正在加载视频...

视频加载失败

返回首页

everyone's paying OpenAI $200 a month. a founder i've been tracking paid Nvidia $2,999 once and came out roughly $22,000 ahead a few months later he was running a micro-SaaS where inference ate 35% of revenue, so scaling users just scaled the losses. he moved everything onto a local...

0xKiyoro's profile picture

Kiyoro

5,646 subscribers

23,184 次观看 • 2 个月前 •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

0 条评论

暂无评论

原始帖子的评论将显示在这里

相关视频

This guy turned a $250K cloud bill into a $2,999 Nvidia box on his desk. One box. One-time charge. Same size as a Mac mini. Runs the workload AWS was charging him $1,900/month for. He made $22,000 in a year just from the bill he stopped paying. The kicker: it speaks OpenAI-compatible API out of the box. Migrating his existing stack was 1 line of code. - No more cloud GPUs. - No more monthly meter. - No more "let me check the AWS dashboard before I run that." Full build, exact math, and what the box actually runs is in the article below 👇
2:04

This guy turned a $250K cloud bill into a $2,999 Nvidia box on his desk. One box. One-time charge. Same size as a Mac mini. Runs the workload AWS was charging him $1,900/month for. He made $22,000 in a year just from the bill he stopped paying. The kicker: it speaks OpenAI-compatible API out of the box. Migrating his existing stack was 1 line of code. - No more cloud GPUs. - No more monthly meter. - No more "let me check the AWS dashboard before I run that." Full build, exact math, and what the box actually runs is in the article below 👇

ZEUS⚡️

14,529 次观看 • 2 个月前

NVIDIA WILL PAY YOU $150/MONTH TO BOLT 16 BLACKWELL GPUS TO YOUR HOUSE - OR YOU BUY THE BOX AND MAKE $22,000 A YEAR same NVIDIA chips. the contract is where it gets interesting. they attach a $1,000,000 data center to your house and pay you for it - you get free internet, battery backup and cheaper electricity while they run an asset serving Amazon, Microsoft and Google 24/7 on your property or you spend $2,999 on a DGX Spark the size of a paperback - 128GB memory, runs a 70B model locally, $10/month in electricity if you were paying $1,900/month on cloud GPU rentals it pays for itself in 6 weeks and puts $22,000 back in year one one contract you are the infrastructure. the other one you own it.
0:30

NVIDIA WILL PAY YOU $150/MONTH TO BOLT 16 BLACKWELL GPUS TO YOUR HOUSE - OR YOU BUY THE BOX AND MAKE $22,000 A YEAR same NVIDIA chips. the contract is where it gets interesting. they attach a $1,000,000 data center to your house and pay you for it - you get free internet, battery backup and cheaper electricity while they run an asset serving Amazon, Microsoft and Google 24/7 on your property or you spend $2,999 on a DGX Spark the size of a paperback - 128GB memory, runs a 70B model locally, $10/month in electricity if you were paying $1,900/month on cloud GPU rentals it pays for itself in 6 weeks and puts $22,000 back in year one one contract you are the infrastructure. the other one you own it.

Sprytix

26,231 次观看 • 2 个月前

CHINESE AI TEACHER STACKED 4 NVIDIA DGX SPARK CHIPS INTO A CLUSTER - AND NOW RUNS A BUSINESS ON IT FROM HIS DESK 4 chips at $2,999 each - one time investment - and now he has a cluster that handles client inference requests around the clock while he does something else he's running a Qwen 32 35B model with 4 concurrent requests at the same time and the speed barely drops compared to a single request what used to require a $10,000+/month cloud setup now sits on his desk and costs him $40-60/month in electricity 4 chips at $2,999 each - one time investment - and now he has a cluster that handles client inference requests around the clock while he does something else the people still paying per token are financing someone else's infrastructure
1:42

CHINESE AI TEACHER STACKED 4 NVIDIA DGX SPARK CHIPS INTO A CLUSTER - AND NOW RUNS A BUSINESS ON IT FROM HIS DESK 4 chips at $2,999 each - one time investment - and now he has a cluster that handles client inference requests around the clock while he does something else he's running a Qwen 32 35B model with 4 concurrent requests at the same time and the speed barely drops compared to a single request what used to require a $10,000+/month cloud setup now sits on his desk and costs him $40-60/month in electricity 4 chips at $2,999 each - one time investment - and now he has a cluster that handles client inference requests around the clock while he does something else the people still paying per token are financing someone else's infrastructure

