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30 years. for 30 years the pc was the same thing: intel or amd inside, gpu next to it, and praying it doesn't crash. nvidia just ended that in a keynote. rtx spark. their first chip for personal computers. cpu, gpu and memory on a single piece of silicon.... show more

kai.

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289,887 Aufrufe • vor 1 Tag •via X (Twitter)

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35 Kommentare

Profilbild von adri

adrivor 1 Tag

an ai agent running 24/7 on your own machine with no subscription is a genuinely different pitch than what everyone else is selling

Profilbild von kai.

kai.vor 1 Tag

that's the shift, everyone's been renting you the ai, this is the first one selling you the machine instead

Profilbild von robert.

robert.vor 1 Tag

is this actually shipping or another "announced" thing that takes 2 years to show up

Profilbild von kai.

kai.vor 1 Tag

laptops are expected this fall from several major brands, not just a concept this time

Profilbild von Ahhhh Sing

Ahhhh Singvor 23 Stunden

And it only costs $10,000

Profilbild von Charles

Charlesvor 19 Stunden

AI slop. You couldn't even write the advertisement yourself. smh

Profilbild von Seth

Sethvor 19 Stunden

The rumors are that this has 5060 to 5070 performance and the prices are going to be 5k-7k and it will be lucky to get released by the end of the year. Just get a Strix/Gorgon Halo mini pc which is available right now.

Profilbild von z

zvor 1 Tag

14mm is insane for what's inside that thing, my current laptop is basically a brick in comparison

Profilbild von kai.

kai.vor 1 Tag

that's the part that got me too, cpu+gpu+128gb unified memory usually means a laptop you can't actually carry around

Profilbild von Chris

Chrisvor 19 Stunden

It won't matter if nobody can afford it.

Profilbild von Rich Ellefritz

Rich Ellefritzvor 18 Stunden

Awesome. Can I get one that doesn't have Windows preinstalled?

Profilbild von Chief

Chiefvor 16 Stunden

This only looks amazing because it isn't running MS new AI OS... once that comes out this thing will take 5 min to boot barely run 5 chrome tabs. The software will always bloat to exceed the hardware advances.

Profilbild von Moses, Maimonides, Garcia

Moses, Maimonides, Garciavor 22 Stunden

Apple leads. The rest follow.

Profilbild von Abe Burnett

Abe Burnettvor 20 Stunden

I’m only bummed Apple hasn’t done this. I hate Windows, but I WANT these capabilities. Looks insane!

Profilbild von Undius Mundius

Undius Mundiusvor 17 Stunden

But can it run Crysis?

Profilbild von Autodiag.

Autodiag.vor 19 Stunden

If it can run a 120b what it has 256GB or 512GB of RAM? So what it'll cost 10k?

Profilbild von AlekseyD

AlekseyDvor 16 Stunden

Wow. I want my pc to be as locked as not upgradeable as possible. Want more ram? Fuck you. Want other CPU? Fuck you. That is what computing is all about man? To be an Nvidia bitch

Profilbild von JimZ

JimZvor 15 Stunden

Sounds a lot like what Apple has been doing for the last 5 years with their PCs. Multiple CPU cores, GPU cores, Neural Engine cores, huge on chip cache, memory shared across all. Welcome to Macintosh.

Profilbild von Nin10dofan

Nin10dofanvor 19 Stunden

Just like Apple lol

Profilbild von lefkosamos

lefkosamosvor 16 Stunden

He wants you to spend 10k$ on a device since now it’s AI and it requires 10x more memory than 5 years ago. While everything is, probably by design, on supply shortages and they continue to push for chips they don’t have

Profilbild von Walletcelinho.ton

Walletcelinho.tonvor 21 Stunden

Ja pra pra colocar linux? 👀😏

Profilbild von SOTO

SOTOvor 21 Stunden

Running WINDOWS?

Profilbild von Zzorg

Zzorgvor 21 Stunden

A perfect gaming/ai machine for just $10k or there abouts. Thanks but I think I will wait this one out.

