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$35 QUAD-CORE ARM BOX STAPLED TO A HARBOR FREIGHT SOLAR PANEL IN HIS GARAGE RUNS A LOCAL LLM ON $60 OF CHARGE CONTROLLER GEAR AND A T-MOBILE 5G BACKUP LINK, KILLED $200 CHATGPT PRO AND $200 CLAUDE CODE MAX SUBSCRIPTIONS THE WEEK HE WENT OFF-GRID 00:03 marco tilts the...

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starmex

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21,856 次观看 • 2 个月前 •via X (Twitter)

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15 条评论

Vash ✝️he Stampede 的头像
Vash ✝️he Stampede2 个月前

Yea dog that ain't replacing ChatGPT if I can fire off GPT 5.6 Sol at high effort and one shot most tasks and OpenAI being generous with resets. It's cool they were able to do that though.

Scry 的头像
Scry2 个月前

The interesting part isn't running AI on solar. It's how little power local models can need for everyday tasks

Alexandra Swara 的头像
Alexandra Swara2 个月前

Bro went full rogue with harbor freight tech and won. Peak cyberpunk energy.

dhinna ship .ico 的头像
dhinna ship .ico2 个月前

The $35 ARM box runs tiny models fine. Multi-step coding agents still force me back to Claude once context fills

lagerskoy 的头像
lagerskoy2 个月前

the interesting part is not that a pi beats frontier models, it is that useful local inference can run almost anywhere now

John AI 的头像
John AI2 个月前

building an off grid ai rig like that is absolute legend tier engineering

crucial 的头像
crucial2 个月前

thx 4 info , saved

ALEXYZ 的头像
ALEXYZ2 个月前

$35 box. Subscriptions dead. Off grid wins hard.

AI Mastery Guide 的头像
AI Mastery Guide2 个月前

Running local AI off solar and a battery pack instead of paying for cloud subscriptions is genuinely clever 🔋

/ 的头像
/1 个月前

Very impressive! but def won’t replace claude code max nor gpt pro cmon now

Radar 24h 的头像
Radar 24h2 个月前

Anh ấy thật sáng tạo và tiết kiệm!

Tsera 的头像
Tsera2 个月前

Solar power, zero subscriptions.

www 的头像
www2 个月前

Local LLMs are a smart escape from $200/month subscriptions. But some jobs still need a stronger cloud lane for build/test work. Before paying, test it. unlimitedcodex gives 1-hour Codex/OpenAI-compatible test keys via profile site.

GaleForceAI 的头像
GaleForceAI2 个月前

I've run Ollama on similar hardware. Fine for quick queries, wouldn't reach for it over Claude for anything serious. The off-grid power setup is the clever bit.

Fokki 的头像
Fokki2 个月前

$35 worth it

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THIS SOLAR-POWERED MESH NODE PACKS A LOCAL LLM AND A 6-WATT PANEL, KILLED $200 CLAUDE CODE MAX AND $200 CHATGPT PRO SUBSCRIPTIONS THE DAY IT WENT LIVE AND RUNS AT $0/MO EVEN UNDER CLOUD COVER 00:22 he taps the case with the red led blinking, "even though we have complete cloud cover today, the sun's not even out and we're still getting a charge, that's absolutely phenomenal" the node runs a rak 4630 lora board with a 6-watt solar panel, a small battery bank inside the ip67 case, and a raspberry pi zero 2w wedged next to it running a quantized 3b model on ollama from the rooftop it services 71 other meshtastic nodes across the neighborhood offline, and the same box also handles ai queries piped in over the mesh from his phone without touching the internet claude code points at the pi over tailscale, the cli behaves identically to the cloud version except every token generates on his own rooftop under the panel that keeps charging through cloud cover $200 chatgpt pro and $200 claude code max used to hit his card monthly, and the whole stack died the day the rooftop went live because ai queries now travel over lora mesh and generate on his own hardware for free bookmark this and read the article below
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THIS SOLAR-POWERED MESH NODE PACKS A LOCAL LLM AND A 6-WATT PANEL, KILLED $200 CLAUDE CODE MAX AND $200 CHATGPT PRO SUBSCRIPTIONS THE DAY IT WENT LIVE AND RUNS AT $0/MO EVEN UNDER CLOUD COVER 00:22 he taps the case with the red led blinking, "even though we have complete cloud cover today, the sun's not even out and we're still getting a charge, that's absolutely phenomenal" the node runs a rak 4630 lora board with a 6-watt solar panel, a small battery bank inside the ip67 case, and a raspberry pi zero 2w wedged next to it running a quantized 3b model on ollama from the rooftop it services 71 other meshtastic nodes across the neighborhood offline, and the same box also handles ai queries piped in over the mesh from his phone without touching the internet claude code points at the pi over tailscale, the cli behaves identically to the cloud version except every token generates on his own rooftop under the panel that keeps charging through cloud cover $200 chatgpt pro and $200 claude code max used to hit his card monthly, and the whole stack died the day the rooftop went live because ai queries now travel over lora mesh and generate on his own hardware for free bookmark this and read the article below