Sprytix

51,010 次观看 • 2 个月前

This is what AI subscription companies are afraid of. A guy with a screwdriver, a $700 pile of components, and one free weekend. They built their entire business model on you never figuring out that the same models run locally. On hardware you own. No rate limits. No data leaving the room. No invoice at the end of the month. He figured it out on a Saturday. By Sunday night six agents were online. Research, writing, QA, publishing, monitoring. All running locally for $23 a month in electricity. By the following month he had eight clients paying $2,500 each to run the same system for their businesses. $20,000 a month. Built on a PC he assembled himself in a weekend. They're still sending him renewal emails. He stopped opening them.
0:45

This is what AI subscription companies are afraid of. A guy with a screwdriver, a $700 pile of components, and one free weekend. They built their entire business model on you never figuring out that the same models run locally. On hardware you own. No rate limits. No data leaving the room. No invoice at the end of the month. He figured it out on a Saturday. By Sunday night six agents were online. Research, writing, QA, publishing, monitoring. All running locally for $23 a month in electricity. By the following month he had eight clients paying $2,500 each to run the same system for their businesses. $20,000 a month. Built on a PC he assembled himself in a weekend. They're still sending him renewal emails. He stopped opening them.

Superior

22,686 次观看 • 1 个月前

15-year-old American made $14,000 in his first month selling a service most marketers have never even heard of. Every time someone searches for a business on Google - the first thing they see is an AI response, not a website and not an ad. ChatGPT gives 5-6 recommendations and if a business isn't there - the customer goes to a competitor without a single click. His secret - AI visibility. He optimized local businesses to appear in ChatGPT responses, Google AI Overview and Meta AI instead of paying for ads that no longer work. He'd walk up to a business owner, show them that their business didn't appear in AI responses and ask if they wanted to fix it. Almost everyone said yes immediately. 8 clients at $800 in the first month, 20 clients in the second - because every satisfied client referred him to someone else. This isn't a marketing problem - it's a visibility problem. And he was the only one solving it in his city.
0:45

15-year-old American made $14,000 in his first month selling a service most marketers have never even heard of. Every time someone searches for a business on Google - the first thing they see is an AI response, not a website and not an ad. ChatGPT gives 5-6 recommendations and if a business isn't there - the customer goes to a competitor without a single click. His secret - AI visibility. He optimized local businesses to appear in ChatGPT responses, Google AI Overview and Meta AI instead of paying for ads that no longer work. He'd walk up to a business owner, show them that their business didn't appear in AI responses and ask if they wanted to fix it. Almost everyone said yes immediately. 8 clients at $800 in the first month, 20 clients in the second - because every satisfied client referred him to someone else. This isn't a marketing problem - it's a visibility problem. And he was the only one solving it in his city.

Noisy

43,115 次观看 • 3 个月前

A company wants to pay you to put a $300,000 PC on your front lawn. His gut says that thing's getting stolen GTA style. He bought a $2,999 version instead. Fits on a desk. Runs the same AI workloads. Costs $10/month in electricity. 16 NVIDIA GPUs on your lawn, their compute, your property, their revenue. DGX Spark on your desk, your compute, your property, your revenue. He was spending $1,900/month renting cloud GPUs for client AI work. Fine-tuning models, running 70B assistants, processing document batches. The box does all of it locally. $10/month. Nothing billable. Nothing leaving the building. Break-even in 6 weeks. $22,000 saved in year one. The lawn option comes with free internet and a cheaper power bill. His option came with $22,000.
0:48

A company wants to pay you to put a $300,000 PC on your front lawn. His gut says that thing's getting stolen GTA style. He bought a $2,999 version instead. Fits on a desk. Runs the same AI workloads. Costs $10/month in electricity. 16 NVIDIA GPUs on your lawn, their compute, your property, their revenue. DGX Spark on your desk, your compute, your property, your revenue. He was spending $1,900/month renting cloud GPUs for client AI work. Fine-tuning models, running 70B assistants, processing document batches. The box does all of it locally. $10/month. Nothing billable. Nothing leaving the building. Break-even in 6 weeks. $22,000 saved in year one. The lawn option comes with free internet and a cheaper power bill. His option came with $22,000.

