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A $1,800 MINI PC RUNS CLAUDE CODE WITHOUT THE INTERNET it looks like a hardcover book sitting on a shelf, but this is the GMKtec EVO-X2, and it changes the local AI math completely built on AMD's Ryzen AI Max+ 395, with 128GB of unified memory shared between CPU...

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13,321 次观看 • 2 个月前 •via X (Twitter)

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AMD'S NEW MINI PC RUNS CLAUDE CODE OFFLINE FOR $0/MONTH AND REPLACES $200 OPENAI + $200 CLAUDE CODE SUBSCRIPTIONS 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 coder 30b at 40 to 50 tokens per second and llama 3.3 70b at 20 to 25 tokens per second locally. on linux you get 110gb of usable vram out of 128gb setup takes 90 minutes. wipe windows for linux, install ollama with one command, pull the model, point claude code at localhost. same interface, same agent loop, nothing leaves your network a heavy ai user pays $200 for claude code max, $200 for chatgpt pro and $20 for cursor. that's $5,040 a year and the box pays itself off in 5 months after break-even every month is $420 that used to leave your account. three year math is roughly $13,000 not paid to ai companies plus zero rate limits on overnight agents bookmark this and read the article below
0:52

AMD'S NEW MINI PC RUNS CLAUDE CODE OFFLINE FOR $0/MONTH AND REPLACES $200 OPENAI + $200 CLAUDE CODE SUBSCRIPTIONS 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 coder 30b at 40 to 50 tokens per second and llama 3.3 70b at 20 to 25 tokens per second locally. on linux you get 110gb of usable vram out of 128gb setup takes 90 minutes. wipe windows for linux, install ollama with one command, pull the model, point claude code at localhost. same interface, same agent loop, nothing leaves your network a heavy ai user pays $200 for claude code max, $200 for chatgpt pro and $20 for cursor. that's $5,040 a year and the box pays itself off in 5 months after break-even every month is $420 that used to leave your account. three year math is roughly $13,000 not paid to ai companies plus zero rate limits on overnight agents bookmark this and read the article below

starmex

33,516 次观看 • 2 个月前

AMD CEO LISA SU HELD A MINI PC ON STAGE THAT RUNS A 235B MODEL AND REPLACES YOUR $440/MONTH AI STACK amd's ryzen ai max+ 395 is the first x86 chip that runs a 200 billion parameter model on one piece of silicon. cpu and gpu share 128gb of unified memory, no separate graphics card needed 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 install ollama, pull the model, point claude code at localhost. same interface, nothing leaves the machine, nothing costs per request bookmark this and read the article below
0:59

AMD CEO LISA SU HELD A MINI PC ON STAGE THAT RUNS A 235B MODEL AND REPLACES YOUR $440/MONTH AI STACK amd's ryzen ai max+ 395 is the first x86 chip that runs a 200 billion parameter model on one piece of silicon. cpu and gpu share 128gb of unified memory, no separate graphics card needed 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 install ollama, pull the model, point claude code at localhost. same interface, nothing leaves the machine, nothing costs per request bookmark this and read the article below

starmex

980,139 次观看 • 2 个月前

A $1,800 MINI PC ON YOUR DESK JUST MADE $5,040 A YEAR IN AI SUBSCRIPTIONS POINTLESS Claude Code Max, ChatGPT Pro, Cursor. That's $420 a month just to keep the workflow alive. A GMKtec mini PC with 128GB of unified memory runs the same stack locally for a one time cost. Ollama, Linux, local endpoints, Claude Code pointed at your own machine. Every prompt stays on your desk. Nothing touches the cloud.
8:33

A $1,800 MINI PC ON YOUR DESK JUST MADE $5,040 A YEAR IN AI SUBSCRIPTIONS POINTLESS Claude Code Max, ChatGPT Pro, Cursor. That's $420 a month just to keep the workflow alive. A GMKtec mini PC with 128GB of unified memory runs the same stack locally for a one time cost. Ollama, Linux, local endpoints, Claude Code pointed at your own machine. Every prompt stays on your desk. Nothing touches the cloud.