starmex

50,557 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
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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 • 2 个月前

AS SOMEONE WHO TESTED THIS $30 SOLAR MESHTASTIC RIG FROM HIS ROOFTOP ACROSS 71 NEIGHBORING NODES, IT KILLED HIS $200 CHATGPT PRO AND $200 CLAUDE CODE MAX three months ago he bolted a rak 4630 lora board with a 6-watt solar panel to a rooftop mount, whole rig cost him $30 in used marketplace parts solar charges under complete cloud cover -> pi zero 2w runs quantized qwen 2.5 7b on ollama -> mesh services 71 neighboring nodes -> phone tunnels ai prompts through the mesh -> answers land locally with zero cell tower the panel keeps the battery full even through a full day of cloud cover, mesh handshakes with 71 neighboring nodes automatically, every prompt over the rf link answers back in under 3 seconds without cellular $200 claude code max and $200 chatgpt pro cancelled the day the solar started charging in cloud cover, a $30 rooftop rig handles what those subs charged $400 for bookmark this and read the article below
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AS SOMEONE WHO TESTED THIS $30 SOLAR MESHTASTIC RIG FROM HIS ROOFTOP ACROSS 71 NEIGHBORING NODES, IT KILLED HIS $200 CHATGPT PRO AND $200 CLAUDE CODE MAX three months ago he bolted a rak 4630 lora board with a 6-watt solar panel to a rooftop mount, whole rig cost him $30 in used marketplace parts solar charges under complete cloud cover -> pi zero 2w runs quantized qwen 2.5 7b on ollama -> mesh services 71 neighboring nodes -> phone tunnels ai prompts through the mesh -> answers land locally with zero cell tower the panel keeps the battery full even through a full day of cloud cover, mesh handshakes with 71 neighboring nodes automatically, every prompt over the rf link answers back in under 3 seconds without cellular $200 claude code max and $200 chatgpt pro cancelled the day the solar started charging in cloud cover, a $30 rooftop rig handles what those subs charged $400 for bookmark this and read the article below

starmex

50,759 次观看 • 1 个月前

THIS 1-WATT RASPBERRY PI ON A MOUNTAIN TOP PIPES AI QUERIES OVER A PRIVATE MESH TO A LOCAL LLM AT HOME, KILLED $200 CHATGPT PRO AND $200 CLAUDE CODE MAX SUBSCRIPTIONS THE DAY IT WENT LIVE 01:25 he picks up the handheld and says, "this node is tough as nails and the battery life is around 10 days" the mountain pi sits a few kilometers from his apartment with a 915 mhz antenna tuned for long range, meshtastic firmware handles the packet routing between nodes on the mesh wireguard stitches the mountain pi to his home rig running qwen 3.6 27b on a used rtx 3090, ai prompts travel over the private mesh and answers come back the same way without ever touching the public internet the ollama stack handles his coding, writing and research from any point on the network, no cloud api reads his prompts and no rate limit hits on a friday launch because nothing runs on someone else's servers $200 chatgpt pro and $200 claude code max used to cover the queries he now sends over his own antennas, the whole subscription stack died the day the pi went live because the local rig handles what those apis used to charge for bookmark this and read the article below
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THIS 1-WATT RASPBERRY PI ON A MOUNTAIN TOP PIPES AI QUERIES OVER A PRIVATE MESH TO A LOCAL LLM AT HOME, KILLED $200 CHATGPT PRO AND $200 CLAUDE CODE MAX SUBSCRIPTIONS THE DAY IT WENT LIVE 01:25 he picks up the handheld and says, "this node is tough as nails and the battery life is around 10 days" the mountain pi sits a few kilometers from his apartment with a 915 mhz antenna tuned for long range, meshtastic firmware handles the packet routing between nodes on the mesh wireguard stitches the mountain pi to his home rig running qwen 3.6 27b on a used rtx 3090, ai prompts travel over the private mesh and answers come back the same way without ever touching the public internet the ollama stack handles his coding, writing and research from any point on the network, no cloud api reads his prompts and no rate limit hits on a friday launch because nothing runs on someone else's servers $200 chatgpt pro and $200 claude code max used to cover the queries he now sends over his own antennas, the whole subscription stack died the day the pi went live because the local rig handles what those apis used to charge for bookmark this and read the article below

