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CHINESE DEVELOPER JUST DROPPED A FULL 8-MINUTE SETUP GUIDE FOR THE NVIDIA DGX SPARK - AND SHOWED EXACTLY HOW TO RUN AI AGENTS AND ROBOTICS SIMULATIONS ON IT he unboxed the DGX Spark on camera - plugged in power, keyboard and ethernet and was inside the system within minutes...

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Sprytix

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57,210 Aufrufe • vor 20 Tagen •via X (Twitter)

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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.
1:58

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 🇺🇸

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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
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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

2,992,337 Aufrufe • vor 8 Monaten

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
0:40

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 Aufrufe • vor 6 Monaten

I set up the Hermes Agent on my NVIDIA DGX Spark and had it sending cold outreach emails for BridgeMind in under 20 minutes. Self-improving AI agent. It completes tasks, evaluates results, creates skills, and gets better on its own. No micromanaging. OpenClaw got the hype. Hermes got the architecture right. Full setup and demo below.
15:10

I set up the Hermes Agent on my NVIDIA DGX Spark and had it sending cold outreach emails for BridgeMind in under 20 minutes. Self-improving AI agent. It completes tasks, evaluates results, creates skills, and gets better on its own. No micromanaging. OpenClaw got the hype. Hermes got the architecture right. Full setup and demo below.

BridgeMind

29,260 Aufrufe • vor 2 Monaten

This afternoon I picked up a new Nvidia DGX Spark computer with the goal of trying to run Gemma 4 31b (4bit) on it locally as a server. Just 1.5 hours later, it’s working! Using Open WebUI on my MacBook as the interface and it’s connecting to my DGX Spark running as a Gemma 4 server.
0:46

This afternoon I picked up a new Nvidia DGX Spark computer with the goal of trying to run Gemma 4 31b (4bit) on it locally as a server. Just 1.5 hours later, it’s working! Using Open WebUI on my MacBook as the interface and it’s connecting to my DGX Spark running as a Gemma 4 server.

Dave Lee

137,810 Aufrufe • vor 2 Monaten

This guy plugged a DGX Spark (the $3K Nvidia box) and a Mac Mini M4 together to run AI and what happened next surprised everyone > the Nvidia box handles the hard part - processing your prompt in milliseconds > Mac Mini M4 handles the fast part - generating the response at memory bandwidth speeds nothing else can match > together they hit 84 tokens per second on Llama - 6x faster than the Spark alone > running compute agents locally on this setup means your data never leaves your hardware > two boxes. two different architectures. one AI system that Deepseek runs at data center scale he ran it on his desk save this. the way we build local AI is about to change
18:41

This guy plugged a DGX Spark (the $3K Nvidia box) and a Mac Mini M4 together to run AI and what happened next surprised everyone > the Nvidia box handles the hard part - processing your prompt in milliseconds > Mac Mini M4 handles the fast part - generating the response at memory bandwidth speeds nothing else can match > together they hit 84 tokens per second on Llama - 6x faster than the Spark alone > running compute agents locally on this setup means your data never leaves your hardware > two boxes. two different architectures. one AI system that Deepseek runs at data center scale he ran it on his desk save this. the way we build local AI is about to change

Mr. Buzzoni

153,102 Aufrufe • vor 22 Tagen

NVIDIA sent us 2 DGX Sparks. For a while we wondered what we would do with them. The memory bandwidth is 273GB/s making it 3x slower than an M3 Ultra (819GB/s) for batch_size=1 inference. But it has 4x more FLOPS (100 TFLOPS compared to 26 TFLOPS). So we thought, what if we could combine the DGX Spark & M3 Ultra, and make use of both the massive compute on the DGX Spark and the massive memory-bandwidth on the M3 Ultra. We came up with a way to split inference across both devices and achieve a speedup of up to 4x for long prompts compared to the M3 Ultra on its own. Full details in the blog post linked below.
1:13

NVIDIA sent us 2 DGX Sparks. For a while we wondered what we would do with them. The memory bandwidth is 273GB/s making it 3x slower than an M3 Ultra (819GB/s) for batch_size=1 inference. But it has 4x more FLOPS (100 TFLOPS compared to 26 TFLOPS). So we thought, what if we could combine the DGX Spark & M3 Ultra, and make use of both the massive compute on the DGX Spark and the massive memory-bandwidth on the M3 Ultra. We came up with a way to split inference across both devices and achieve a speedup of up to 4x for long prompts compared to the M3 Ultra on its own. Full details in the blog post linked below.