0xMarioNawfal

50,730 次观看 • 2 个月前

THIS GUY WIRED GMKTEC EVO-X2 BOXES, A $40 USB-C BRICK AND AN RTX 3090 INTO A $6,800/MONTH OFFLINE AI FARM it looks like a messy rack with purple cables, mini pcs and a gpu lying on the desk. but the real point is brutal: one $1,800 gmktec evo-x2 can replace a $440/month ai stack, then the rack turns it into a local backend. the evo-x2 runs amd’s ryzen ai max+ 395 with 128gb of unified memory shared between cpu, gpu and npu. on linux, that gives up to 110gb of usable vram for local models without renting cloud compute. that is why the setup gets weird. qwen3-coder 30b, llama 3.3 70b, deepseek v3 and 200b-class models can run from boxes smaller than consoles. the rtx 3090 becomes a 24gb side node, not the whole system. the $40 anker nano ii 65w brick is the funny part. cheap power, tiny machines, one old gpu and local inference. the whole stack starts looking less like a workstation and more like a private ai grid. the subscription math is ugly. claude code max is $200/month, chatgpt pro is $200/month, cursor is $20/month and gemini adds another $20. that is $5,280/year before api usage even starts. point claude code at localhost, pull models through ollama and run agents all day: code reviews, scraping, transcription, research reports and client automations. 3 clients at $2,200/month turns this into a $6,800/month backend. bookmark this and read the article below
0:47

THIS GUY WIRED GMKTEC EVO-X2 BOXES, A $40 USB-C BRICK AND AN RTX 3090 INTO A $6,800/MONTH OFFLINE AI FARM it looks like a messy rack with purple cables, mini pcs and a gpu lying on the desk. but the real point is brutal: one $1,800 gmktec evo-x2 can replace a $440/month ai stack, then the rack turns it into a local backend. the evo-x2 runs amd’s ryzen ai max+ 395 with 128gb of unified memory shared between cpu, gpu and npu. on linux, that gives up to 110gb of usable vram for local models without renting cloud compute. that is why the setup gets weird. qwen3-coder 30b, llama 3.3 70b, deepseek v3 and 200b-class models can run from boxes smaller than consoles. the rtx 3090 becomes a 24gb side node, not the whole system. the $40 anker nano ii 65w brick is the funny part. cheap power, tiny machines, one old gpu and local inference. the whole stack starts looking less like a workstation and more like a private ai grid. the subscription math is ugly. claude code max is $200/month, chatgpt pro is $200/month, cursor is $20/month and gemini adds another $20. that is $5,280/year before api usage even starts. point claude code at localhost, pull models through ollama and run agents all day: code reviews, scraping, transcription, research reports and client automations. 3 clients at $2,200/month turns this into a $6,800/month backend. bookmark this and read the article below

Gipp 🦅

20,031 次观看 • 2 个月前

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
1:06

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

93,465 次观看 • 2 个月前

AMD CEO Lisa Su showcased a mini PC that could replace your entire AI stack what's changed: - 128GB of unified memory on a single chip - the CPU and GPU share the same memory space - a 235-billion-parameter model can be loaded entirely locally - no cloud, no subscriptions, no logs an active AI user spends around $420 a month on subscriptions - that's $5,280 a year the EVO-X2 costs $1,800 nstall ollama, pull the model, point claude code at localhost. same interface, nothing leaves the machine, nothing costs per request bookmark this and read the article below
0:59