Profilbild von Santi

Santivor 1 Tag

running 120b params locally without a cloud call is the actual headline here not the gaming benchmarks

Profilbild von 𝕸𝖔𝖗𝖌𝖆𝖓 𝕷𝖆𝖓𝖈𝖆𝖘𝖙𝖊𝖗

𝕸𝖔𝖗𝖌𝖆𝖓 𝕷𝖆𝖓𝖈𝖆𝖘𝖙𝖊𝖗vor 16 Stunden

Fuckin lame. What happened to real hardware? Real performance? Real progress???? Now its just lame fake frames, input delay, and the need to use Ai instead of RAW power. Fuckin pathetic.

Profilbild von 5 Tonight

5 Tonightvor 15 Stunden

MacBooks will still win in battery life

Profilbild von alex

alexvor 22 Stunden

For sure

Profilbild von Phillip Lanos

Phillip Lanosvor 20 Stunden

would be dope to have a surface tablet with this ability

Profilbild von MrDaffy 🇫🇷 avec les bâtisseurs

MrDaffy 🇫🇷 avec les bâtisseursvor 14 Stunden

AMD le fait déjà depuis 1an avec son Ryzen AI 395+ max et le nouveau Ryzen 495 qui sort emporte une Radeon 8065S et 192go de ram unifié. Couplé au SSD de phison avec leur aidaptiv+ et 90go de cash mémoire tu rentre des modèles de plus de 200B

Profilbild von Jörg Kachelofen

Jörg Kachelofenvor 20 Stunden

Great. I know now where my framework laptop will head mid-term👌😌

Profilbild von Chuck Overdrive

Chuck Overdrivevor 15 Stunden

But can it fit on my watch and in my sunglasses as a combo unit?

Profilbild von Devyfox111

Devyfox111vor 17 Stunden

Why. Do you type like this. It's a little weird.

Profilbild von Stryker336

Stryker336vor 19 Stunden

What???

Profilbild von David Peyton

David Peytonvor 14 Stunden

@grok link the actual keynote

Profilbild von Chris

Chrisvor 18 Stunden

I wonder what’s on this specific chip 🤨

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AMD JUST KILLED THE $200 - A - MONTH AI SUBSCRIPTION - A 65-WATT BOX WITH 128GB OF UNIFIED MEMORY THAT RUNS 70B MODELS LOCALLY. that clip is amd's ryzen ai max+ 395 mini box, held up on stage. the whole pitch is one spec: 128gb of high-speed unified memory. why it matters: cpu, gpu and npu share the same 128gb pool, so a model that used to need a rack of vram just fits. what it actually runs: llama 70b in full precision on the built-in gpu open models up to ~100b parameters, locally, no cloud all of it in a mini pc pulling around 65 watts that's the part that ends the subscription: your prompts, your data, your model, on a box on your desk, not metered by the token. honest line: this runs open models, not gpt-5 or claude opus. for chat, coding help and agents on your own data it's more than enough. for the absolute frontier, the cloud still wins. and it isn't free: the box runs ~$1,500 and up. but that's a few months of a $200 sub, then it's yours forever. no monthly ai bill, no tokens metered, no prompt leaving the room. the uncomfortable part isn't that amd made a fast box. it's that "you need the cloud for ai" was a pricing choice, and unified memory just made it optional. follow RetroChainer for the hardware that turns rent into ownership, and bookmark this before your next ai renewal.

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NVIDIA just handed every solo creator and freelancer an unfair advantage. Jensen Huang walked on stage and announced RTX Spark. An ARM-based laptop chip that nobody saw coming. They called it the most power efficient PC chip ever built. 20 cores. Blackwell graphics. 6144 CUDA cores. Up to 128GB of LPDDR5X memory. But forget the spec sheet for a second. Here is what actually matters. RTX Spark is built to run AI models locally. No cloud subscription. No API costs. No waiting on a server somewhere. Everything runs directly on the laptop at full speed. That changes the math completely for anyone using AI to make money. The guy generating 3D assets in Blender with Claude his renders now take minutes instead of hours. More projects per day. More income per week. The girl producing AI kids content for YouTube local rendering means no upload wait times, no generation limits, no monthly fees eating into her margins. The freelancer building websites and automating outreach every AI tool in his stack now runs faster and cheaper than before. 30 laptops from Asus, Dell, Lenovo, MSI and others. Available this fall. For years the barrier was hardware. You needed an expensive setup to run serious AI workflows locally. NVIDIA just put that power inside a thin laptop anyone can carry anywhere. The people who already figured out how to monetize AI are about to move twice as fast. The people who haven’t started yet just ran out of excuses. Save this.

