ASUS Ascent GX10-GG0010BN Black 2026
NVIDIA GB10 Grace Blackwell Superchip과 128GB 통합 메모리를 탑재해 1.48kg의 소형 메탈 섀시에서 페타플롭스급 AI 연산 성능을 제공합니다. OpenClaw 및 NemoClaw와 같은 에이전틱 AI 프레임워크를 지원하며, 온디바이스 추론과 샌드박스 실행 환경을 갖춰 보안이 중요한 워크플로우에 최적화되었습니다. DGX OS 기반의 풀스택 개발 환경과 10GbE, Wi-Fi 7 연결성을 제공하여 비공개 로컬 환경에서 대규모 언어 모델을 구축하고 배포하는 AI 개발자에게 적합합니다.
요약
The 30-Second Version
The ASUS Ascent GX10 is a compact AI supercomputer built for developers who need to run massive models locally. Its 128GB of unified memory is best-in-class, but the CPU is mediocre and sustained training hits thermal walls. Only buy it if you're deep into AI development and can find it priced near the low end of its massive $3,800 to $7,800 range.
Pros & Cons
장점
- Massive 128GB unified memory handles huge AI models locally 100th
- Petaflop-scale AI performance in a tiny, stackable chassis 93rd
- Excellent port selection with Thunderbolt, 10GbE, and Wi-Fi 7 87th
- Purpose-built DGX OS with support for agentic AI frameworks 77th
- Runs cool and quiet for its class, perfect for desktop use
단점
- Wildly inconsistent pricing across vendors, watch out for markups
- CPU performance is mediocre for non-AI tasks
- Thermal limits choke sustained heavy training workloads
- Restocking fees make it a risky buy if it doesn't fit your workflow
- 1TB storage is just okay, you'll likely need external drives fast
사용자 의견
The Word on the Street
시간에 따라 사용자 평판이 어떻게 변했는가
독점고객이 실제로 리뷰를 작성한 시점을 기준으로 합니다. 초기의 호평이 유지되었는지 확인할 수 있습니다.
날짜가 있는 고객 리뷰 5건을 기준으로 달력 분기별로 묶었습니다. 기간별 분석은 영어로 제공됩니다.
근거 자료
Performance
Let's be real, this machine is built for one thing: AI. In our database, it scores an 83.8 out of 100 for AI and LLM workloads, which is genuinely impressive for a box this small. The 128GB of unified memory is the absolute best right now, landing in the 100th percentile. That means you can load massive 200-billion-parameter models locally without breaking a sweat, something most desktops can only dream of. The Blackwell GPU is a strong performer too, sitting well above average. But it's not a flawless victory. The 20-core ARM-based CPU is underwhelming for general compute tasks, falling behind most competitors. And if you're thinking of sneaking in some gaming on the side, don't. The gaming score of 67.2 is a weak spot, so stick to training models, not playing them.
Specifications
Full Specifications
Processor
| CPU | NVIDIA GB10 |
| Cores | 20 |
| Frequency | 2.8 GHz |
Graphics
| GPU | NVIDIA Blackwell Architecture |
| Type | Discrete |
| VRAM | 128 GB |
| VRAM Type | LPDDR5X |
Memory & Storage
| RAM | 128 GB |
| RAM Generation | DDR5 |
| Storage | 1000 GB |
| Storage Type | NVMe SSD |
Build
| Form Factor | mini |
| PSU | 240 |
| Weight | 1.5 kg / 3.3 lbs |
Connectivity
| USB-C Ports | 4 |
| USB Ports | 4 |
| Thunderbolt | Not stated |
| HDMI | 1 x HDMI 2.1 |
| DisplayPort | 0 |
| Wi-Fi | Wi-Fi 7 |
| Bluetooth | ✓ |
| Ethernet | Gigabit Ethernet |
System
| OS | NVIDIA DGX OS |
vs Competition
The ASUS Ascent GX10 exists in a strange no-man's land. Compared to a traditional desktop like the HP Omen 45L or Lenovo Legion 34IAS10, the GX10 gets absolutely smoked in gaming and general CPU grunt. Those towers are for gamers and creators who need a big GPU for rendering or frame rates. The GX10 is for AI devs who need a local LLM beast. Its real rival is the Apple Mac Studio M4 Max. Both are compact, unified-memory powerhouses, but the Mac Studio is a far more polished, general-purpose machine with a much better CPU. The GX10 fights back with its native CUDA ecosystem and DGX software stack, which is non-negotiable for many AI workflows. The MSI MEG Vision X AI tries to bridge the gap with a big RTX GPU, but it can't touch the GX10's 128GB of unified memory for model capacity.
