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NVIDIA DGX Spark. World’s smallest AI supercomputer with 128GB memory

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Alex Cheema

50,283 subscribers

312,131 просмотров • 1 год назад •via X (Twitter)

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Комментарии: 11

Фото профиля The Highly Automated Cat — e/acc ⏩
The Highly Automated Cat — e/acc ⏩1 год назад

256GB would have been a more direct attack on Apple imo

Фото профиля Alex Cheema - e/acc
Alex Cheema - e/acc1 год назад

Jensen brought out a MacBook. Apple Silicon and NVIDIA hardware will work in unison!

Фото профиля VRLA Tech
VRLA Tech1 год назад

Your next W? A fresh gaming PC. Don’t lose out. 🎮🔥

Фото профиля Ian “Meme” Malcolm
Ian “Meme” Malcolm1 год назад

How much and where do i press the sold out button?

Фото профиля Gordon Shumway
Gordon Shumway1 год назад

I was excited for it but new Mac Studio made it irrelevant. It still can be useful for tasks that require CUDA specifically.

Фото профиля Alex Cheema - e/acc
Alex Cheema - e/acc1 год назад

Waiting for more details to be released but I could see it being better for FLOPS-bound workloads e.g. prefill-heavy inference and finetuning

Фото профиля pr337h4m
pr337h4m1 год назад

can fit a cluster of five of them to power this droid here

Фото профиля Mik
Mik1 год назад

Are we closer to the truth on how this compares to Mac Studio?

Фото профиля dozm
dozm1 год назад

So this is Digits?

Фото профиля Richard
Richard1 год назад

Needs at least 256GB memory.

Фото профиля Jan Koch
Jan Koch1 год назад

I thought it was announced as DIGITS already? Or is this something else?

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When NVIDIA CEO Jensen Huang presented the DGX Spark, then he recalled how, back in 2016, he unveiled the world’s first AI supercomputer, the DGX-1, and how Elon Musk, then at OpenAI, became its first customer. The DGX Spark is far more advanced, delivering five times the computational power of the DGX-1.
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When NVIDIA CEO Jensen Huang presented the DGX Spark, then he recalled how, back in 2016, he unveiled the world’s first AI supercomputer, the DGX-1, and how Elon Musk, then at OpenAI, became its first customer. The DGX Spark is far more advanced, delivering five times the computational power of the DGX-1.

SMX 🇺🇸

13,315,514 просмотров • 9 месяцев назад

We are getting 2 new devices from NVIDIA and Microsoft: 1. The DGX Station, with GB300 superchip and up to 748GB of memory. 2. The RTX Spark laptop, with 1 petaflop of AI performance and 128GB of unified memory. The hardware here is pretty bonkers! Think about it this way:
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We are getting 2 new devices from NVIDIA and Microsoft: 1. The DGX Station, with GB300 superchip and up to 748GB of memory. 2. The RTX Spark laptop, with 1 petaflop of AI performance and 128GB of unified memory. The hardware here is pretty bonkers! Think about it this way:

Santiago

15,204 просмотров • 2 месяцев назад

RIP CPU-based AI supercomputers? NVIDIA just announced DGX GH200, an AI supercomputer that combines whooping 256 Grace CPUs & Hopper GPUs in the same package with 144 Terabytes of shared memory! Here's the breakdown
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RIP CPU-based AI supercomputers? NVIDIA just announced DGX GH200, an AI supercomputer that combines whooping 256 Grace CPUs & Hopper GPUs in the same package with 144 Terabytes of shared memory! Here's the breakdown

Min Choi

769,185 просмотров • 3 лет назад

From rockets to AI. Nine years after the original NVIDIA DGX-1 handoff, Jensen Huang delivered a brand-new DGX Spark to Elon Musk at Starbase. 🚀✨ The DGX Spark is a petaflop powerhouse built for creators, researchers, and developers — a desktop-sized supercomputer with five times the performance of the first DGX-1. Filmed at SpaceX’s rocket factory in Texas, this moment captures a conversation between the two visionariesI. ➡️ 📹 #SparkSomethingBig
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From rockets to AI. Nine years after the original NVIDIA DGX-1 handoff, Jensen Huang delivered a brand-new DGX Spark to Elon Musk at Starbase. 🚀✨ The DGX Spark is a petaflop powerhouse built for creators, researchers, and developers — a desktop-sized supercomputer with five times the performance of the first DGX-1. Filmed at SpaceX’s rocket factory in Texas, this moment captures a conversation between the two visionariesI. ➡️ 📹 #SparkSomethingBig