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11,334 Aufrufe • vor 2 Monaten

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AMD CEO Lisa Su just killed Nvidia’s $4,000 AI box with a $1,499 lunchbox. She walked on stage, held it in one hand, and ran a 235 billion parameter model live. No data center. No cloud. No rented GPU. The chip inside is something nobody saw coming. AMD’s Ryzen AI Max+ 395 is the first x86 silicon where CPU and GPU share the same 128GB of memory. That single trick lets a desktop run models that used to need a server rack. Out of those 128GB, Linux hands the GPU 110GB to play with. For context, an RTX 5090 gives you 32GB. A 4090 gives you 24. This box gives you more than three times either of them, in a chassis the size of a thick paperback. The benchmark that broke the room: this chip beat an Nvidia RTX 5080 by more than 3x on DeepSeek R1 inference. A $1,499 lunchbox outrunning a $1,000 discrete graphics card on a real AI workload. Nvidia spent a decade convincing the world you needed their hardware for serious AI. AMD just put that on a desk for half the price. Here is what nobody is telling you. A heavy AI user right now pays $200 for Claude Code Max, $200 for ChatGPT Pro, $20 for Cursor, $20 for Gemini. That is $5,280 a year leaving your account. The box pays itself off in 9 months and then runs free for the rest of its life. Install Ollama. Pull Qwen3 235B. Point Claude Code at localhost. Same interface you already use, except now nothing leaves your machine, nothing costs per request, and no company throttles your usage at 3am when you finally have time to build. This is the moment every AI subscription becomes optional. Lawyers stop fearing OpenAI leaks. Developers stop watching the token meter. Founders stop renting H100s for prototypes that never ship because the bill scared them. The first thousand people to figure this out will own the next two years of private AI consulting. Save this, and read the full breakdown article below you are watching the next shift hit before everyone else does.

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3,397,308 Aufrufe • vor 3 Monaten

I ran a 35-billion parameter AI agent on a $600 Mac mini. Specs: M4 Mac-Mini 16GB RAM The model doesn't fit in RAM. It pages from the SSD at 30 tokens/second. On NVIDIA, the same paging gives you 1.6 tok/s. Apple Silicon gives you 30. That's 18.6x faster. No cloud. No API keys. $0/month. Here's what it can do 🧵

I ran a 35-billion parameter AI agent on a $600 Mac mini. Specs: M4 Mac-Mini 16GB RAM The model doesn't fit in RAM. It pages from the SSD at 30 tokens/second. On NVIDIA, the same paging gives you 1.6 tok/s. Apple Silicon gives you 30. That's 18.6x faster. No cloud. No API keys. $0/month. Here's what it can do 🧵

thestreamingdev()

732,235 Aufrufe • vor 6 Monaten

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Julian Goldie SEO

15,983 Aufrufe • vor 7 Monaten

BOLT A GPU ONTO THIS $200 FANLESS BOARD AND IT DOES THE TWO THINGS A RASPBERRY PI PHYSICALLY CAN'T: LOCAL AI AND 4K TRANSCODING. that clip is a zimaboard with a graphics card plugged straight into its pcie slot. that slot is the whole point. a pi has gpio and usb, but no real pcie, so it tops out where this one starts. drop a gpu in and the tiny box suddenly does: ollama and local models with actual gpu acceleration, not cpu crawl plex or jellyfin transcoding several 4k streams at once, in hardware anything else that was "you need a real pc for that", on a fanless board the rest of the board backs it up: quad-core intel up to 3.6, dual sata, dual 2.5gbe, runs zimaos, linux, even windows. so one silent box becomes a nas, a media server, and a local ai node at the same time. no tower, no raspberry-pi ceiling, no cloud gpu rented by the hour. the uncomfortable part isn't that it takes a gpu. it's that "a pi can do it" quietly stopped being true the moment the workload needed a real pcie lane. follow RetroChainer for the small boxes that punch way above their size, and bookmark this before you buy a whole tower for one gpu job.