Alex Cheema

281,225 Aufrufe • vor 8 Monaten

Anthropic engineer showed how one person can run 5 AI agents, that code, test, review, and deploy at the same time. In 30 minutes they built the whole thing live in one session. Here's what they cover: > when to use one agent vs a full team > how to split work so agents don't step on each other > the exact framework for deciding what each agent handles that's exactly why, I put together a guide on building agent teams that actually work. full guide in the article below 👇
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Anthropic engineer showed how one person can run 5 AI agents, that code, test, review, and deploy at the same time. In 30 minutes they built the whole thing live in one session. Here's what they cover: > when to use one agent vs a full team > how to split work so agents don't step on each other > the exact framework for deciding what each agent handles that's exactly why, I put together a guide on building agent teams that actually work. full guide in the article below 👇

darkzodchi

836,038 Aufrufe • vor 28 Tagen

I got NVIDIA’s PersonaPlex running on Reachy Mini and it’s uncanny. Ultra-low latency changes everything for voice agents. BTW, NVIDIA is offering a ~$7k prize (including a DGX Spark!) for the best Reachy Mini community app in the next 15 days.
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I got NVIDIA’s PersonaPlex running on Reachy Mini and it’s uncanny. Ultra-low latency changes everything for voice agents. BTW, NVIDIA is offering a ~$7k prize (including a DGX Spark!) for the best Reachy Mini community app in the next 15 days.

Andi Marafioti

54,126 Aufrufe • vor 4 Monaten

NVIDIA JUST FEATURED HERMES AGENT AT COMPUTEX 2026. Hermes is integrating with NVIDIA OpenShell and Microsoft security primitives for secure on-device agents on Windows. Dillon Rolnick, CEO of Nous Research: "RTX Spark and NVIDIA OpenShell give Hermes users a powerful and secure environment for agents to run and work alongside you. You realize you're buying a full-fledged assistant, not a typical laptop." RTX Spark specs: → 1 petaflop AI performance → 20-core Grace CPU (built with MediaTek) → Blackwell GPU, 6,144 CUDA cores → 5th gen Tensor Cores with FP4 precision → up to 128GB LPDDR5X unified memory, 300 GB/s → NVLink C2C chip-to-chip interconnect → runs 120B parameter LLMs locally → up to 1M token context window on device → 2x inference speed via multi-token prediction RTX Spark devices ship Fall 2026 from ASUS, Dell, HP, Lenovo, Microsoft Surface, MSI. full NVIDIA press release in the comments. full Hermes setup guide in the article 👇
2:28

NVIDIA JUST FEATURED HERMES AGENT AT COMPUTEX 2026. Hermes is integrating with NVIDIA OpenShell and Microsoft security primitives for secure on-device agents on Windows. Dillon Rolnick, CEO of Nous Research: "RTX Spark and NVIDIA OpenShell give Hermes users a powerful and secure environment for agents to run and work alongside you. You realize you're buying a full-fledged assistant, not a typical laptop." RTX Spark specs: → 1 petaflop AI performance → 20-core Grace CPU (built with MediaTek) → Blackwell GPU, 6,144 CUDA cores → 5th gen Tensor Cores with FP4 precision → up to 128GB LPDDR5X unified memory, 300 GB/s → NVLink C2C chip-to-chip interconnect → runs 120B parameter LLMs locally → up to 1M token context window on device → 2x inference speed via multi-token prediction RTX Spark devices ship Fall 2026 from ASUS, Dell, HP, Lenovo, Microsoft Surface, MSI. full NVIDIA press release in the comments. full Hermes setup guide in the article 👇

YanXbt

45,550 Aufrufe • vor 20 Tagen

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!
0:20

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 🤗

75,499 Aufrufe • vor 5 Monaten

✨ One year after the debut of "Project Digits," DGX Spark has transformed from concept to reality and is now available from NVIDIA and OEM partners. See it in action lighting up the show floor at #CES2026. #SparkSomethingBig
0:47

✨ One year after the debut of "Project Digits," DGX Spark has transformed from concept to reality and is now available from NVIDIA and OEM partners. See it in action lighting up the show floor at #CES2026. #SparkSomethingBig

NVIDIA AI Developer

38,253 Aufrufe • vor 5 Monaten

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

Alex Cheema

312,051 Aufrufe • vor 1 Jahr

DeepSeek-V4-Flash-Spark and Spark-Mini were born today. 1 command setup to Pi / vllm-studio / docker deployment. All this is running local on a single DGX Spark.
3:57

DeepSeek-V4-Flash-Spark and Spark-Mini were born today. 1 command setup to Pi / vllm-studio / docker deployment. All this is running local on a single DGX Spark.

0xSero

20,019 Aufrufe • vor 25 Tagen

I just went on My First Million and showed how to replace a developer, designer, marketer, researcher, and product manager with AI agents for under $500 (copy my workflow in 55 minutes)
55:01

I just went on My First Million and showed how to replace a developer, designer, marketer, researcher, and product manager with AI agents for under $500 (copy my workflow in 55 minutes)

GREG ISENBERG

1,178,172 Aufrufe • vor 1 Jahr

The Hermes Agent Accelerated Business Hackathon presented by NVIDIA AI × Stripe × Nous Research starts now, for builders making agents that can earn, spend, and run real operations at any scale. Our NVIDIA integrations let your team run agents safely through NemoClaw, quickly on Nemotron 3 Ultra, and intelligently with access to their extensive agent skills. The new Stripe Skills for Hermes let your agent buy what it needs, provision its own SaaS, and pay for the services it uses. We want to see what kind of business tooling you can build on top of this foundation, whether it’s a fully automated company or a framework to accelerate enterprise functions. Prizes: 1st — $10,000 cash + NVIDIA DGX Spark + $5,000 Stripe Credits 2nd — $5,000 cash + NVIDIA DGX Spark + $3,000 Stripe Credits 3rd — $2,500 cash + NVIDIA DGX Spark + $1,000 Stripe Credits To enter: 1) Tweet a 1-3 minute demo video tagging Nous Research with a short writeup 2) Drop the link in the submissions channel: 3) Fill out the submission form: Judged by Nous Research, NVIDIA, and Stripe on usefulness, viability, and presentation. Submissions due EOD Tuesday, June 30.
1:06