starmex

38,742 次观看 • 2 个月前

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40,403 次观看 • 2 个月前

ONE BUILDER WIRED 4 RASPBERRY PI MODULES INTO A €450 AI CLUSTER WITH 64GB OF RAM AND KILLED HIS $200/MONTH CHATGPT SUBSCRIPTION 00:37 he points at the terminal, "loaded, loaded, loaded - 4 nodes synced over gigabit, 64 gigabytes total, llama 3.1 partitioned across the cluster" he stacked 4 raspberry pi CM5 lite modules with 16 gigabytes each onto a sipeed nanocluster board, the whole rig runs off a single 65 watt power supply and a gigabit internal switch distributed llama partitions the model across the nodes with synchronized workloads handled over the internal fabric, no quantization needed, the cluster hits about 30 tokens per second on small models a heavy developer pays $200 a month for chatgpt pro and another $200 for claude code, this rig cost €450 in parts and breaks even on the stack in month 2 most people will keep paying anthropic and openai forever, a few will spend a weekend wiring 4 raspberry pi modules and never see a subscription invoice again the window is open, follow and bookmark before it closes
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ONE BUILDER WIRED 4 RASPBERRY PI MODULES INTO A €450 AI CLUSTER WITH 64GB OF RAM AND KILLED HIS $200/MONTH CHATGPT SUBSCRIPTION 00:37 he points at the terminal, "loaded, loaded, loaded - 4 nodes synced over gigabit, 64 gigabytes total, llama 3.1 partitioned across the cluster" he stacked 4 raspberry pi CM5 lite modules with 16 gigabytes each onto a sipeed nanocluster board, the whole rig runs off a single 65 watt power supply and a gigabit internal switch distributed llama partitions the model across the nodes with synchronized workloads handled over the internal fabric, no quantization needed, the cluster hits about 30 tokens per second on small models a heavy developer pays $200 a month for chatgpt pro and another $200 for claude code, this rig cost €450 in parts and breaks even on the stack in month 2 most people will keep paying anthropic and openai forever, a few will spend a weekend wiring 4 raspberry pi modules and never see a subscription invoice again the window is open, follow and bookmark before it closes

Antid

64,291 次观看 • 2 个月前

STARLINK CHARGES $120/MO TO GET ONLINE OFF-GRID. HE DOES IT FOR $0 - A $30 PANEL ANTENNA ON A MAST REACHING A USED GPU 80KM OUT. RUNS OPUS-5 AND GPT-5.6 LOCALLY he clamped a directional panel and a tp-link adapter to a telescoping mast and ran it up past the roofline, whole rig cost him $30 in used marketplace parts the higher it goes the farther it hears -> it locks a node 80km out -> the prompt tunnels down to the used gpu in his closet -> a local kimi k3 answers before the page finishes loading one node it kept pulling in stayed online through last month's grid blackout, turned out to be a repeater on a water tower a county away running off a small solar pack height is the whole cheat, lift a directional antenna over the treeline and line-of-sight does the rest, every node it reaches is just another road home to his own gpu $200 opus-5 and $200 gpt-5.6 pro stopped hitting his card the week that mast went up, a $30 antenna and a used gpu do what anthropic and openai charged $400 a month for full breakdown of the 5-device stack that zeroes your ai bill in the article below
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STARLINK CHARGES $120/MO TO GET ONLINE OFF-GRID. HE DOES IT FOR $0 - A $30 PANEL ANTENNA ON A MAST REACHING A USED GPU 80KM OUT. RUNS OPUS-5 AND GPT-5.6 LOCALLY he clamped a directional panel and a tp-link adapter to a telescoping mast and ran it up past the roofline, whole rig cost him $30 in used marketplace parts the higher it goes the farther it hears -> it locks a node 80km out -> the prompt tunnels down to the used gpu in his closet -> a local kimi k3 answers before the page finishes loading one node it kept pulling in stayed online through last month's grid blackout, turned out to be a repeater on a water tower a county away running off a small solar pack height is the whole cheat, lift a directional antenna over the treeline and line-of-sight does the rest, every node it reaches is just another road home to his own gpu $200 opus-5 and $200 gpt-5.6 pro stopped hitting his card the week that mast went up, a $30 antenna and a used gpu do what anthropic and openai charged $400 a month for full breakdown of the 5-device stack that zeroes your ai bill in the article below