BOLT A GPU ONTO THIS $200 FANLESS BOARD AND IT DOES THE TWO THINGS A RASPBERRY PI PHYSICALLY CAN'T: LOCAL AI AND 4K TRANSCODING. that clip is a zimaboard with a graphics card plugged straight into its pcie slot. that slot is the whole point. a pi has gpio and usb, but no real pcie, so it tops out where this one starts. drop a gpu in and the tiny box suddenly does: ollama and local models with actual gpu acceleration, not cpu crawl plex or jellyfin transcoding several 4k streams at once, in hardware anything else that was "you need a real pc for that", on a fanless board the rest of the board backs it up: quad-core intel up to 3.6, dual sata, dual 2.5gbe, runs zimaos, linux, even windows. so one silent box becomes a nas, a media server, and a local ai node at the same time. no tower, no raspberry-pi ceiling, no cloud gpu rented by the hour. the uncomfortable part isn't that it takes a gpu. it's that "a pi can do it" quietly stopped being true the moment the workload needed a real pcie lane. follow RetroChainer for the small boxes that punch way above their size, and bookmark this before you buy a whole tower for one gpu job.

RetroChainer

24,813 Aufrufe • vor 1 Monat

Your cloud agent runs $10–20 a day. This box runs OpenAI's 120B model for $0. Same workload. It just sits in a closet on AMD silicon. A Minisforum mini PC, Strix Halo, 128GB unified memory. The model lives entirely on-device. 56 tokens a second. No API key. Nothing leaves the network. Cloud only handles the exceptions now. Claude or OpenAI by routing, not by default. Everyone calls this "free." Wrong word. It's not free. It's owned. The bill just stops existing. The cloud was never the only option. It was the default nobody bothered to question.

Your cloud agent runs $10–20 a day. This box runs OpenAI's 120B model for $0. Same workload. It just sits in a closet on AMD silicon. A Minisforum mini PC, Strix Halo, 128GB unified memory. The model lives entirely on-device. 56 tokens a second. No API key. Nothing leaves the network. Cloud only handles the exceptions now. Claude or OpenAI by routing, not by default. Everyone calls this "free." Wrong word. It's not free. It's owned. The bill just stops existing. The cloud was never the only option. It was the default nobody bothered to question.

RetroChainer

13,925 Aufrufe • vor 3 Monaten

First hands-on with Microsoft’s new Surface Laptop Ultra. Microsoft is clearly positioning this as a new class of creator and AI laptop, powered by new NVIDIA silicon with an RTX GPU built for local AI, creative workflows, and gaming. A few standout specs: -New NVIDIA chip with RTX GPU -Up to 1 petaflop of AI compute -Up to 128GB unified memory -15-inch mini-LED PixelSense Ultra touchscreen -3:2 aspect ratio -262 PPI -Up to 2,000 nits peak HDR brightness -Less than 18mm thick

First hands-on with Microsoft’s new Surface Laptop Ultra. Microsoft is clearly positioning this as a new class of creator and AI laptop, powered by new NVIDIA silicon with an RTX GPU built for local AI, creative workflows, and gaming. A few standout specs: -New NVIDIA chip with RTX GPU -Up to 1 petaflop of AI compute -Up to 128GB unified memory -15-inch mini-LED PixelSense Ultra touchscreen -3:2 aspect ratio -262 PPI -Up to 2,000 nits peak HDR brightness -Less than 18mm thick

