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1Fix the driver behind crashes, sound loss and screen glitches2Clear out junk files and repair common Windows errors3Scan for outdated or missing drivers - takes under a minuteNVIDIA has announced a 64GB version of its DGX Spark compact AI system, with a starting price of $4,999 and availability through manufacturer partners scheduled for October 23, 2026. The new configuration keeps the GB10 Grace Blackwell Superchip and DGX software stack, but halves the unified memory of the 128GB version. NVIDIA says it can run models with up to 100 billion parameters on-device; that is a vendor capability claim, not a guarantee that every such model will fit or run well in every workload.
What is the 64GB NVIDIA DGX Spark?
It is a distinct, lower-memory configuration of NVIDIA DGX Spark, sold through OEM partners rather than directly by NVIDIA. NVIDIA says it retains the same GB10 Grace Blackwell Superchip, DGX OS, and AI software stack as the 128GB configuration. The key announced difference is unified-memory capacity: 64GB instead of 128GB.
NVIDIA names Acer, ASUS, Dell, Gigabyte, HP, and MSI as manufacturers. The announcement does not identify final model names or establish that every manufacturer will offer the same storage, ports, or other system details.
How much does it cost, and when does it go on sale?
NVIDIA announced a starting price of $4,999 and says partner systems are scheduled to become available on October 23, 2026. As of the October 2 announcement, those were forward-looking details: actual inventory, regional pricing, and the prices of individual OEM configurations were not confirmed.
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- Supercomputer performance directly to your desk in a compact, energy-efficient design, enabling enterprise-scale AI and high-performance computing right where you need it.
- The power of Grace Blackwell architecture, delivering up to 1 petaFLOP of AI performance for local model fine-tuning, inference, and analytics, accelerating your time-to-solution.
- Designed from the ground up to build and run AI, delivering seamless integration of the full NVIDIA AI software stack —so you can develop locally and deploy anywhere.
- NVIDIA DGX Spark gives you the freedom to experiment, prototype, and innovate faster by augmenting laptop, desktop, cloud, or data center resources. With more power to learn, prototype, test, and innovate, NVIDIA DGX Spark delivers exceptional ROI for increased productivity.
- Use NVIDIA DGX Spark to unlock new ideas and experiment with large models (up to 200 billion parameters at FP4) directly on your desktop with 128GB of unified memory. Empower rapid testing, validation, and iteration—driving innovation in a secure, high-performance setting.
The $4,999 figure is not a documented earlier price for this 64GB model. Separately, NVIDIA said in February 2026 that it had adjusted the DGX Spark Founders Edition MSRP from $3,999 to $4,699, citing worldwide memory supply constraints. That change applied to the Founders Edition; it does not establish why the new partner configuration starts at $4,999.
What does 64GB mean for local AI workloads?
NVIDIA says one 64GB DGX Spark supports on-device models with up to 100 billion parameters. Parameter count alone does not determine whether a model will fit in memory or how it will perform: the model, quantization, context length, software, and workload all matter. NVIDIA’s announcement does not provide independent test results for this configuration, so treat the 100-billion figure as the company’s stated upper-end support claim rather than a promise about a particular model or response speed.
The practical question is whether the memory available to your intended model and workload is sufficient. If you regularly need more room for model weights, context, or other concurrent work, the 128GB configuration offers twice the stated unified memory. The available sources do not establish a measured performance comparison between a single 64GB system and a single 128GB system.
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Can two DGX Spark systems combine their memory?
NVIDIA says two systems can pool 128GB of memory using ConnectX-7 networking and Sync Cluster Assistant, supporting workloads of up to 200 billion parameters. That is a two-system setup, not a way to expand one 64GB unit by itself; the announcement does not state the total purchase price for such a setup.
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Random freezes, missing sound and display glitches usually trace back to one bad driver. Find and replace yours safely.Free scan · under a minuteNVIDIA also reports up to 1.7x performance for a specific two-system Qwen 3.8 27B test compared with one system. This is NVIDIA’s result for that named test, not an independently verified general scaling figure. It should not be assumed to apply to other models or workloads.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.How does the 64GB announcement compare with the documented 128GB system?
| Detail | 64GB partner configuration | Documented 128GB system |
|---|---|---|
| Unified memory | 64GB, announced by NVIDIA | 128GB LPDDR5x |
| Memory bandwidth | Not stated for the 64GB OEM configurations in NVIDIA’s announcement | 273 GB/s in NVIDIA’s DGX Spark hardware guide |
| Storage | Not specified across OEM configurations in NVIDIA’s announcement | 1TB or 4TB NVMe options in NVIDIA’s hardware guide |
| Connectivity and power | Individual OEM configurations are not fully specified in the announcement | Wi-Fi 7, 10 GbE, ConnectX-7, and a 240W power supply in NVIDIA’s hardware guide |
| Chip and software | GB10 Grace Blackwell Superchip, DGX OS, and AI software stack, according to NVIDIA | Same platform context; NVIDIA says the 64GB model retains the 128GB model’s chip and software stack |
| Price and timing | $4,999 starting price; partner availability scheduled for October 23, 2026, according to NVIDIA | The cited hardware guide does not state a price or availability date |
The 128GB column reflects specifications in NVIDIA’s documentation for its 128GB system. Those details should not be assumed to describe every 64GB model sold by Acer, ASUS, Dell, Gigabyte, HP, or MSI.
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- 140MM FAN MOUNT: Built around a 140 mm fan layout with approximately 124.5 mm hole spacing, creating a defined top-mount position for a compact workstation cooling setup
- SINGLE-PIECE DUCT: One-piece fan shroud forms a simple airflow channel between the upper vent area and a 140 mm fan position, keeping the desktop workstation setup compact
- TOP-MOUNT LAYOUT: Designed to sit above a compatible compact AI workstation, the cooling duct uses the upper device area without requiring a larger external frame
- OPEN AIRFLOW PATH: The central round passage links the workstation vent area with the fan mount, giving the setup a clear physical airflow route without internal moving parts
- COMPACT SIZE: Approx. 157 x 178 x 51 mm body keeps the fan duct close to the workstation, fitting home lab, AI development desk, and compact compute setups
Who should consider the smaller configuration?
The 64GB version may suit buyers whose local AI work fits within a smaller memory budget and who value the same named chip and software stack at a lower starting price than the 128GB system’s separately announced Founders Edition MSRP. That is not a direct price comparison between identical retail configurations: the $4,999 figure is a starting price for partner systems, while $4,699 was NVIDIA’s adjusted Founders Edition MSRP in February 2026.
Before choosing, check the exact OEM SKU and confirm its memory, storage, ports, regional price, and stock. The announcement establishes the 64GB capacity and shared platform claims, but not a complete specification sheet or retail listing for each partner model.
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Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