Superior

34,445 次观看 • 2 个月前

NVIDIA will cut your power bill if you let them bolt a $1,000,000 data center to your house. Or spend $2,999 and make $22,000. Option 1, they bolt 16 Blackwell chips to the outside of your house. You get free internet, battery backup, cheaper electricity. They get a million-dollar asset running 24/7 on your property, serving requests for Amazon, Microsoft, Google. Option 2, you buy a DGX Spark for $2,999. Size of a paperback. Sits on your desk. 128GB memory. Runs a 70B model locally. $10/month in electricity. No data leaves the room. Paid for itself in 6 weeks for someone spending $1,900/month on cloud GPU rentals. $22,000 back in year one. One option, you're the infrastructure. Other option, you own it. Same NVIDIA chips. Very different contracts.
1:21

NVIDIA will cut your power bill if you let them bolt a $1,000,000 data center to your house. Or spend $2,999 and make $22,000. Option 1, they bolt 16 Blackwell chips to the outside of your house. You get free internet, battery backup, cheaper electricity. They get a million-dollar asset running 24/7 on your property, serving requests for Amazon, Microsoft, Google. Option 2, you buy a DGX Spark for $2,999. Size of a paperback. Sits on your desk. 128GB memory. Runs a 70B model locally. $10/month in electricity. No data leaves the room. Paid for itself in 6 weeks for someone spending $1,900/month on cloud GPU rentals. $22,000 back in year one. One option, you're the infrastructure. Other option, you own it. Same NVIDIA chips. Very different contracts.

Superior

387,708 次观看 • 2 个月前

people burn $1,900 a month on cloud, this $2,999 NVIDIA box runs 5 AI models at once and costs $10 to power 128GB of unified memory, stack two together and you double it, enough to run models a $2,000 graphics card cannot even open in the demo it ran Qwen3 Vision, Nemotron, a voice model, text to speech and speech to text all at once, and only used half the box here is the math that makes people switch: > cloud GPUs were costing $1,900 every single month, billed forever > the box is $2,999 one time, then about $10 of electricity a month > it paid for itself in two months, $22,000 stayed in the business in year one > zero data ever leaves your desk, no rental, no rate limits most people are still renting what this owns outright the full breakdown of the box and the exact math is in the article below
1:04

people burn $1,900 a month on cloud, this $2,999 NVIDIA box runs 5 AI models at once and costs $10 to power 128GB of unified memory, stack two together and you double it, enough to run models a $2,000 graphics card cannot even open in the demo it ran Qwen3 Vision, Nemotron, a voice model, text to speech and speech to text all at once, and only used half the box here is the math that makes people switch: > cloud GPUs were costing $1,900 every single month, billed forever > the box is $2,999 one time, then about $10 of electricity a month > it paid for itself in two months, $22,000 stayed in the business in year one > zero data ever leaves your desk, no rental, no rate limits most people are still renting what this owns outright the full breakdown of the box and the exact math is in the article below

John Doe

46,754 次观看 • 2 个月前

AMD might have disrupted Nvidia's entire cloud GPU rental business. In January at CES, AMD CEO Lisa Su demonstrated a $1,499 mini PC running the same class of AI model that currently costs companies $2,500 to $3,000 every month to rent from Nvidia-powered cloud servers. AMD's own branded version opened pre-orders this month at $3,999. Third party manufacturers have been selling the same chip since 2025 starting at $1,499. Here is exactly why this is dangerous for Nvidia. Nvidia's $75 billion quarterly revenue is built almost entirely on one business model, companies rent access to Nvidia GPUs through cloud providers like AWS and Lambda Labs to run AI. They pay monthly. Nvidia gets paid every time someone runs an AI model in the cloud. That recurring rental income is what turned Nvidia into a $5 trillion company. The AMD box eliminates that monthly fee permanently. One AI consultant switched from $2,800 per month in Nvidia cloud rental costs to $8 per month in electricity. The hardware paid for itself in 11 days. Over 8 months he generated $47,000 running the same AI workloads that previously left him paying Nvidia's ecosystem $2,800 every single month. Multiply that across thousands of enterprise customers and the revenue erosion becomes structural. Every business that buys this box stops paying cloud rental fees forever. Lawyers, doctors, banks, accountants, and financial advisors, businesses with sensitive data that cannot legally go to a cloud server represent billions in annual cloud GPU fees that Nvidia is now at risk of losing permanently. The threat is also closing in from the top. Google signed deals worth tens of billions with Anthropic and Meta to replace Nvidia with its own chips. Amazon built its own AI chips across AWS. Apple trained its AI on Google's chips, not Nvidia's. Custom silicon has grown from 21% of the AI chip market in 2025 to 28% in 2026. Nvidia's rental model only worked because serious AI compute had no alternative.
1:42