Chubby♨️

65,993 Aufrufe • vor 3 Monaten

NVIDIA'S BIGGEST COMPETITOR AMD BUILT A BOX THAT RUNS A 235B MODEL AND KILLS $200 OPENAI AND $200 CLAUDE CODE FOR $9 A MONTH amd's ryzen ai max+ 395 is the first x86 chip that runs a 200 billion parameter model on a single piece of silicon with 128gb of unified memory the gmktec evo-x2 runs qwen3 235b fully, deepseek v3 comfortably and llama 3.3 70b with headroom. on linux you get 110gb of usable vram out of 128gb amd claimed the chip beat an nvidia rtx 5080 by more than 3x on deepseek r1 inference. a lunchbox sized pc outrunning a $1,000 discrete gpu on a real ai workload a heavy ai user pays $200 for claude code max, $200 for chatgpt pro, $20 for cursor and $20 for gemini. that's $5,280 a year and the box pays itself off in 9 to 10 months ollama installs in one command and claude code points at localhost so nothing leaves the machine and nothing costs per request bookmark this and read the article below

NVIDIA'S BIGGEST COMPETITOR AMD BUILT A BOX THAT RUNS A 235B MODEL AND KILLS $200 OPENAI AND $200 CLAUDE CODE FOR $9 A MONTH amd's ryzen ai max+ 395 is the first x86 chip that runs a 200 billion parameter model on a single piece of silicon with 128gb of unified memory the gmktec evo-x2 runs qwen3 235b fully, deepseek v3 comfortably and llama 3.3 70b with headroom. on linux you get 110gb of usable vram out of 128gb amd claimed the chip beat an nvidia rtx 5080 by more than 3x on deepseek r1 inference. a lunchbox sized pc outrunning a $1,000 discrete gpu on a real ai workload a heavy ai user pays $200 for claude code max, $200 for chatgpt pro, $20 for cursor and $20 for gemini. that's $5,280 a year and the box pays itself off in 9 to 10 months ollama installs in one command and claude code points at localhost so nothing leaves the machine and nothing costs per request bookmark this and read the article below

starmex

93,580 Aufrufe • vor 3 Monaten

the CEO of NVIDIA just said the PC you use today will be gone, replaced by an AI supercomputer that lives in your house Jensen Huang stood on stage holding the machine and said it becomes less like a computer and more like R2-D2, a thing in your home that just does work for you all day he put it bluntly, this is as big as the day the phone became the smartphone and the wild part is the hardware to do it already exists and ships this year here is what he actually unveiled: > a desktop that runs a one trillion parameter AI model locally, 768GB of memory, sitting by your desk > agents that run 24/7 with no meter, no cloud bill, no rental, doing work while you sleep > NVIDIA and Microsoft rebuilding the PC from the ground up for the first time in 40 years > a full lineup, from a $249 chip to enterprise monsters, and almost nobody knows which one they actually need the hype is going to push everyone toward the biggest most expensive machine i wrote the honest breakdown, every NVIDIA AI box, what each really does, the real math, and which one is actually yours the full guide is in the article below

the CEO of NVIDIA just said the PC you use today will be gone, replaced by an AI supercomputer that lives in your house Jensen Huang stood on stage holding the machine and said it becomes less like a computer and more like R2-D2, a thing in your home that just does work for you all day he put it bluntly, this is as big as the day the phone became the smartphone and the wild part is the hardware to do it already exists and ships this year here is what he actually unveiled: > a desktop that runs a one trillion parameter AI model locally, 768GB of memory, sitting by your desk > agents that run 24/7 with no meter, no cloud bill, no rental, doing work while you sleep > NVIDIA and Microsoft rebuilding the PC from the ground up for the first time in 40 years > a full lineup, from a $249 chip to enterprise monsters, and almost nobody knows which one they actually need the hype is going to push everyone toward the biggest most expensive machine i wrote the honest breakdown, every NVIDIA AI box, what each really does, the real math, and which one is actually yours the full guide is in the article below

John Doe

194,375 Aufrufe • vor 4 Monaten

A guy I know was paying $200 a month for AI. ChatGPT. Claude. Midjourney. Then AMD put it in a box the size of a book. He bought one. Canceled every subscription. Now everything runs on his desk. No cloud. No monthly bill. For years we rented AI. Now some people own it.

A guy I know was paying $200 a month for AI. ChatGPT. Claude. Midjourney. Then AMD put it in a box the size of a book. He bought one. Canceled every subscription. Now everything runs on his desk. No cloud. No monthly bill. For years we rented AI. Now some people own it.

wluha

15,509 Aufrufe • vor 3 Monaten