Nvidia Launches 64GB DGX Spark at $4,999 as Memory Shortage Drives New AI Hardware Strategy
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Set Up Your At-Home AI Lab With the Compact NVIDIA DGX Spark 64GB
The age of agentic AI, in which systems can be fully autonomous and act on their own, has arrived. And as the availability of open models that fit into the VRAM of a single GPU grows, so does the number of developers, students, and AI tinkerers looking to build and run their own tools. But the
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Nvidia introduces 64GB DGX Spark to throw local AI fans a lifeline amid the RAMpocalypse -- new GB10 config starts at $4999 for those who can work with less
Nvidia is tailoring its popular DGX Spark platform and the GB10 SoC to better fit the realities of today's AI models and the broader silicon supply crunch. The company is introducing a 64GB version of the Spark that's meant to be more affordable to local AI trailblazers who just don't need 128GB of
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Nvidia debuts $4,999 DGX Spark with half the RAM and storage, amid memory crunch
In an effort to provide a more affordable AI system, Nvidia is introducing a cut down version of the DGX Spark with half the memory and storage. The GB10-based systems will be offered exclusively through hardware partners including Acer, Asus, Dell, Gigabyte, HP, and MSI, and are expected to retail
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Nvidia's DGX Spark is getting a 64GB RAM variant to make running local models more affordable
* Nvidia launches 64GB DGX Spark using the same GB10 Grace Blackwell Superchip as the 128GB model. * 64GB Spark is priced at $4,999 as a budget entry option vs. the pricier 128GB model. * Sync Cluster Assistant lets you link Sparks to share RAM (e.g., 2×64GB→128GB or 4×128GB→512GB). If you're an
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Facing Memory Crunch, Nvidia Creates 64GB RTX Spark. It Still Costs $4,999
The ongoing memory shortage has prompted Nvidia to create a 64GB version of its DGX Spark mini PC, which runs AI models locally. The only problem? The upcoming product costs even more than the original 128GB model did when it launched a year ago. The 64GB version launches on Friday, Oct. 23,
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NVIDIA DGX Spark 64GB Gives Developers More Ways to Build and Scale Local AI
Local AI is becoming more useful by the token. As AI agents move from experiments into everyday development, increasingly capable open models are shrinking to fit on more devices, giving builders more to run locally. Coming this month, NVIDIA DGX Spark will be available with 64GB of unified
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NVIDIA DGX Spark 64GB is for people who want to build with AI, not just use it
NVIDIA's compact AI system is designed for people who want to stop merely using models and start building with them. An AI enthusiast can spend an unreasonable amount of time trying to make a model do something it wasn't quite designed to do. Feed it a private collection of documents. Give it a
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IDIA Launches 64GB DGX Spark Desktop AI System for $4,999
NVIDIA has announced a 64GB version of its DGX Spark desktop AI system, priced from $4,999. Sales are scheduled to begin on October 23. The company has also updated the price of the 128GB Founder's Edition to $6,950. Acer, Dell, ASUS, Gigabyte, MSI and H3C are expected to release complete systems
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NVIDIA's 64 GB DGX Spark "AI Supercomputer" Launches This Month For $4999, While The 128 GB Spark Jumps Past $6000
NVIDIA is launching a new version of its DGX Spark AI Supercomputer which packs half the memory, but is priced the same as the 128 GB model. DGX Spark Prices Jump Astronomically Due to Rising Memory Costs, So NVIDIA Is Releasing A New 64 GB Model That Is Priced The Same As The 128 GB Model Last
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Nvidia unveils a 64GB version of its DGX Spark AI supercomputer priced at $4,999, responding to skyrocketing memory costs while maintaining the powerful GB10 Grace Blackwell Superchip. The new configuration targets developers and students running local AI models, offering a more accessible entry point as the 128GB variant now costs up to $9,000.
