Adamant Custom
Adamant Custom 24-Core Core Ultra 9 285K 192GB DDR5 8TB NVMe RTX 5070 Ti gaming PC
A 24-core Intel Core Ultra 9 285K desktop with 192GB DDR5, 8TB NVMe storage and an RTX 5070 Ti 16GB GPU, liquid-cooled in a Corsair 4000D tower running Windows 11 Pro
- Release Year2026
- Form FactorTower
- AI FeaturesAI Ready
- ColorBlack
- Cooling SystemLiquid Cooling
- Operating SystemWindows 11 Pro
- 24-core Intel Core Ultra 9 285K handles heavy rendering and AI workloads
- 192GB DDR5 memory supports large datasets and multitasking without bottlenecks
- 8TB NVMe storage across two Samsung 990 PRO drives delivers fast read and write speeds
- RTX 5070 Ti 16GB GPU accelerates creative and AI applications
- 360mm liquid cooler keeps the CPU quiet under sustained load
Workstation-class 24-core desktop
This Adamant Custom tower pairs a 24-core Intel Core Ultra 9 285K processor with 192GB of DDR5 memory and an 8TB NVMe array built from two Samsung 990 PRO drives. The GeForce RTX 5070 Ti adds 16GB of video memory for rendering, modelling and AI learning workloads. Windows 11 Pro is pre-installed on the system drive.
Pre-assembled liquid-cooled tower
The PC arrives fully built with a 360mm quiet-edition AIO cooler mounted on the LGA 1851 socket and a Thermaltake Smart 850W 80 PLUS Bronze power supply already wired. The Corsair 4000D chassis provides front-panel USB 3.2 Type-C and audio, while the Gigabyte Z890 UD motherboard adds rear USB4 Type-C, 2.5Gb Ethernet, Wi-Fi 6E and Bluetooth 5.3. No component installation is required unless you add extra drives to the two internal 3.5-inch or 2.5-inch bays.
Sustained-load thermal and power behaviour
Under continuous multi-core loads the 24-core CPU can reach 5.70 GHz while the 360mm liquid loop keeps temperatures in check without excessive fan noise. The 850W Bronze-rated PSU delivers stable power to the CPU and RTX 5070 Ti through prolonged render or compute sessions. The Samsung 990 PRO SSDs maintain sequential reads up to 7450 MB/sec and writes up to 6900 MB/sec during extended data transfers.
주요 특징
- 24-core Intel Core Ultra 9 285K handles heavy rendering and AI workloads
- 192GB DDR5 memory supports large datasets and multitasking without bottlenecks
- 8TB NVMe storage across two Samsung 990 PRO drives delivers fast read and write speeds
- RTX 5070 Ti 16GB GPU accelerates creative and AI applications
- 360mm liquid cooler keeps the CPU quiet under sustained load
사양
| Release Year | 2026 |
|---|---|
| Form Factor | Tower |
| AI Features | AI Ready |
| Color | Black |
| Cooling System | Liquid Cooling |
| Operating System | Windows 11 Pro |
| Windows 11 | Ready |
| CPU Type | Intel Core Ultra 9 (Series 2) |
| CPU Name | Intel Core Ultra 9 285K |
| CPU Socket Type | LGA 1851 |
| GPU/VGA Type | GeForce RTX 5070 Ti |
| Memory Capacity | 192GB DDR5 |
| Memory Slots (Available/Total) | 4 total |
| Maximum Memory Supported | 192 GB |
| SSD | 8TB NVMe |
| HDD | No |
| Optical Drive Type | No |
| Screen Size | No Screen |
| Audio Chipset | Integrated |
| Audio Channels | 7.1 channels |
| LAN Chipset | Integrated |
| LAN Speed | 2.5Gbps |
| WLAN | 802.11ax Wireless LAN |
| WiFi Generation | Wi-Fi 6E |
| Bluetooth | Bluetooth 5.4 |
| RJ45 | 1 port |
이 상품에 대한 질문
How can I confirm the Intel Core Ultra 9 285K is running at its 5.70 GHz boost clock under load?
Open Task Manager or a hardware monitor while running a heavy render or AI workload; the CPU frequency should reach 5.70 GHz on active cores and the 360 mm liquid cooler should keep temperatures stable.
What components are included and what must I add to start working?
The tower ships fully assembled with the 24-core CPU, 192 GB DDR5, 8 TB NVMe storage (two 4 TB Samsung 990 PRO drives), RTX 5070 Ti 16 GB GPU, Windows 11 Pro, liquid cooling, 850 W PSU, Wi-Fi 6E and Bluetooth 5.3; only a monitor, keyboard and mouse are needed.
Which memory capacity should I choose for 3D modelling and AI training?
The system already provides the maximum supported 192 GB DDR5 across four slots, which is the highest capacity this platform allows and is ideal for large scene files and model training.
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