NVIDIA

3,159,083 просмотров • 10 месяцев назад

Unsloth AI and NVIDIA are Revolutionizing Local LLM Fine-Tuning: From RTX Desktops to DGX Spark Fine-tune popular AI models faster with Unsloth on NVIDIA RTX AI PCs such as GeForce RTX desktops and laptops to RTX PRO workstations and the new DGX Spark to build personalized assistants for coding, creative work, and complex agentic workflows. The landscape of modern AI is shifting. We are moving away from a total reliance on massive, generalized cloud models and entering the era of local, agentic AI. Whether it is tuning a chatbot to handle hyper-specific product support or building a personal assistant that manages intricate schedules, the potential for generative AI on local hardware is boundless. However, developers face a persistent bottleneck: How do you get a Small Language Model (SLM) to punch above its weight class and respond with high accuracy for specialized tasks? The answer is Fine-Tuning, and the tool of choice is Unsloth. Unsloth provides an easy and high-speed method to customize models. Optimized for efficient, low-memory training on NVIDIA GPUs, Unsloth scales effortlessly from GeForce RTX desktops and laptop all the way to the DGX Spark, the world’s smallest AI supercomputer...... Full analysis: NVIDIA NVIDIA AI NVIDIA AIDev NVIDIAnewsroom Unsloth AI Unsloth
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Unsloth AI and NVIDIA are Revolutionizing Local LLM Fine-Tuning: From RTX Desktops to DGX Spark Fine-tune popular AI models faster with Unsloth on NVIDIA RTX AI PCs such as GeForce RTX desktops and laptops to RTX PRO workstations and the new DGX Spark to build personalized assistants for coding, creative work, and complex agentic workflows. The landscape of modern AI is shifting. We are moving away from a total reliance on massive, generalized cloud models and entering the era of local, agentic AI. Whether it is tuning a chatbot to handle hyper-specific product support or building a personal assistant that manages intricate schedules, the potential for generative AI on local hardware is boundless. However, developers face a persistent bottleneck: How do you get a Small Language Model (SLM) to punch above its weight class and respond with high accuracy for specialized tasks? The answer is Fine-Tuning, and the tool of choice is Unsloth. Unsloth provides an easy and high-speed method to customize models. Optimized for efficient, low-memory training on NVIDIA GPUs, Unsloth scales effortlessly from GeForce RTX desktops and laptop all the way to the DGX Spark, the world’s smallest AI supercomputer...... Full analysis: NVIDIA NVIDIA AI NVIDIA AIDev NVIDIAnewsroom Unsloth AI Unsloth

Marktechpost AI Dev News ⚡

31,551 просмотров • 8 месяцев назад

In 2016, Jensen Huang hand-delivered the world’s first AI supercomputer to a startup in San Francisco called OpenAI. The culmination of a decade of work from thousands of NVIDIA engineers, DGX-1 set the stage for a new industrial revolution.
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In 2016, Jensen Huang hand-delivered the world’s first AI supercomputer to a startup in San Francisco called OpenAI. The culmination of a decade of work from thousands of NVIDIA engineers, DGX-1 set the stage for a new industrial revolution.

NVIDIA

61,439 просмотров • 1 год назад

NVIDIA DGX Spark is the most powerful personal AI supercomputer right now. I am running AI agents working for me 24/7 while keeping my data 100% private. In this video I cover the full setup, real benchmarks and tradeoffs. Here's the honest breakdown:
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112,285 просмотров • 4 дней назад

🔬 Fold proteomes privately, no queues, no bottlenecks Bring protein structure prediction to your desktop. Powered by the GB10 Grace Blackwell Superchip, our new NVIDIA DGX Spark will deliver: ⚡ 1 petaFLOP of AI performance 🧠 128 GB coherent unified system memory It’s more than a workstation - it’s a personal AI supercomputer for digital biology. Get ready to #SparkSomethingBig.
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🔬 Fold proteomes privately, no queues, no bottlenecks Bring protein structure prediction to your desktop. Powered by the GB10 Grace Blackwell Superchip, our new NVIDIA DGX Spark will deliver: ⚡ 1 petaFLOP of AI performance 🧠 128 GB coherent unified system memory It’s more than a workstation - it’s a personal AI supercomputer for digital biology. Get ready to #SparkSomethingBig.

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13,606 просмотров • 11 месяцев назад

It's been an amazing week for open models running on NVIDIA Local AI systems! 👀 Here's a few you’ll want to know about, all ready to run locally on NVIDIA RTX, DGX Spark, DGX Station, and Jetson.
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It's been an amazing week for open models running on NVIDIA Local AI systems! 👀 Here's a few you’ll want to know about, all ready to run locally on NVIDIA RTX, DGX Spark, DGX Station, and Jetson.