Nvidia Responds to Memory Crisis With New 64GB Configuration
Nvidia is launching a 64GB version of its DGX Spark on October 23, priced at $4,999
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. This new configuration of the AI supercomputer addresses the ongoing memory crunch that has pushed prices of the original 128GB model from its initial $3,999 launch price to between $7,000 and $9,0003
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. The 64GB DGX Spark ships from OEM partners including Acer, ASUS, Dell, Gigabyte, HP, and MSI1
, making local AI development more accessible to developers, students, and enthusiasts who don't require enterprise-grade memory capacity.
Source: NVIDIA
GB10 Superchip Powers Affordable Local AI Hardware
The DGX Spark 64GB retains the same Nvidia GB10 Superchip architecture as its 128GB counterpart, featuring a 20-core Arm CPU and Blackwell GPU with fifth-generation Tensor Cores
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. The Grace Blackwell Superchip delivers up to one petaflop of AI compute and maintains 273 GB/s of memory bandwidth through coherent unified memory2
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. This shared memory architecture eliminates data duplication between system RAM and VRAM, accelerating workflows for inference and fine-tuning tasks1
. The system supports running local models up to roughly 100 billion parameters, compared to 200 billion on the 128GB version5
.
Source: Digital Trends
Running Local Models Becomes More Practical
The shift toward 64GB RAM reflects rapid AI development progress. Highly capable dense models like Qwen 3.8 27B, Meta Muse Glimmer, and Nvidia Nemotron 3.5 Lightning now deliver performance comparable to frontier models from months ago while fitting comfortably within 64GB of memory
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. Models in the 30-35 billion parameter range are now sufficient for local AI inference powering autonomous agents3
. Running local AI eliminates per-token cloud inference fees, keeps data and models on-device for improved security, and enables developers to experiment freely without cloud costs accumulating1
. This proves particularly valuable for freelance developers and students working within budget constraints.Sync Cluster Assistant Enables Scalable AI Development
Nvidia is introducing the Sync Cluster Assistant, a new software tool that automates the process of clustering multiple DGX Spark systems together
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. The 64GB model includes built-in ConnectX-7 networking, allowing users to cluster two 64GB systems to achieve 128GB of unified memory or link four 128GB units for 512GB capacity1
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. Two clustered 64GB systems provide up to 1.7 times the performance of a single 128GB unit, with twice the AI compute and memory bandwidth reaching 546GB per second1
. Nvidia is also adding Model Launcher to Sync, which automatically downloads and deploys models like Qwen 3.8 27B across clustered systems2
.Related Stories
Memory Shortage Reshapes AI Hardware Landscape
The memory crunch has fundamentally altered pricing expectations across AI hardware. Nvidia previously raised the 128GB DGX Spark price from $3,999 to $4,699 in February, citing memory supply constraints
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. The company then adjusted it again to $6,9503
, representing a nearly 75 percent increase from a year ago. Major supplier Micron expects the memory crunch to worsen through 2027 and 2028, stating "we do not have line-of-sight to when supply and demand will return to balance"5
. This volatile market makes the $4,999 price point for 64GB potentially attractive in retrospect, though it still represents $1,000 more than the original 128GB launch price5
. Interested consumers have reported difficulty finding 128GB versions in stock, with Nvidia's own model remaining unavailable5
.Competition and Future RTX Spark Implications
The pricing pressure affects Nvidia's broader product strategy. RTX Spark notebooks and mini PCs based on the same GB10 silicon, announced at Computex for general computing tasks like gaming and content creation, could now sell for significantly more than anticipated
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. Nvidia faces competition from AMD's Gorgon Halo SoCs, which offer memory capacities from 32GB to 192GB for the Ryzen AI Max+ 495 SKUs at prices currently below the 128GB DGX Spark3
. However, testing consistently shows the GB10's GPU delivers substantially higher performance for AI development tasks3
. AMD's alternative starts at $3,999, offering another option for budget-conscious developers5
. Watch for how memory pricing evolves through 2027 and whether Nvidia adjusts its RTX Spark launch strategy accordingly.
Source: Guru3D
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