here's the surprise: one owner reports inference speeds about half of what an RTX 3080 delivers, and they blame the memory bandwidth. That's a real letdown when the whole pitch is petaflop-scale performance. The hardware looks great on paper, but real-world AI workloads aren't hitting the numbers you'd expect from the marketing.

Performance Percentiles

CPU 52.5
GPU 84.2
RAM 98.9
Anschlüsse 49.3
Speicher 98.2
Zuverlässigkeit 11.6
Nutzerresonanz 16.5

Specifications

Full Specifications

Processor

CPU NVIDIA GB10
Cores 20
Frequency 3.3 GHz

Graphics

GPU NVIDIA
Type Discrete

Memory & Storage

RAM 128 GB
RAM Generation DDR5
Storage 4 TB
Storage Type NVMe SSD

Build

Form Factor mini
PSU 240
Weight 1.2 kg / 2.6 lbs

Connectivity

USB-C Ports 4
Thunderbolt USB 4
HDMI 1x HDMI 2.1a
Wi-Fi Wi-Fi 7
Bluetooth Bluetooth 5.3
Ethernet 10 GbE

System

OS NVIDIA DGX

vs Competition

The Apple Mac Studio M3 Ultra is the obvious alternative if you want a polished, reliable mini workstation that just works. Apple's unified memory architecture handles large models well, and the onboarding is painless. The Lenovo Legion Tower 5a Gen 10 and Alienware Aurora ACT1250 are bigger, cheaper, and more flexible if you don't need the AI-specific hardware. The ATOM's advantage is the GB10 Superchip and that massive 128GB of RAM, but you're trading reliability and ease of use for that raw spec sheet.

Spec Gigabyte AI TOP ATOM ATAGB10-9000 Apple Mac Studio M3 Ultra Lenovo T Series Towers Legion Tower 5a Gen 10 Dell Desktop ECT1250 HP OMEN GT16-0364 CLX SET TGMSETRTU5204BM
CPU NVIDIA GB10 Apple M3 Ultra AMD Ryzen 7 7800X3D Intel Core Ultra 7 265 AMD Ryzen 7 8700F Intel Core i9 14900KF
RAM (GB) 128 96 32 32 32 64
Storage (GB) 4096 1024 4096 2048 1024 8192
GPU NVIDIA Apple M3 Ultra 60-core NVIDIA GeForce RTX 5070 Ti Intel UHD Graphics NVIDIA GeForce RTX 5070 NVIDIA GeForce RTX 5070
Form Factor mini sff mid-tower sff mid-tower mid-tower
Psu W 240 - 850 180 850 850
OS NVIDIA DGX macOS Windows 11 Home Windows 11 Home Windows 11 Home Windows 11 Home
Compare Compare Compare Compare Compare
Produkt CPUGPURAMAnschlüsseSpeicherZuverlässigkeitNutzerresonanz
Gigabyte AI TOP ATOM ATAGB10-9000 52.584.298.949.398.211.616.5
Apple Mac Studio M3 Ultra Compare 99.77695.793.853.799.386.3
Lenovo T Series Towers Legion Tower 5a Gen 10 Compare 73.693.178.188.498.270100
Dell Desktop ECT1250 Compare 88.658.781.874.582.97099.1
HP OMEN GT16-0364 Compare 69.889.387.39853.77099.1
CLX SET TGMSETRTU5204BM Compare 9589.396.584.299.211.694.8

Preis

Value & Pricing

Pricing is all over the place. In the US, you'll see listings from $4,700 to $9,000, and in Canada the spread is even worse at $5,457 to $15,027. Memory Express has the best Canadian deal by a wide margin. If you're paying anywhere near the top of that range, you're getting fleeced. At the low end, this is a compelling local AI box. At the high end, you're better off building a workstation with a stack of consumer GPUs.

Ab 9.000 $ 1 Angebot bei 1 Händler
Amazon 1 Angebot Ab 9.000 $

Price History

2.000 $ 4.000 $ 6.000 $ 8.000 $ 10.000 $ 3. Mai16. Juni14. Aug.21. Okt. 9.000 $

Mehr erfahren

Overview

The Gigabyte AI TOP ATOM is a tiny box with a huge promise: petaflop-scale AI work on your desk, no cloud required. It packs NVIDIA's GB10 Grace Blackwell Superchip, 128GB of LPDDR5x RAM, and a 4TB PCIe 5.0 SSD into a 1.2kg mini workstation. The one thing to know? This is a developer's dream machine for local AI training and inference, but the onboarding experience is rough enough to make you question the whole purchase.

Common Questions

Q: Can this replace a cloud GPU instance for AI training?

For smaller models and prototyping, yes. The 128GB of RAM lets you load models that would choke most consumer GPUs. But if you need serious throughput, the memory bandwidth will hold you back. Think of it as a local dev box, not a data center replacement.

Q: Is the setup really that bad?

From what we're seeing, yes. The hardware is solid, but the NVIDIA DGX OS onboarding has connectivity problems that multiple owners have hit. Expect to spend time troubleshooting your network setup before you get to the fun part.

Q: How does it compare to a Mac Studio for AI work?

The Mac Studio M3 Ultra is more reliable and easier to set up, and Apple's unified memory is no joke. But the ATOM has more raw RAM and NVIDIA's CUDA ecosystem, which still matters for a lot of AI frameworks. If you value your time, go Mac. If you need CUDA and max RAM, the ATOM is the play.

Who Should Skip This

If you want a plug-and-play workstation that just works out of the box, this isn't it. Go get a Mac Studio M3 Ultra and save yourself the headache. And if you're a gamer or general content creator, the ATOM is overkill and overpriced. A Lenovo Legion Tower or Alienware Aurora will serve you better for less money.

Verdict

If you're a developer who needs a local AI box and you're willing to fight through the setup, the ATOM delivers specs you can't get elsewhere at this size. But the onboarding issues and weak reliability scores are red flags. Buy it only if you find it at the low end of the price range and you're comfortable troubleshooting. Everyone else should wait for NVIDIA to sort out the software or look at the Mac Studio.

Usage Scores

Gesamt (62.2)AI/LLM (40.7)Gaming (62.4)Mobilität (55.7)Kreative (64.9)Business (49.3)Entwicklung (64.6)Home Office (62.5)Workstation (64.6)
  • Gesamt62.2
  • AI/LLM40.7
  • Gaming62.4
  • Mobilität55.7
  • Kreative64.9
  • Business49.3
  • Entwicklung64.6
  • Home Office62.5
  • Workstation64.6

Ähnliche Produkte