AMD CEO Lisa Su showcased a mini PC that could replace your entire AI stack what's changed: - 128GB of unified memory on a single chip - the CPU and GPU share the same memory space - a 235-billion-parameter model can be loaded entirely locally - no cloud, no subscriptions, no logs an active AI user spends around $420 a month on subscriptions - that's $5,280 a year the EVO-X2 costs $1,800 nstall ollama, pull the model, point claude code at localhost. same interface, nothing leaves the machine, nothing costs per request bookmark this and read the article below

kepo

15,451 次观看 • 1 个月前

THIS GUY OPENED A TINY PC AND SHOWED HOW A $1,800 GMKTEC EVO-X2 TURNS INTO A LOCAL AI SERVER not a cloud dashboard. not another $200/mo subscription. just one box on a desk, upgraded with storage, cleaner airflow, faster networking, and pointed at real local models. the numbers are what make it interesting. Claude Code Max is $200/mo, ChatGPT Pro is $200/mo, Cursor is another $20/mo. that is $5,040/year just to rent tools most people use for coding, research, summaries, and agents. EVO-X2 flips the setup because it has 128GB unified memory, Ryzen AI Max+ 395, and up to 110GB usable as VRAM on Linux. enough room for Qwen3-Coder 30B, Llama 70B, and 200B-class local models when speed is not the bottleneck. so the workflow becomes simple: buy the box once, install Linux, run the model locally, connect the CLI, and let the machine handle jobs from your own network instead of sending every request to the cloud. this is where the real edge starts. overnight code audits, private document search, local RAG, scraping agents, transcription, file cleanup, all running while the token meter stays at zero. frontier models still win for the hardest prompts. but for daily automation, coding, research, and private workflows, local AI is already moving from nerd setup to obvious business math. the next flex won’t be “which AI plan do you pay for?” it’ll be “what’s running under your desk?”
1:09

THIS GUY OPENED A TINY PC AND SHOWED HOW A $1,800 GMKTEC EVO-X2 TURNS INTO A LOCAL AI SERVER not a cloud dashboard. not another $200/mo subscription. just one box on a desk, upgraded with storage, cleaner airflow, faster networking, and pointed at real local models. the numbers are what make it interesting. Claude Code Max is $200/mo, ChatGPT Pro is $200/mo, Cursor is another $20/mo. that is $5,040/year just to rent tools most people use for coding, research, summaries, and agents. EVO-X2 flips the setup because it has 128GB unified memory, Ryzen AI Max+ 395, and up to 110GB usable as VRAM on Linux. enough room for Qwen3-Coder 30B, Llama 70B, and 200B-class local models when speed is not the bottleneck. so the workflow becomes simple: buy the box once, install Linux, run the model locally, connect the CLI, and let the machine handle jobs from your own network instead of sending every request to the cloud. this is where the real edge starts. overnight code audits, private document search, local RAG, scraping agents, transcription, file cleanup, all running while the token meter stays at zero. frontier models still win for the hardest prompts. but for daily automation, coding, research, and private workflows, local AI is already moving from nerd setup to obvious business math. the next flex won’t be “which AI plan do you pay for?” it’ll be “what’s running under your desk?”

Gipp 🦅

13,271 次观看 • 1 个月前

> you pay $5,000 a year for AI > and still ration every request > AMD just broke that math > Ryzen AI Max+ 395. 200B on one die. > EVO-X2. Claude Code. one evening. > one variable and Claude Code points at your room > nothing leaves the network. nothing on the meter. > stop paying per token stop rationing > the edge isn't the cloud. it's the meter being off.
0:31

> you pay $5,000 a year for AI > and still ration every request > AMD just broke that math > Ryzen AI Max+ 395. 200B on one die. > EVO-X2. Claude Code. one evening. > one variable and Claude Code points at your room > nothing leaves the network. nothing on the meter. > stop paying per token stop rationing > the edge isn't the cloud. it's the meter being off.

RetroChainer

81,891 次观看 • 2 个月前

THE CHINESE INSTALLED 6 AI AGENTS RUNNING 24/7 FOR $11 A MONTH. THE BOX UNDER ONE DESK REPLACED $1,200 IN CLOUD SUBSCRIPTIONS. The Minisforum MS-S1 Max ships with 128GB of unified memory shared between CPU and GPU. Qwen3-Coder 30B runs at 40 to 50 tokens per second. 6 agents run simultaneously without anyone watching the meter. An inbox sorter drafts replies every 15 minutes. A research monitor watches 30+ feeds and lands a digest by 7 AM, a job that costs $15 to $20 a day on cloud APIs. The same stack on cloud subscriptions ran $800 to $1,200 a month. The hardware costs $3,000 once. Break-even hits month 3 to 4. The real shift is behavior, not savings. A meeting prep agent never would have justified per-token cost. Running it free overnight made it obvious.
0:53