| Spec | ASUS Ascent GX10-GG0010BN | Lenovo Legion 34IAS10 | HP OMEN GT22-3080 | MSI MEG Vision X AI 2NVZ9-045US | Corsair ONE i600 | CLX Horus TGMHORRTU5103BM |
|---|---|---|---|---|---|---|
| CPU | NVIDIA GB10 | Intel Core Ultra 9 | Intel Core Ultra 7 265K | Intel Core Ultra 9 | Intel Core Ultra 9 285K | Intel Core Ultra 9 285K |
| RAM (GB) | 128 | 64 | 32 | 64 | 64 | 96 |
| Storage (GB) | 1000 | 3072 | 2048 | 2048 | 2048 | 10000 |
| GPU | NVIDIA Blackwell Architecture | NVIDIA GeForce RTX 5080 | NVIDIA GeForce RTX 5080 | NVIDIA GeForce RTX 5090 | NVIDIA GeForce RTX 5080 | NVIDIA GeForce RTX 5080 |
| Form Factor | mini | mid-tower | mid-tower | mid-tower | desktop | mid-tower |
| Psu W | 240 | 1200 | 850 | 1300 | 1000 | 850 |
| OS | NVIDIA DGX OS | Windows 11 Pro | Windows 11 Pro | Windows 11 Pro | Windows 11 Home | Windows 11 Home |
| Compare | Compare | Compare | Compare | Compare |
| 제품 | CPU | GPU | RAM | 포트 | 저장 공간 | 신뢰성 | 사용자 평판 |
|---|---|---|---|---|---|---|---|
| ASUS Ascent GX10-GG0010BN | 37.6 | 76.5 | 99.5 | 92.5 | 63.6 | 36.4 | 87.1 |
| Lenovo Legion 34IAS10 Compare | 97.6 | 88 | 96.7 | 91.7 | 96.5 | 69.7 | 84.8 |
| HP OMEN GT22-3080 Compare | 96.1 | 88 | 79 | 93.2 | 91.6 | 69.7 | 87.6 |
| MSI MEG Vision X AI 2NVZ9-045US Compare | 97.6 | 89.8 | 97.6 | 98.2 | 91.6 | 36.4 | 87.4 |
| Corsair ONE i600 Compare | 97.6 | 88 | 98 | 97.4 | 91.6 | 31.3 | 0 |
| CLX Horus TGMHORRTU5103BM Compare | 97.6 | 88 | 98.6 | 96.1 | 99.5 | 11.1 | 87.1 |
가격
Value & Pricing
Value here is a moving target. We've seen this unit listed everywhere from $3,800 to a staggering $7,837. At the lower end, it's a compelling entry point into a dedicated NVIDIA DGX environment. At the high end, you're getting into territory where a more powerful traditional workstation or cloud compute credits start to make a lot more sense. If you're buying, shop around aggressively. Best Buy seems to have the most grounded pricing with a price match guarantee, which makes it the safest bet. For pure AI prototyping, the value is there if you snag it near MSRP. For anything else, it's a tough sell.
Amazon.co.jp 가격 1개 최저 JP¥787,837
2026년 5월 30일부터 이 제품의 가격을 추적하고 있습니다. 데이터가 쌓이면 차트가 표시됩니다.
더 보기
Overview
The ASUS Ascent GX10 is not your typical mini PC. This thing is a full-blown AI workstation crammed into a 1.48kg stackable metal box. Built around the NVIDIA GB10 Grace Blackwell Superchip, it pairs a 20-core Grace CPU with a Blackwell GPU packing 128GB of unified LPDDR5x memory. If you're an AI developer looking for a dedicated local rig to prototype and run agentic workflows, this is aimed squarely at you. It runs NVIDIA DGX OS and supports frameworks like OpenClaw and NemoClaw for private, sandboxed inference right on your desk. Just know that with a price tag that can swing wildly from around $3,800 to over $7,800 depending on the seller, this is a serious investment for a very specific audience.
Common Questions
Q: Is the ASUS Ascent GX10 good for gaming?
No, the ASUS Ascent GX10 is not good for gaming. It scores poorly in our gaming benchmarks and is built specifically for AI development, not running the latest AAA titles.
Q: Can the ASUS Ascent GX10 run large language models?
Yes, it excels at running large language models. The 128GB of unified memory lets you load models with up to 200 billion parameters entirely on-device for private inference.
Q: How does the ASUS Ascent GX10 compare to a Mac Studio?
The Mac Studio M4 Max is a better all-around computer with a stronger CPU for general tasks, but the ASUS Ascent GX10 offers a native NVIDIA CUDA environment and more unified memory, which is crucial for many AI development workflows.
Q: What operating system does the ASUS Ascent GX10 use?
It runs NVIDIA DGX OS, a specialized Linux-based operating system designed for AI workloads, with support for frameworks like OpenClaw and NemoClaw.
Who Should Skip This
Skip the ASUS Ascent GX10 if you're a gamer, video editor, or general content creator. A traditional desktop like the HP Omen 45L or a Mac Studio will serve you much better for those tasks. You should also skip it if your AI work involves heavy, sustained training runs, as the thermal design will bottleneck performance. If you're just curious about AI and want to dabble, a powerful consumer GPU in a standard PC is a far more flexible and cost-effective starting point.
Verdict
Should you buy the ASUS Ascent GX10? If you're an AI developer who needs to run, fine-tune, and deploy large language models locally without touching the cloud, and you find it for a price near $3,800, it's a fascinating and powerful tool. The ability to have a private, petaflop-scale sandbox on your desk is the whole point, and it delivers on that promise for inference and light training. But if your workflow involves heavy, sustained training runs, the thermal limits will frustrate you. And if you just want a fast computer for video editing or gaming, this is absolutely the wrong machine. It's a specialized instrument, not a Swiss Army knife.