NVIDIA
NVIDIA 940-54242-0000-000 DGX Spark AI edge system 20-core Arm 128 GB LPDDR5x 4 TB NVME
A compact AI workstation with a 20-core Arm processor, 128 GB LPDDR5x unified memory, 4 TB NVME storage, and Wi-Fi 7 connectivity
- TypeGaming & Entertainment
- UsageConsumer
- Processor20 core Arm, 10 Cortex-X925 + 10 Cortex-A725 Arm
- Processor Main Features64 bit 20-Core Processor
- Memory128 GB LPDDR5x, unified system memory
- StorageUp to 4 TB NVME.M2 with self-encryption
Type NVIDIA DGX Spark
- GMKtec Ryzen Al Max+ 395
- NVIDIA DGX Spark
Struck-through versions exist but are not stocked here.
- Up to 1 petaFLOP of AI compute at FP4 precision with Blackwell architecture
- 128 GB LPDDR5x unified memory runs models up to 200 billion parameters locally
- 20-core Arm CPU (10 Cortex-X925 + 10 Cortex-A725) delivers 64-bit high-performance processing
- 4 TB NVME self-encrypting storage with 10 Gbps LAN and Wi-Fi 7 connectivity
- Pre-installed NVIDIA DGX OS and AI stack enables immediate development, fine-tuning and inference
DGX Spark personal AI computer
The NVIDIA DGX Spark is a desktop AI workstation built on the GB10 Grace Blackwell Superchip. It combines a 20-core Arm processor with 10 Cortex-X925 and 10 Cortex-A725 cores alongside a Blackwell GPU. The system ships with 128 GB of unified LPDDR5x memory and a 4 TB NVME SSD. It runs NVIDIA DGX OS for local AI development, fine-tuning, and inference.
240 W power supply and thermal profile
The unit operates from a 240 W power supply in a compact form factor. Unified memory reduces data movement between CPU and GPU, lowering overall power draw during model workloads. Wi-Fi 7 and Bluetooth 5.4 connectivity add minimal thermal load. The 10 Gbps LAN port supports high-throughput transfers without active cooling noise in typical office environments.
Preinstalled NVIDIA AI software stack
DGX OS includes the full NVIDIA AI software stack pre-optimised for the GB10 Superchip. This enables immediate prototyping with models up to 200 billion parameters using FP4 precision. ConnectX networking allows linking two systems to scale to 405 billion parameter models. The self-encrypting NVME drive protects model weights and datasets at rest.
Highlights
- Up to 1 petaFLOP of AI compute at FP4 precision with Blackwell architecture
- 128 GB LPDDR5x unified memory runs models up to 200 billion parameters locally
- 20-core Arm CPU (10 Cortex-X925 + 10 Cortex-A725) delivers 64-bit high-performance processing
- 4 TB NVME self-encrypting storage with 10 Gbps LAN and Wi-Fi 7 connectivity
- Pre-installed NVIDIA DGX OS and AI stack enables immediate development, fine-tuning and inference
Specifications
| Brand | NVIDIA |
|---|---|
| Model | DGX Spark Founders Edition |
| Part Number | 940-54242-0000-000 |
| Type | Gaming & Entertainment |
| Usage | Consumer |
| Processor | 20 core Arm, 10 Cortex-X925 + 10 Cortex-A725 Arm |
| Processor Main Features | 64 bit 20-Core Processor |
| Memory | 128 GB LPDDR5x, unified system memory |
| Storage | Up to 4 TB NVME.M2 with self-encryption |
| Graphics | NVIDIA Blackwell Architecture |
| Power Supply | 240W |
| Operating System | NVIDIA DGX OS |
| CPU Type | 20-core Arm,10 Cortex-X925 + 10 Cortex A725 |
| Memory Capacity | 128GB LPDDR5x |
| SSD | 4TB NVMe |
| Optical Drive Type | No |
| LAN Speed | 10Gbps |
| WLAN | 802.11be Wireless LAN |
| WiFi Generation | Wi-Fi 7 |
| Bluetooth | Bluetooth 5.4 |
| Video Ports | 1 x HDMI 2.1a |
| Rear USB | 4 x USB Type-C |
| RJ45 | 1 port |
| Dimensions (H x W x D) | 1.99" x 5.91" x 5.91" |
| Weight | 2.65 lbs. |
| Shipping weight | 3.18 kg |
| Package size | 245 × 245 × 152 mm |
Questions about this item
What operating system ships on the system and is it ready for AI development?
NVIDIA DGX OS comes pre-installed and is pre-optimised for AI development, fine-tuning, and inference workloads.
How many AI model parameters can this system handle locally?
The 128 GB unified memory supports models up to 200 billion parameters for local prototyping and inference.
Can two units be linked together for larger models?
Yes, NVIDIA ConnectX networking allows two systems to work together on models up to 405 billion parameters.
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