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59,251 просмотров • 7 дней назад

Qwen3.8 Max UD-Q1_0 4× DGX Spark + llama.cpp/MTP3 53,448 tokens · 1h54m44s · 7.76 tok/s NVIDIA AI Qwen Qwen Developers
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15,149 просмотров • 9 дней назад

Watch Gemma-4-26B running 18 concurrent sessions on a single NVIDIA AI DGX Spark — delivering a cumulative 300 tokens per second. 🔥
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Watch Gemma-4-26B running 18 concurrent sessions on a single NVIDIA AI DGX Spark — delivering a cumulative 300 tokens per second. 🔥

Mia

22,995 просмотров • 1 месяц назад

Here's your weekend project. Build a fully local, sandboxed AI assistant. Step-by-step tutorial to build your always-on agent: 🦞 on OpenClaw🦞 ✅ with NVIDIA NemoClaw ✨ using NVIDIA DGX Spark Get started:
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41,752 просмотров • 4 месяцев назад

This is where it all started. 🚀 Ten years ago at #NVIDIAGTC, the journey of #NVIDIADGX began with our CEO Jensen Huang's announcement of DGX-1, the world’s first AI supercomputer. What started as a single system has since evolved into the universal blueprint for modern AI factories. Relive this momentous beginning and explore where the next decade of AI discovery will take us. Add DGX sessions to your GTC schedule now: #DecadeOfDGX
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34,003 просмотров • 5 месяцев назад

INTEL JUST QUIETLY BUILT THE CHEAPEST PATH TO 128GB OF LOCAL AI VRAM, AND IT BEATS NVIDIA'S DGX SPARK BY 2X FOR THE SAME $4,000 00:11 four Arc Pro B70s racked in one chassis. 32GB of GDDR6 each, $949 MSRP, roughly $1,000 street per card stack four and you get 128GB of VRAM for about $4,000 total. a lab benchmarked the quad against a DGX Spark and a single RTX Pro 6000. the four B70s doubled the Spark or better they trail the Pro 6000, but that card is $10,000. so the real choice is now $4K for 128GB from Intel or $10K for 96GB from NVIDIA the article covers the DGX Spark at $3,999 as the single-desk local AI ceiling. this Intel quad matches the price, beats the memory throughput, and nobody is talking about it yet save this before Intel's VRAM-per-dollar advantage becomes the default homelab build ↓
1:26

INTEL JUST QUIETLY BUILT THE CHEAPEST PATH TO 128GB OF LOCAL AI VRAM, AND IT BEATS NVIDIA'S DGX SPARK BY 2X FOR THE SAME $4,000 00:11 four Arc Pro B70s racked in one chassis. 32GB of GDDR6 each, $949 MSRP, roughly $1,000 street per card stack four and you get 128GB of VRAM for about $4,000 total. a lab benchmarked the quad against a DGX Spark and a single RTX Pro 6000. the four B70s doubled the Spark or better they trail the Pro 6000, but that card is $10,000. so the real choice is now $4K for 128GB from Intel or $10K for 96GB from NVIDIA the article covers the DGX Spark at $3,999 as the single-desk local AI ceiling. this Intel quad matches the price, beats the memory throughput, and nobody is talking about it yet save this before Intel's VRAM-per-dollar advantage becomes the default homelab build ↓

NO1ennn

139,651 просмотров • 1 месяц назад

Super cool to see Jensen NVIDIA showcasing Reachy Mini at his #CES26 keynote. Paired with a DGX Spark & Brev, it can make the perfect local home AI robotics setup!
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Super cool to see Jensen NVIDIA showcasing Reachy Mini at his #CES26 keynote. Paired with a DGX Spark & Brev, it can make the perfect local home AI robotics setup!

clem 🤗

75,599 просмотров • 7 месяцев назад

Jensen Huang hand-delivers the new NVIDIA DGX Spark to Elon Musk at Starbase 2016: Jensen hand-delivered the first DGX-1 to Elon at OpenAI Now: Nearly a decade later, he’s delivering the next generation at Starbase • DGX-1 (2016): 3,000 Watts • DGX Spark (2025): 40 Watts
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Jensen Huang hand-delivers the new NVIDIA DGX Spark to Elon Musk at Starbase 2016: Jensen hand-delivered the first DGX-1 to Elon at OpenAI Now: Nearly a decade later, he’s delivering the next generation at Starbase • DGX-1 (2016): 3,000 Watts • DGX Spark (2025): 40 Watts

X Freeze

20,547 просмотров • 6 месяцев назад

Did you know Qwen 3.6 35B NVFP4 with 256k context, MTP, kv cache fp16 & image support takes around 68gb of VRAM? My NVIDIA AI DGX Spark can do 110 tok/s 👇
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Did you know Qwen 3.6 35B NVFP4 with 256k context, MTP, kv cache fp16 & image support takes around 68gb of VRAM? My NVIDIA AI DGX Spark can do 110 tok/s 👇

Mia

35,255 просмотров • 2 месяцев назад

DGX Spark is here!! My so not unboxing video because I am not a fancy youtuber lol. Just organic me loving tech. NVIDIA AI Developer Micro Center
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DGX Spark is here!! My so not unboxing video because I am not a fancy youtuber lol. Just organic me loving tech. NVIDIA AI Developer Micro Center

Joey

51,391 просмотров • 4 месяцев назад