THE CHINESE INSTALLED 6 AI AGENTS RUNNING 24/7 FOR $11 A MONTH. THE BOX UNDER ONE DESK REPLACED $1,200 IN CLOUD SUBSCRIPTIONS. The Minisforum MS-S1 Max ships with 128GB of unified memory shared between CPU and GPU. Qwen3-Coder 30B runs at 40 to 50 tokens per second. 6 agents run simultaneously without anyone watching the meter. An inbox sorter drafts replies every 15 minutes. A research monitor watches 30+ feeds and lands a digest by 7 AM, a job that costs $15 to $20 a day on cloud APIs. The same stack on cloud subscriptions ran $800 to $1,200 a month. The hardware costs $3,000 once. Break-even hits month 3 to 4. The real shift is behavior, not savings. A meeting prep agent never would have justified per-token cost. Running it free overnight made it obvious.

Lummox

14,093 次观看 • 1 个月前

$5,280 a year on AI subscriptions. Claude Max, ChatGPT Pro, Gemini, Cursor. $440 every month going to the cloud. a mini PC for $1,700 does the same thing on your desk. GMKtec EVO-X2 - a box the size of a hardcover book. inside it the chip that Lisa Su personally brought on stage at CES and signed with her name. 128GB of memory in one pool. runs models that cloud subscriptions behind $200 paywalls throttle during peak hours. here there are no limits - your hardware, your rules. NVIDIA's RTX 5080 at $1,000+ lost to this box by 3x on a real AI workload. a discrete GPU beaten by a mini PC the size of a lunchbox. electricity - $9 a month. pays for itself in 10 months. after that $440 every month stays in your pocket. the cloud made sense when nothing on a desk could compete. now it can.
0:32

$5,280 a year on AI subscriptions. Claude Max, ChatGPT Pro, Gemini, Cursor. $440 every month going to the cloud. a mini PC for $1,700 does the same thing on your desk. GMKtec EVO-X2 - a box the size of a hardcover book. inside it the chip that Lisa Su personally brought on stage at CES and signed with her name. 128GB of memory in one pool. runs models that cloud subscriptions behind $200 paywalls throttle during peak hours. here there are no limits - your hardware, your rules. NVIDIA's RTX 5080 at $1,000+ lost to this box by 3x on a real AI workload. a discrete GPU beaten by a mini PC the size of a lunchbox. electricity - $9 a month. pays for itself in 10 months. after that $440 every month stays in your pocket. the cloud made sense when nothing on a desk could compete. now it can.

Ventry

27,360 次观看 • 2 个月前

Claude Code costs $200/month here's how to run it for free. 4 commands. 10 minutes step 1 - install Ollama runs AI models locally → download from → install. it runs in background on localhost:11434 step 2 - download a coding model → ollama pull qwen2.5-coder:14b (7b for 8GB RAM, 32b for 32GB+ RAM) step 3 - redirect Claude Code to your machine → export ANTHROPIC_BASE_URL= → export ANTHROPIC_MODEL=qwen2.5-coder:14b step 4 - launch → claude → "make a hello world website" → it reads files, writes code, runs commands. locally. free same agent loop. same tools. $0/month the $200 was for convenience the capability was always free like + bookmark - you'll need this
1:41