AMD might have disrupted Nvidia's entire cloud GPU rental business. In January at CES, AMD CEO Lisa Su demonstrated a $1,499 mini PC running the same class of AI model that currently costs companies $2,500 to $3,000 every month to rent from Nvidia-powered cloud servers. AMD's own branded version opened pre-orders this month at $3,999. Third party manufacturers have been selling the same chip since 2025 starting at $1,499. Here is exactly why this is dangerous for Nvidia. Nvidia's $75 billion quarterly revenue is built almost entirely on one business model, companies rent access to Nvidia GPUs through cloud providers like AWS and Lambda Labs to run AI. They pay monthly. Nvidia gets paid every time someone runs an AI model in the cloud. That recurring rental income is what turned Nvidia into a $5 trillion company. The AMD box eliminates that monthly fee permanently. One AI consultant switched from $2,800 per month in Nvidia cloud rental costs to $8 per month in electricity. The hardware paid for itself in 11 days. Over 8 months he generated $47,000 running the same AI workloads that previously left him paying Nvidia's ecosystem $2,800 every single month. Multiply that across thousands of enterprise customers and the revenue erosion becomes structural. Every business that buys this box stops paying cloud rental fees forever. Lawyers, doctors, banks, accountants, and financial advisors, businesses with sensitive data that cannot legally go to a cloud server represent billions in annual cloud GPU fees that Nvidia is now at risk of losing permanently. The threat is also closing in from the top. Google signed deals worth tens of billions with Anthropic and Meta to replace Nvidia with its own chips. Amazon built its own AI chips across AWS. Apple trained its AI on Google's chips, not Nvidia's. Custom silicon has grown from 21% of the AI chip market in 2025 to 28% in 2026. Nvidia's rental model only worked because serious AI compute had no alternative.

Bull Theory

26,668 次观看 • 1 个月前

Do you actually understand what's happening. He built a personal local AI voice agent that fits in your pocket. Clients pay him $2,500/month to have one. It runs locally. No cloud. No rate limits. No data going anywhere. You talk to it and it acts in real systems, automatically, without a human in the loop. He looked at that device and didn't think about using it himself. He thought about who would pay him to build one for them. $28,000/month ops team. Five agents. $200/month in tools. Client saves $22,000. He earns $2,500/month to maintain it. They never cancel. Canceling means hiring the team back. 8 clients. $20,000/month recurring. Everyone is talking about AI voice agents like they're a personal productivity tool. He turned one into a business. Different outcome.
0:31

Do you actually understand what's happening. He built a personal local AI voice agent that fits in your pocket. Clients pay him $2,500/month to have one. It runs locally. No cloud. No rate limits. No data going anywhere. You talk to it and it acts in real systems, automatically, without a human in the loop. He looked at that device and didn't think about using it himself. He thought about who would pay him to build one for them. $28,000/month ops team. Five agents. $200/month in tools. Client saves $22,000. He earns $2,500/month to maintain it. They never cancel. Canceling means hiring the team back. 8 clients. $20,000/month recurring. Everyone is talking about AI voice agents like they're a personal productivity tool. He turned one into a business. Different outcome.