The Hermes Agent Accelerated Business Hackathon presented by NVIDIA AI × Stripe × Nous Research starts now, for builders making agents that can earn, spend, and run real operations at any scale. Our NVIDIA integrations let your team run agents safely through NemoClaw, quickly on Nemotron 3 Ultra, and intelligently with access to their extensive agent skills. The new Stripe Skills for Hermes let your agent buy what it needs, provision its own SaaS, and pay for the services it uses. We want to see what kind of business tooling you can build on top of this foundation, whether it’s a fully automated company or a framework to accelerate enterprise functions. Prizes: 1st — $10,000 cash + NVIDIA DGX Spark + $5,000 Stripe Credits 2nd — $5,000 cash + NVIDIA DGX Spark + $3,000 Stripe Credits 3rd — $2,500 cash + NVIDIA DGX Spark + $1,000 Stripe Credits To enter: 1) Tweet a 1-3 minute demo video tagging Nous Research with a short writeup 2) Drop the link in the submissions channel: 3) Fill out the submission form: Judged by Nous Research, NVIDIA, and Stripe on usefulness, viability, and presentation. Submissions due EOD Tuesday, June 30.

Nous Research

1,542,879 Aufrufe • vor 5 Tagen

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
1:10

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 Aufrufe • vor 4 Monaten

THIS NUMBER MADE THE REVIEWER GO “WHOA” ON CAMERA AND IT SHOULD MAKE YOU GO WHOA TOO Mac Mini PP score was 563, Strix Halo came in at 342, and DGX Spark hit 2,170 that’s not a small gap, that’s a completely different category of hardware people were judging Spark on token generation and missing the entire point of what this box was built for prefill is the computationally heavy part, that’s where Blackwell eats everything else sitting on your desk save this before you spend $4k on the wrong machine
1:14

THIS NUMBER MADE THE REVIEWER GO “WHOA” ON CAMERA AND IT SHOULD MAKE YOU GO WHOA TOO Mac Mini PP score was 563, Strix Halo came in at 342, and DGX Spark hit 2,170 that’s not a small gap, that’s a completely different category of hardware people were judging Spark on token generation and missing the entire point of what this box was built for prefill is the computationally heavy part, that’s where Blackwell eats everything else sitting on your desk save this before you spend $4k on the wrong machine

leopardracer

37,702 Aufrufe • vor 21 Tagen

This guy runs an Nvidia Spark from his desk and pulls in $8,000 a month The device is the size of a small speaker and sits right on his desk. Inside is a full Nvidia GPU running AI workloads 24/7. He rents out the compute power to companies that need local AI processing. They pay him a flat monthly fee to use it remotely. $8,000 lands in his account every single month. He just plugged it in and that was it. The $4,000 box paid for itself in two weeks. Now it prints $96,000 a year from a device smaller than a coffee machine. Companies are desperate for local compute and regular people are quietly supplying it. Save this before everyone figures out what he already knows.
0:42

This guy runs an Nvidia Spark from his desk and pulls in $8,000 a month The device is the size of a small speaker and sits right on his desk. Inside is a full Nvidia GPU running AI workloads 24/7. He rents out the compute power to companies that need local AI processing. They pay him a flat monthly fee to use it remotely. $8,000 lands in his account every single month. He just plugged it in and that was it. The $4,000 box paid for itself in two weeks. Now it prints $96,000 a year from a device smaller than a coffee machine. Companies are desperate for local compute and regular people are quietly supplying it. Save this before everyone figures out what he already knows.

winkle.

57,426 Aufrufe • vor 22 Tagen

THIS AI DEVELOPER RUNS 120B PARAMETER MODELS LOCALLY AND HIS MACBOOK PRO CAN’T EVEN OPEN THEM he bought a DGX Spark, gave it the model, went back to his desk by end of day the inference was done, tested, committed his team is still waiting for the cloud GPU queue to free up the only thing between them is 128GB of unified memory in a box smaller than your lunch one Spark is a datacenter node, two Sparks is your own cluster bookmark this and send it to whoever is still paying for cloud GPUs
2:54

THIS AI DEVELOPER RUNS 120B PARAMETER MODELS LOCALLY AND HIS MACBOOK PRO CAN’T EVEN OPEN THEM he bought a DGX Spark, gave it the model, went back to his desk by end of day the inference was done, tested, committed his team is still waiting for the cloud GPU queue to free up the only thing between them is 128GB of unified memory in a box smaller than your lunch one Spark is a datacenter node, two Sparks is your own cluster bookmark this and send it to whoever is still paying for cloud GPUs

leopardracer

83,303 Aufrufe • vor 21 Tagen