Claude Code costs $200/month here's how to run it for free. 4 commands. 10 minutes step 1 - install Ollama runs AI models locally → download from → install. it runs in background on localhost:11434 step 2 - download a coding model → ollama pull qwen2.5-coder:14b (7b for 8GB RAM, 32b for 32GB+ RAM) step 3 - redirect Claude Code to your machine → export ANTHROPIC_BASE_URL= → export ANTHROPIC_MODEL=qwen2.5-coder:14b step 4 - launch → claude → "make a hello world website" → it reads files, writes code, runs commands. locally. free same agent loop. same tools. $0/month the $200 was for convenience the capability was always free like + bookmark - you'll need this

self.dll

178,272 次观看 • 4 个月前

The companies charging $200/month for AI assumed local hardware would never catch up. It caught up. He's assembling the proof right now. A PC that runs Qwen 3.6 27B a free model that beats Claude on vision by 7 points. DeepSeek R1 for math and reasoning. Llama 3.3 70B for everything else. All local. All free. All forever. Electricity: $9/month. Subscriptions: $0. He used to pay $459/month for Claude Code, ChatGPT Pro, and Cursor. That's $5,500 a year going to someone else's servers. The hardware he's building costs less than one year of that bill. And it never sends another invoice. He's still assembling it. The subscription renewal reminder hit his inbox while he was putting it together. He ignored it.
0:59

The companies charging $200/month for AI assumed local hardware would never catch up. It caught up. He's assembling the proof right now. A PC that runs Qwen 3.6 27B a free model that beats Claude on vision by 7 points. DeepSeek R1 for math and reasoning. Llama 3.3 70B for everything else. All local. All free. All forever. Electricity: $9/month. Subscriptions: $0. He used to pay $459/month for Claude Code, ChatGPT Pro, and Cursor. That's $5,500 a year going to someone else's servers. The hardware he's building costs less than one year of that bill. And it never sends another invoice. He's still assembling it. The subscription renewal reminder hit his inbox while he was putting it together. He ignored it.

Superior

444,762 次观看 • 1 个月前

A GIRL BOUGHT A $599 APPLE BOX AND CUT HER AI COSTS FROM $459/MONTH TO $23/MONTH. THE MAC MINI M4 IS QUIETLY BECOMING THE CHEAPEST AI SETUP IN 2026 she didn’t buy it because it looked nice on her desk. she bought it because paying for claude, chatgpt, cursor and api usage every month was getting ridiculous the setup is simple. mac mini m4, ollama, open webui, and local models like qwen, deepseek and llama. for most daily work, that’s enough to write, code, summarize, search notes, and run private workflows without sending everything to the cloud that’s why the math looks so good. a heavy ai stack can hit $459 a month, or $5,508 a year. the mac mini starts at $599 and uses around $3 a month in electricity. if it handles even 70 to 80% of the workload, it pays for itself fast install ollama, point your tools to localhost, and the workflow changes immediately. no token stress, no rate limits, no wondering where your files are going you still keep one cloud model for the hardest tasks but once a small box on your desk does most of the work, paying full price for everything starts to feel stupid
0:23

A GIRL BOUGHT A $599 APPLE BOX AND CUT HER AI COSTS FROM $459/MONTH TO $23/MONTH. THE MAC MINI M4 IS QUIETLY BECOMING THE CHEAPEST AI SETUP IN 2026 she didn’t buy it because it looked nice on her desk. she bought it because paying for claude, chatgpt, cursor and api usage every month was getting ridiculous the setup is simple. mac mini m4, ollama, open webui, and local models like qwen, deepseek and llama. for most daily work, that’s enough to write, code, summarize, search notes, and run private workflows without sending everything to the cloud that’s why the math looks so good. a heavy ai stack can hit $459 a month, or $5,508 a year. the mac mini starts at $599 and uses around $3 a month in electricity. if it handles even 70 to 80% of the workload, it pays for itself fast install ollama, point your tools to localhost, and the workflow changes immediately. no token stress, no rate limits, no wondering where your files are going you still keep one cloud model for the hardest tasks but once a small box on your desk does most of the work, paying full price for everything starts to feel stupid