Superior

71,054 次观看 • 1 个月前

A kid in his tshirt sold an AI receptionist to a hair salon while drinking coffee. $399 a month from the one client. 30 minutes of work. He opened vacancies. Found a salon in Bay Park about to hire someone for $3,000 a month. Copied their website. ChatGPT wrote the system prompt. He dropped it into VAPI. 20 minutes later there was a voice agent answering calls in the salon's tone. He called the salon. Said nobody picked up yesterday. The owner apologized. The kid said cool, I built you an AI receptionist that answers 24/7. Want to hear it? He played the demo on the phone. The owner thinks he spent a week on it. He charges $399 a month. They save $2,600. He has 30 clients. His full setup is below.
1:20

A kid in his tshirt sold an AI receptionist to a hair salon while drinking coffee. $399 a month from the one client. 30 minutes of work. He opened vacancies. Found a salon in Bay Park about to hire someone for $3,000 a month. Copied their website. ChatGPT wrote the system prompt. He dropped it into VAPI. 20 minutes later there was a voice agent answering calls in the salon's tone. He called the salon. Said nobody picked up yesterday. The owner apologized. The kid said cool, I built you an AI receptionist that answers 24/7. Want to hear it? He played the demo on the phone. The owner thinks he spent a week on it. He charges $399 a month. They save $2,600. He has 30 clients. His full setup is below.

Superior

47,818 次观看 • 1 个月前

A guy runs AI ads for local roofers and they pay him $2,000-$5,000 a month each he doesn't film anything. He doesn't hire anyone he opens Facebook's Ad Library and finds ads that have been running for 6+ months - those are the proven winners then he drops them into Higgsfield and has it rebuild the same ad with the client's logo claude writes the script and the ad copy for him in one afternoon he's got 10-15 video ads for a roofing company that never ran a single ad before he launches them on Meta and leads start coming in through a simple form an AI bot texts every lead back in under 2 minutes and books them straight onto the client's calendar the roofer just wakes up to booked appointments. He has no idea AI did all of it some of these clients have paid him the same fee every month for 2 years straight he bills per lead or a flat retainer - either way it's recurring, and the AI does most of the work one skill, a few tools, and small local businesses that have never touched advertising save this, the quietest AI money right now isn't apps - it's running ads nobody knows are AI
35:18

A guy runs AI ads for local roofers and they pay him $2,000-$5,000 a month each he doesn't film anything. He doesn't hire anyone he opens Facebook's Ad Library and finds ads that have been running for 6+ months - those are the proven winners then he drops them into Higgsfield and has it rebuild the same ad with the client's logo claude writes the script and the ad copy for him in one afternoon he's got 10-15 video ads for a roofing company that never ran a single ad before he launches them on Meta and leads start coming in through a simple form an AI bot texts every lead back in under 2 minutes and books them straight onto the client's calendar the roofer just wakes up to booked appointments. He has no idea AI did all of it some of these clients have paid him the same fee every month for 2 years straight he bills per lead or a flat retainer - either way it's recurring, and the AI does most of the work one skill, a few tools, and small local businesses that have never touched advertising save this, the quietest AI money right now isn't apps - it's running ads nobody knows are AI

Archive

104,586 次观看 • 2 个月前

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.

57,919 次观看 • 2 个月前

Sam Altman shared a number that should change how you think about AI. Six and a half years ago, the heaviest AI user on the planet was an OpenAI employee. Using 100,000 tokens a month. That was considered insane at the time. The global average was basically zero. Today the global average is 100,000 tokens a month. What was insane is now normal. And the heaviest user at OpenAI right now? Hundreds of billions of tokens a month. Now here's where it gets wild. If the same pattern repeats, in another six and a half years the average person will use 500 billion tokens a month. That's a 5 million x increase from today. Think about what that means. → AI is not something you open once a day to ask a question anymore. It becomes always on. Running in the background across your work, education, personal life. → Agentic workflows, coding assistants, multi-step reasoning — that's what consumes billions of tokens. Not chatting. → OpenAI is already building for this. Hundreds of billions in infrastructure spend through 2030. Stargate. Partnerships with Microsoft, Oracle, Nvidia. And cost per token keeps falling roughly 10x every 12 months for the same capability level. So usage explodes because it keeps getting cheaper. The pattern is the same one we saw with computing, internet, and mobile. What the power user does today, the average person does in six years. Right now you are the power user. Act like it.
0:46