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144,506 次观看 • 1 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
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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 次观看 • 3 个月前

7-YEAR-OLD RASPBERRY PI WITH 2GB OF RAM IS RUNNING DEEPSEEK RIGHT NOW WHILE SAM ALTMAN BILLS $200/MO AND DARIO AMODEI BILLS $200/MO FOR A MODEL YOU NEVER GET TO KEEP 00:34 he points at the smallest board on the bench and says "out of all these I'm genuinely shocked that I actually got it up and running on this raspberry pi 4b with 2 gigs of ram" raspberry pi 4b, 2gb, seven years old -> ollama with deepseek r1 1.5b -> a dell micro form factor doing cpu-only inference next to it -> an m1 max macbook with 64gb unified memory beating the dual gpu tower on large models -> four machines, four architectures, all serving locally apple's unified memory puts the ram on the same die as the cpu and gpu, so a laptop outruns a two-card workstation on big models, and the cheapest board on that bench costs less than four days of a claude max seat the honest part: 2gb is the actual floor and he says it was rough to get there, a 4gb or 8gb pi would have taken minutes instead, and 1.5b parameters is a model you use for structure not for answers raspberry pi 4b 2gb + dell micro form factor + m1 max 64gb + dual gpu tower + ollama + deepseek r1 watch and save it, musk gave away the agent and moonshot gave away the weights, the full $400 to $25 routing table is in the article below
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7-YEAR-OLD RASPBERRY PI WITH 2GB OF RAM IS RUNNING DEEPSEEK RIGHT NOW WHILE SAM ALTMAN BILLS $200/MO AND DARIO AMODEI BILLS $200/MO FOR A MODEL YOU NEVER GET TO KEEP 00:34 he points at the smallest board on the bench and says "out of all these I'm genuinely shocked that I actually got it up and running on this raspberry pi 4b with 2 gigs of ram" raspberry pi 4b, 2gb, seven years old -> ollama with deepseek r1 1.5b -> a dell micro form factor doing cpu-only inference next to it -> an m1 max macbook with 64gb unified memory beating the dual gpu tower on large models -> four machines, four architectures, all serving locally apple's unified memory puts the ram on the same die as the cpu and gpu, so a laptop outruns a two-card workstation on big models, and the cheapest board on that bench costs less than four days of a claude max seat the honest part: 2gb is the actual floor and he says it was rough to get there, a 4gb or 8gb pi would have taken minutes instead, and 1.5b parameters is a model you use for structure not for answers raspberry pi 4b 2gb + dell micro form factor + m1 max 64gb + dual gpu tower + ollama + deepseek r1 watch and save it, musk gave away the agent and moonshot gave away the weights, the full $400 to $25 routing table is in the article below

Antid

10,442 次观看 • 11 天前

THIS FRENCH GUY RUNS OPENCLAW AND HERMES AI AGENTS ON A HOMELAB THAT REPLACED GOOGLE DRIVE AND ICLOUD ENTIRELY ON JUST 10 WATTS The project: host his own local AI agents, OpenClaw and Hermes, ditch cloud storage subscriptions entirely by running his own NAS, and use the whole build to prep for his K8s certification – all running on 4 Raspberry Pis. Today's upgrade: a PoE module. One Ethernet cable now does two jobs – powers the Raspberry Pi AND gives it network access at the same time. No separate power adapters, no cable clutter, no juggling connections during maintenance. Total power draw for all 4 Raspberry Pis combined: max 10 watts. He's not renting cloud storage anymore. He's not paying monthly subscriptions for space he already owns the hardware for. His files, his AI agents, his data – all sitting on hardware in his own home, on a fraction of the power a lightbulb uses. Next up: blocking ads network-wide across his entire home, using one of the automation services running on the same setup. This is what "own your data" actually looks like when someone builds it instead of just talking about it. Bookmark this post. Full build in the video below.
0:45