Gipp 🦅

457,929 次观看 • 2 个月前

NVIDIA CEO JENSEN HUANG UNVEILED THE RTX 3090 AND THE USED VERSION ON EBAY NOW KILLS A $400/MONTH CLAUDE CODE AND OPENAI BILL the rtx 3090 has 24gb of vram, the same as a new rtx 4090 that costs $2,000. for local ai inference vram matters more than anything else and the 3090 sells for $650-800 used it runs qwen 3.6 27b comfortably, deepseek r1 14b at 60+ tokens per second and mistral 7b for fast automation. 16gb of qwen 3.6 fits with 8gb of headroom for long context alibaba's qwen 3.6 27b beats claude 4.5 opus on realworldqa vision 84.1 vs 77.0 and on ifbench instructions 76.5 vs 58.0. a free open weight model out-benchmarks anthropic's flagship 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 a used 3090 pays itself off in 3.5 months install ollama, pull qwen 3.6 27b, point claude code at localhost. same interface, nothing leaves the machine, nothing costs per request bookmark this and read the article below
0:33

NVIDIA CEO JENSEN HUANG UNVEILED THE RTX 3090 AND THE USED VERSION ON EBAY NOW KILLS A $400/MONTH CLAUDE CODE AND OPENAI BILL the rtx 3090 has 24gb of vram, the same as a new rtx 4090 that costs $2,000. for local ai inference vram matters more than anything else and the 3090 sells for $650-800 used it runs qwen 3.6 27b comfortably, deepseek r1 14b at 60+ tokens per second and mistral 7b for fast automation. 16gb of qwen 3.6 fits with 8gb of headroom for long context alibaba's qwen 3.6 27b beats claude 4.5 opus on realworldqa vision 84.1 vs 77.0 and on ifbench instructions 76.5 vs 58.0. a free open weight model out-benchmarks anthropic's flagship 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 a used 3090 pays itself off in 3.5 months install ollama, pull qwen 3.6 27b, point claude code at localhost. same interface, nothing leaves the machine, nothing costs per request bookmark this and read the article below

starmex

86,410 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

THIS PORTABLE HACKER KIT PACKS A RASPBERRY PI 5 WITH 16GB OF RAM AND A 512GB NVME THAT ALSO RUNS LOCAL LLMs, KILLED $200 CLAUDE CODE MAX AND $200 CHATGPT PRO SUBSCRIPTIONS THE DAY IT WENT MOBILE 00:08 he sets down the pi and starts the tour, "this is my raspberry pi 5, 16 gigs of ram, 512 gigabyte nvme ssd storage, this thing means business" the kit stacks the pi next to a bluetooth analyzer, a 5g wifi router with a battery, and a pen-testing dongle for packet injection, the whole rig runs off usb-c and fits in a shoulder bag he uses it for evil-twin wifi tests and bluetooth device audits, and the same pi 5 also handles ollama with a 7b or 14b model locally at usable speed with every packet capture staying inside the case claude code points at localhost through a single environment variable, the cli behaves identically to the cloud version except every token generates on the pi in his hand and the api bill never arrives $200 chatgpt pro and $200 claude code max used to hit the same card that pays his internet, the whole subscription stack died the day the pi got mobile and ai bills went to zero because the model runs on the same box that runs his packet capture bookmark this and read the article below
1:03

THIS PORTABLE HACKER KIT PACKS A RASPBERRY PI 5 WITH 16GB OF RAM AND A 512GB NVME THAT ALSO RUNS LOCAL LLMs, KILLED $200 CLAUDE CODE MAX AND $200 CHATGPT PRO SUBSCRIPTIONS THE DAY IT WENT MOBILE 00:08 he sets down the pi and starts the tour, "this is my raspberry pi 5, 16 gigs of ram, 512 gigabyte nvme ssd storage, this thing means business" the kit stacks the pi next to a bluetooth analyzer, a 5g wifi router with a battery, and a pen-testing dongle for packet injection, the whole rig runs off usb-c and fits in a shoulder bag he uses it for evil-twin wifi tests and bluetooth device audits, and the same pi 5 also handles ollama with a 7b or 14b model locally at usable speed with every packet capture staying inside the case claude code points at localhost through a single environment variable, the cli behaves identically to the cloud version except every token generates on the pi in his hand and the api bill never arrives $200 chatgpt pro and $200 claude code max used to hit the same card that pays his internet, the whole subscription stack died the day the pi got mobile and ai bills went to zero because the model runs on the same box that runs his packet capture bookmark this and read the article below

starmex

25,094 次观看 • 1 个月前

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.
0:50

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.