Sam Altman shared a number that should change how you think about AI. Six and a half years ago, the heaviest AI user on the planet was an OpenAI employee. Using 100,000 tokens a month. That was considered insane at the time. The global average was basically zero. Today the global average is 100,000 tokens a month. What was insane is now normal. And the heaviest user at OpenAI right now? Hundreds of billions of tokens a month. Now here's where it gets wild. If the same pattern repeats, in another six and a half years the average person will use 500 billion tokens a month. That's a 5 million x increase from today. Think about what that means. → AI is not something you open once a day to ask a question anymore. It becomes always on. Running in the background across your work, education, personal life. → Agentic workflows, coding assistants, multi-step reasoning — that's what consumes billions of tokens. Not chatting. → OpenAI is already building for this. Hundreds of billions in infrastructure spend through 2030. Stargate. Partnerships with Microsoft, Oracle, Nvidia. And cost per token keeps falling roughly 10x every 12 months for the same capability level. So usage explodes because it keeps getting cheaper. The pattern is the same one we saw with computing, internet, and mobile. What the power user does today, the average person does in six years. Right now you are the power user. Act like it.

Vaibhav Sisinty

24,323 次观看 • 2 天前

JENSEN HUANG PUT 1 PETAFLOP AND 128GB OF GPU MEMORY IN A $150,000 BOX. THE $249 JETSON RUNS THE SAME MODELS AND CUTS A $200/MONTH AI BILL TO $2 IN ELECTRICITY the $249 jetson orin nano super runs llama 3, mistral and deepseek locally at 67 trillion operations per second. zero api fees, zero data leaving your machine, $2 a month in electricity andrej karpathy says 99% of ai users are missing 7 basics that have nothing to do with the hardware. a proper config file, a /raw and /wiki folder, saved reference pages. the model stops guessing and starts helping most people pay $200 a month and still get bad output because the problem was never the model. it was the workflow around it. fix the system and a $249 box handles 80% of what you open chatgpt for the jetson breaks even in 6 weeks at $100/month api spend. after that every month is $98 back in your pocket. first year that's over $1,000 saved from a one-time $249 purchase the people building local ai infrastructure in 2026 with a proper workflow are going to look very far ahead in 2028 bookmark this and read the article below
0:33

JENSEN HUANG PUT 1 PETAFLOP AND 128GB OF GPU MEMORY IN A $150,000 BOX. THE $249 JETSON RUNS THE SAME MODELS AND CUTS A $200/MONTH AI BILL TO $2 IN ELECTRICITY the $249 jetson orin nano super runs llama 3, mistral and deepseek locally at 67 trillion operations per second. zero api fees, zero data leaving your machine, $2 a month in electricity andrej karpathy says 99% of ai users are missing 7 basics that have nothing to do with the hardware. a proper config file, a /raw and /wiki folder, saved reference pages. the model stops guessing and starts helping most people pay $200 a month and still get bad output because the problem was never the model. it was the workflow around it. fix the system and a $249 box handles 80% of what you open chatgpt for the jetson breaks even in 6 weeks at $100/month api spend. after that every month is $98 back in your pocket. first year that's over $1,000 saved from a one-time $249 purchase the people building local ai infrastructure in 2026 with a proper workflow are going to look very far ahead in 2028 bookmark this and read the article below

starmex

87,065 次观看 • 2 个月前

NVIDIA quietly built two desktop boxes that delete a $25,000/year AI subscription bill You don't rewrite your stack, you don't rent another data center, you just plug both into the wall and switch one line of code One looks like a deck of cards, the other like a hardback novel, together they replace ChatGPT Plus, Claude Pro, Cursor Pro, the OpenAI API meter, and every cloud GPU you were renting for fine-tunes It's built on the same CUDA stack the data center runs, which means once you migrate one workflow the rest follow on the same code path The reason NVIDIA shipped this is simple The bigger you scale on cloud AI, the harder you get taxed, and a one-person operator paying $2,100/month is producing exactly $0 of asset value at the end of every month And their solution is to skip the rental meter entirely, push inference back onto your desk, and let you loop agents overnight without watching a number tick on someone else's invoice This is much cheaper, faster, and pays itself back in 6 weeks for anyone already running AI for work But there is still a question nobody has answered yet, what happens when the next frontier model drops and your local 70B falls 6 months behind mid-quarter Also, technically a stack of four of the big box runs a 1.6 trillion parameter model on a desk for under $12,000 Even a fraction of that compute is more than most people will ever need in a year Bookmark this, it's worth coming back to when you have time 👇
0:35