THIS FRENCH GUY RUNS OPENCLAW AND HERMES AI AGENTS ON A HOMELAB THAT REPLACED GOOGLE DRIVE AND ICLOUD ENTIRELY ON JUST 10 WATTS The project: host his own local AI agents, OpenClaw and Hermes, ditch cloud storage subscriptions entirely by running his own NAS, and use the whole build to prep for his K8s certification – all running on 4 Raspberry Pis. Today's upgrade: a PoE module. One Ethernet cable now does two jobs – powers the Raspberry Pi AND gives it network access at the same time. No separate power adapters, no cable clutter, no juggling connections during maintenance. Total power draw for all 4 Raspberry Pis combined: max 10 watts. He's not renting cloud storage anymore. He's not paying monthly subscriptions for space he already owns the hardware for. His files, his AI agents, his data – all sitting on hardware in his own home, on a fraction of the power a lightbulb uses. Next up: blocking ads network-wide across his entire home, using one of the automation services running on the same setup. This is what "own your data" actually looks like when someone builds it instead of just talking about it. Bookmark this post. Full build in the video below.

SCOTTY BEAM

18,175 次观看 • 2 个月前

HAO WANG BUILT AN AI SERVER FARM OUT OF 100 MAC MINIS. ONE $599 BOX KILLS A $200/MONTH CLAUDE CODE BILL FOR $3 IN ELECTRICITY a developer posted his $170 claude code bill from 10 days on reddit. someone replied "i bought a mac mini m4. haven't paid anthropic since" the m4 chip has 120 gb/s memory bandwidth and unified memory. a $599 mac mini runs ai faster than a $1,500 windows pc with a discrete gpu ollama now supports the anthropic messages api. claude code connects to your local mac mini with one environment variable. zero api costs, same interface a heavy developer pays $459 a month across claude code, chatgpt pro, gemini, cursor and copilot. the mac mini pays off in 3 months and runs on $3 after that uber rolled out claude code to 5,000 engineers and burned $3.4 billion in 4 months. the people who own the hardware in 2026 will look very far ahead in 2028 bookmark this and read the article below
0:20

HAO WANG BUILT AN AI SERVER FARM OUT OF 100 MAC MINIS. ONE $599 BOX KILLS A $200/MONTH CLAUDE CODE BILL FOR $3 IN ELECTRICITY a developer posted his $170 claude code bill from 10 days on reddit. someone replied "i bought a mac mini m4. haven't paid anthropic since" the m4 chip has 120 gb/s memory bandwidth and unified memory. a $599 mac mini runs ai faster than a $1,500 windows pc with a discrete gpu ollama now supports the anthropic messages api. claude code connects to your local mac mini with one environment variable. zero api costs, same interface a heavy developer pays $459 a month across claude code, chatgpt pro, gemini, cursor and copilot. the mac mini pays off in 3 months and runs on $3 after that uber rolled out claude code to 5,000 engineers and burned $3.4 billion in 4 months. the people who own the hardware in 2026 will look very far ahead in 2028 bookmark this and read the article below

starmex

50,756 次观看 • 3 个月前

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 • 3 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

86,831 次观看 • 2 个月前

THIS TOKYO PROGRAMMER MADE $8,500 IN HIS FIRST MONTH WITH A MAC MINI — AND SAYS IT'S THE ONLY MACHINE YOU NEED FOR AI Claude Code, Codex, any AI tool - all of it runs on a Mac Mini with zero issues and zero monthly cloud bills at the 0:11 second mark he turns the monitor around - Claude Code with Opus 4.7 running in full context, terminal active and the agent already working - one programmer, one room in Tokyo, one $599 Mac Mini used to pay $200+ a month on subscriptions and cloud GPU - now pays $3 in electricity and everything else stays in his business $599 invested once - and in the first year he saved $2,364 that used to go to someone else's data center his advice is simple: if you're serious about AI - the Mac Mini is the first thing you should buy
0:25

