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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.

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0xSero

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20,019 görüntüleme • 2 ay önce •via X (Twitter)

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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!
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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!

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Deepseek-V4-Flash helping me setup Nvidia's Dynamo for disaggregated inference. I have really gotten this model to be a daily driver now. It's really strong at agentic workflows and a decent programmer. For all my side stuff, it's local deepseek now Claude sub cancelled wdyt

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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. 🔥
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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. 🔥

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A spark plug is a small device in a car’s engine that creates a tiny electric spark to ignite the fuel and air mixture inside the cylinder. This spark is what makes the engine start and keep running. Without spark plugs, gasoline engines wouldn’t work
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A spark plug is a small device in a car’s engine that creates a tiny electric spark to ignite the fuel and air mixture inside the cylinder. This spark is what makes the engine start and keep running. Without spark plugs, gasoline engines wouldn’t work

HOW THINGS WORK

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15 concurrent terminal workloads on a local DGX Spark, all served by nvidia/nemotron-3-super 120B A12B NVFP4 through vLLM. 15/15 completed, 0 errors, 30.2s wall time: no fake dashboard, just local inference under concurrent load. fineprint: live local concurrency demo
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15 concurrent terminal workloads on a local DGX Spark, all served by nvidia/nemotron-3-super 120B A12B NVFP4 through vLLM. 15/15 completed, 0 errors, 30.2s wall time: no fake dashboard, just local inference under concurrent load. fineprint: live local concurrency demo

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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.
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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

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image → 3D generation. a prompt is gently refined with Nemotron → FLUX paints a reference image → TRELLIS reconstructs a textured 3D mesh, running locally on an NVIDIA AI DGX Spark. quiet, local, always on.
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image → 3D generation. a prompt is gently refined with Nemotron → FLUX paints a reference image → TRELLIS reconstructs a textured 3D mesh, running locally on an NVIDIA AI DGX Spark. quiet, local, always on.

three.ws

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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
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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

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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.
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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

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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

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GLM-5.2 running under my desk, modifying GGUFs to enable MTP on the Spark. What a world we live in, where you can have a megamind running off electrons going really fast.
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GLM-5.2 running under my desk, modifying GGUFs to enable MTP on the Spark. What a world we live in, where you can have a megamind running off electrons going really fast.

0xSero

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16 people chatting with Qwen3.6-35B at once ONE DGX Spark. This is a real capture, not a mockup: every token you see replays at its actual measured arrival time. Peaks ~440 tok/s total. A single user gets 105 tok/s. NVFP4 + MTP-3 on vLLM.
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16 people chatting with Qwen3.6-35B at once ONE DGX Spark. This is a real capture, not a mockup: every token you see replays at its actual measured arrival time. Peaks ~440 tok/s total. A single user gets 105 tok/s. NVFP4 + MTP-3 on vLLM.

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I'm now used to this speed 🤣 Running DeepSeek-V4-Flash-IQ2XXS on my single 3090 and 64GB RAM tg is fine, its the prefill that actually hurts.
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I'm now used to this speed 🤣 Running DeepSeek-V4-Flash-IQ2XXS on my single 3090 and 64GB RAM tg is fine, its the prefill that actually hurts.

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Introducing Spark 1 Pro and Spark 1 Mini 🔥 Two new models powering /agent, our state of the art agent that searches, navigates, and extracts web data from a prompt. Mini is 60% cheaper and Pro delivers higher accuracy, making this our most powerful extraction endpoint yet.

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Muse Spark 1.1 is here! Available today via API and on Of all the agentic use cases, I’m most excited about this one: going from a single video shot straight to task completion. 🚀 We’ve also polished and launched Computer Use and Video-Audio Perception for Muse Spark 1.1. Read more:

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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 then showed how to install iSECSIM 5.1 for virtual simulations, cloned the repo from GitHub, configured GCC 11 and built the entire stack from scratch 128GB of available memory, ARM processor, full Python library support and a complete AI development environment - all on a box the size of a paperback book at the end he launched a robotics environment and showed the DGX Spark handling full physics simulations in real time from unboxing to running agents in under 8 minutes - full guide on camera

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Receipts in video, see it float at ~100-150 while coding the fluctuations were for task and context switching of the model. This thing rips through code! A Single NVIDIA AI DGX Spark ⚡️
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Receipts in video, see it float at ~100-150 while coding the fluctuations were for task and context switching of the model. This thing rips through code! A Single NVIDIA AI DGX Spark ⚡️

ÆON FORGE ✨

10,815 görüntüleme • 1 ay önce

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 ↓

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Covid and HIV were patented and genetically modified to attack the nervous system . It has a direct command to go there . Covid is the spark which turns on Epstein Barr .
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Covid and HIV were patented and genetically modified to attack the nervous system . It has a direct command to go there . Covid is the spark which turns on Epstein Barr .

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🔥 Spark Mainnet Beta is Live!🔥 We’re excited to officially launch Spark Beta, a central limit order book and a spot exchange on Fuel.
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🔥 Spark Mainnet Beta is Live!🔥 We’re excited to officially launch Spark Beta, a central limit order book and a spot exchange on Fuel.

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