NVIDIA quietly built two desktop boxes that delete a $25,000/year AI subscription bill You don't rewrite your stack, you don't rent another data center, you just plug both into the wall and switch one line of code One looks like a deck of cards, the other like a hardback novel, together they replace ChatGPT Plus, Claude Pro, Cursor Pro, the OpenAI API meter, and every cloud GPU you were renting for fine-tunes It's built on the same CUDA stack the data center runs, which means once you migrate one workflow the rest follow on the same code path The reason NVIDIA shipped this is simple The bigger you scale on cloud AI, the harder you get taxed, and a one-person operator paying $2,100/month is producing exactly $0 of asset value at the end of every month And their solution is to skip the rental meter entirely, push inference back onto your desk, and let you loop agents overnight without watching a number tick on someone else's invoice This is much cheaper, faster, and pays itself back in 6 weeks for anyone already running AI for work But there is still a question nobody has answered yet, what happens when the next frontier model drops and your local 70B falls 6 months behind mid-quarter Also, technically a stack of four of the big box runs a 1.6 trillion parameter model on a desk for under $12,000 Even a fraction of that compute is more than most people will ever need in a year Bookmark this, it's worth coming back to when you have time 👇

ZEUS⚡️

65,369 次观看 • 2 个月前

RTX 5090 ($2,000). Ollama (free). $2,000/month from clients who can't legally use Chat GPT5.5 xhigh,. here's the trade. the 5090 has 32GB of VRAM enough to run a 30B model locally without it ever touching the cloud. Ollama is one terminal command. setup is a Saturday afternoon. what you sell: 2-4 small businesses a private AI assistant that lives on your hardware, reads their docs, answers their team's questions, and never crosses their network. $500-1,000/month per retainer. three clients = $2,000+/month, every month, on a card that paid itself back in week one. who actually pays this: / law firms whose clients' contracts can't go in ChatGPT / accountants drowning in client books they can't paste anywhere public / real estate brokerages with vendor data they signed NDAs over / clinics, e-commerce ops, anyone whose "we use ChatGPT" answer gets them a lawyer's email they don't need "smart AI." they need private AI that runs somewhere they trust. for $2,000 in hardware, that "somewhere" is now a card on your desk. the AI freelance market in 2026 isn't about who writes the best prompt. it's about who can host a 30B model on silicon no client's legal team has to ask about.
0:20

RTX 5090 ($2,000). Ollama (free). $2,000/month from clients who can't legally use Chat GPT5.5 xhigh,. here's the trade. the 5090 has 32GB of VRAM enough to run a 30B model locally without it ever touching the cloud. Ollama is one terminal command. setup is a Saturday afternoon. what you sell: 2-4 small businesses a private AI assistant that lives on your hardware, reads their docs, answers their team's questions, and never crosses their network. $500-1,000/month per retainer. three clients = $2,000+/month, every month, on a card that paid itself back in week one. who actually pays this: / law firms whose clients' contracts can't go in ChatGPT / accountants drowning in client books they can't paste anywhere public / real estate brokerages with vendor data they signed NDAs over / clinics, e-commerce ops, anyone whose "we use ChatGPT" answer gets them a lawyer's email they don't need "smart AI." they need private AI that runs somewhere they trust. for $2,000 in hardware, that "somewhere" is now a card on your desk. the AI freelance market in 2026 isn't about who writes the best prompt. it's about who can host a 30B model on silicon no client's legal team has to ask about.

dunik

157,551 次观看 • 2 个月前

A guy got tired of renting intelligence from the cloud, so he put a 120-billion-parameter model in his closet for $0 a month. One mini PC. The Minisforum MS-S1 MAX. 128GB of unified memory, and a trick that hands 96GB of it straight to the GPU. Here's how it breaks: That 96GB is the whole game. Enough to run GPT-OSS-120B fully local, and still keep the agent and dashboard on the same box. 120 billion parameters. 56.6 tokens a second. A 5,000-word essay in one pass at 110W and 68°C. Quiet. Cool. Local. Then Hermes Agent goes on top, pointed at localhost. No API key, because there's nothing to phone home to. It drafts, researches, runs tool calls, manages sub-agents. None of it leaves the network. The cloud version cost $10 to $20 a day, keys and customer data routed through machines he didn't own. Now it's a box in a closet. $0 a month. The chip is real. The build is brilliant. And somewhere in the first few minutes, the AI stopped being a bill he paid every morning and became a machine he owns, humming in a closet, working for free.
0:39