AdiiX

3,392,892 次观看 • 2 个月前

AMD on local AI: "this is the smallest AI development system in the world, capable of running models up to 200 billion parameters locally, not connected to anything" 128GB of unified memory shared by CPU, GPU, and NPU fits in your hand. Runs a model larger than GPT-3 with no internet $3,999 once. roughly $16 a month in power Cloud equivalent: up to $750 a month The question was never whether local AI could compete on power It was whether it could compete on price. Now it does
1:00

AMD on local AI: "this is the smallest AI development system in the world, capable of running models up to 200 billion parameters locally, not connected to anything" 128GB of unified memory shared by CPU, GPU, and NPU fits in your hand. Runs a model larger than GPT-3 with no internet $3,999 once. roughly $16 a month in power Cloud equivalent: up to $750 a month The question was never whether local AI could compete on power It was whether it could compete on price. Now it does

plutos

152,392 次观看 • 2 个月前

A 23-YEARS-OLD MADE $22,500 USING MAC MINI M4 THAT CUT DEVELOPER AI CREDITS BY 80 PERCENT A typical developer spending $150 to $200 a month on Claude or OpenAI API credits can route routine work to local models and keep cloud models for hard reasoning. The stack is simple : Mac Mini M4, Ollama, LiteLLM, Open WebUI, Qwen, Llama, Gemma or Phi. The math is the hook. Electricity costs $3 to $5 a month, while cron jobs, summaries, formatting, code reviews and draft emails stop burning paid tokens. The edge is not replacing Claude. It is using Claude only where Claude actually matters.
0:33

A 23-YEARS-OLD MADE $22,500 USING MAC MINI M4 THAT CUT DEVELOPER AI CREDITS BY 80 PERCENT A typical developer spending $150 to $200 a month on Claude or OpenAI API credits can route routine work to local models and keep cloud models for hard reasoning. The stack is simple : Mac Mini M4, Ollama, LiteLLM, Open WebUI, Qwen, Llama, Gemma or Phi. The math is the hook. Electricity costs $3 to $5 a month, while cron jobs, summaries, formatting, code reviews and draft emails stop burning paid tokens. The edge is not replacing Claude. It is using Claude only where Claude actually matters.

BeingInvested

11,805 次观看 • 1 个月前

I just found a way to use Claude Code completely free. Claude Code is Anthropic’s terminal coding agent that usually needs a paid API key to run. But a viral GitHub project called Free Claude Code, now sitting at 37k stars, lets you skip the billing entirely. It works as a tiny proxy that sits between Claude Code and free model providers like NVIDIA NIM, OpenRouter, DeepSeek, and Gemini. Every request Claude Code would send to Anthropic gets quietly rerouted to a free model on the other side. The interface stays the same. What’s actually thinking behind it changes. Setup takes a couple of quick commands and a free API key from NVIDIA NIM or OpenRouter. Paste it into the local dashboard, pick a model, and you’re building. The catch is you’re not really using Claude anymore. But when the code ships, does the model badge matter? -- I have shared the Github Link in my free Whatsapp Community ↓
0:36

I just found a way to use Claude Code completely free. Claude Code is Anthropic’s terminal coding agent that usually needs a paid API key to run. But a viral GitHub project called Free Claude Code, now sitting at 37k stars, lets you skip the billing entirely. It works as a tiny proxy that sits between Claude Code and free model providers like NVIDIA NIM, OpenRouter, DeepSeek, and Gemini. Every request Claude Code would send to Anthropic gets quietly rerouted to a free model on the other side. The interface stays the same. What’s actually thinking behind it changes. Setup takes a couple of quick commands and a free API key from NVIDIA NIM or OpenRouter. Paste it into the local dashboard, pick a model, and you’re building. The catch is you’re not really using Claude anymore. But when the code ships, does the model badge matter? -- I have shared the Github Link in my free Whatsapp Community ↓

Vaibhav Sisinty

36,809 次观看 • 1 个月前