A guy got tired of renting intelligence from the cloud, so he put a 120-billion-parameter model in his closet for $0 a month. One mini PC. The Minisforum MS-S1 MAX. 128GB of unified memory, and a trick that hands 96GB of it straight to the GPU. Here's how it breaks: That 96GB is the whole game. Enough to run GPT-OSS-120B fully local, and still keep the agent and dashboard on the same box. 120 billion parameters. 56.6 tokens a second. A 5,000-word essay in one pass at 110W and 68°C. Quiet. Cool. Local. Then Hermes Agent goes on top, pointed at localhost. No API key, because there's nothing to phone home to. It drafts, researches, runs tool calls, manages sub-agents. None of it leaves the network. The cloud version cost $10 to $20 a day, keys and customer data routed through machines he didn't own. Now it's a box in a closet. $0 a month. The chip is real. The build is brilliant. And somewhere in the first few minutes, the AI stopped being a bill he paid every morning and became a machine he owns, humming in a closet, working for free.

shmidt

245,607 次观看 • 1 个月前

A guy installed a mini Nvidia AI data center on his house and gets paid monthly The box is the size of a small fridge and bolts right onto the wall. Inside it is packed with Nvidia GPUs running AI workloads 24/7. He hooked it up next to his AC and that was it. Now the company pays him a flat fee for the power and Wi-Fi it uses. He says it lands him around $2,500 a month straight into his account. The unit even helps cool the side of his house, dropping his AC bill by $150. That stacks to over $30,000 a year for doing literally nothing. His mortgage is now fully paid by a box in his yard. The crazy part is regular homes are quietly becoming AI infrastructure. Save this, you are watching the next gold rush hit the suburbs.
0:33

A guy installed a mini Nvidia AI data center on his house and gets paid monthly The box is the size of a small fridge and bolts right onto the wall. Inside it is packed with Nvidia GPUs running AI workloads 24/7. He hooked it up next to his AC and that was it. Now the company pays him a flat fee for the power and Wi-Fi it uses. He says it lands him around $2,500 a month straight into his account. The unit even helps cool the side of his house, dropping his AC bill by $150. That stacks to over $30,000 a year for doing literally nothing. His mortgage is now fully paid by a box in his yard. The crazy part is regular homes are quietly becoming AI infrastructure. Save this, you are watching the next gold rush hit the suburbs.

winkle.

7,178,973 次观看 • 2 个月前

Do you actually understand what's happening right now. Everyone is talking about AI agents. Nobody is talking about selling them as a business. And this guy just literally built himself a system on a mini PC that makes $20,000/month doing exactly that. Small businesses are paying $20,000-$30,000/month for ops teams doing repetitive work. He replaces 80% of it with Claude agents for $200/month in tools. Charges $2,500/month to maintain them. The client is saving money from day one. He's collecting a retainer forever. 8 clients. $20,000/month. 85% margin. Every business in your city is a potential client. Most of them have never heard of n8n or Claude API. They just know their team spends too much time on things that should be automatic. That's the pitch. That's the business. Most people are still watching. A few are already billing.
1:30

Do you actually understand what's happening right now. Everyone is talking about AI agents. Nobody is talking about selling them as a business. And this guy just literally built himself a system on a mini PC that makes $20,000/month doing exactly that. Small businesses are paying $20,000-$30,000/month for ops teams doing repetitive work. He replaces 80% of it with Claude agents for $200/month in tools. Charges $2,500/month to maintain them. The client is saving money from day one. He's collecting a retainer forever. 8 clients. $20,000/month. 85% margin. Every business in your city is a potential client. Most of them have never heard of n8n or Claude API. They just know their team spends too much time on things that should be automatic. That's the pitch. That's the business. Most people are still watching. A few are already billing.

Superior

287,160 次观看 • 1 个月前