THIS TOKYO PROGRAMMER MADE $8,500 IN HIS FIRST MONTH WITH A MAC MINI — AND SAYS IT'S THE ONLY MACHINE YOU NEED FOR AI Claude Code, Codex, any AI tool - all of it runs on a Mac Mini with zero issues and zero monthly cloud bills at the 0:11 second mark he turns the monitor around - Claude Code with Opus 4.7 running in full context, terminal active and the agent already working - one programmer, one room in Tokyo, one $599 Mac Mini used to pay $200+ a month on subscriptions and cloud GPU - now pays $3 in electricity and everything else stays in his business $599 invested once - and in the first year he saved $2,364 that used to go to someone else's data center his advice is simple: if you're serious about AI - the Mac Mini is the first thing you should buy

Sprytix

14,771 次观看 • 3 个月前

As announced on Pi Day 2026, the initial version of the Token Launchpad has been released as a Pi App on the Testnet with a test token! Watch the video walkthrough to learn the implemented design in action, and read the blog—originally published in the Pi Day announcement—to understand its deeper meaning. Pi believes financial literacy is necessary for people to live in an AI-pervasive economy, so Pioneers should start learning today by testing the Testnet Launchpad app through the Pi Browser.
4:15

As announced on Pi Day 2026, the initial version of the Token Launchpad has been released as a Pi App on the Testnet with a test token! Watch the video walkthrough to learn the implemented design in action, and read the blog—originally published in the Pi Day announcement—to understand its deeper meaning. Pi believes financial literacy is necessary for people to live in an AI-pervasive economy, so Pioneers should start learning today by testing the Testnet Launchpad app through the Pi Browser.

Pi Network

308,718 次观看 • 5 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

981,107 次观看 • 3 个月前

This guy replaced an $8,000 survey crew with one drone and a pipeline on Claude Code that digitizes a whole site in a single trip. Inside it is not one drone but a whole pipeline of 5 modules on Claude Code each with its own job all answering to a single orchestrator. And he built them himself with no team. He draws one line on the map from the controller and the whole site starts turning into data at once. Pilot flies the DJI Matrice 350 RTK along the route and reaches where a crew drags tripods: the parking lot and the roofs and the grading. Scanner on the Zenmuse L2 records the geometry with a laser down to the centimeter. Builder in DJI Terra stitches the point cloud into a digital twin. Analyst on Claude builds what the client needs out of the finished model: a volume report and a progress diff and a tour behind a link. Mobile lives in his iPhone and hands the developer a link to the model while he drives to the next site. The site is ready as a file in about an hour and the developer rotates it in the browser himself and measures distances. No crew. No tripods. No week on site. Just him and a pickup and a drone and one API key. The whole processing pipeline lives in a folder at /Users/dev/site-capture. But he did not stop at a one time scan. The pipeline raises him by voice only when a flight misses a patch or when a sag on site goes past tolerance. And this is not made up: the DJI Matrice 350 RTK and the Zenmuse L2 are off the shelf enterprise hardware. The specs are one search away and the L2 really does write around 240,000 points per second. A crew for the same job charges $8,000 and three trips plus a week of desk work. His cost is tokens and subscriptions: one battery charge per flight and around $300 a month to host the finished models. In the end he draws one line on the map and an operator that does not exist scans the site and calculates the volumes and builds the report while he never leaves his truck. There is a huge market of everyone who needs to measure construction sites and warehouses and roofs and parking lots over and over while they still send out a photographer with a camera and wait a week. And he built this whole pipeline himself: one drone and one scanner and Claude Code that turns a flight into a file the developer pays for.
0:41

This guy replaced an $8,000 survey crew with one drone and a pipeline on Claude Code that digitizes a whole site in a single trip. Inside it is not one drone but a whole pipeline of 5 modules on Claude Code each with its own job all answering to a single orchestrator. And he built them himself with no team. He draws one line on the map from the controller and the whole site starts turning into data at once. Pilot flies the DJI Matrice 350 RTK along the route and reaches where a crew drags tripods: the parking lot and the roofs and the grading. Scanner on the Zenmuse L2 records the geometry with a laser down to the centimeter. Builder in DJI Terra stitches the point cloud into a digital twin. Analyst on Claude builds what the client needs out of the finished model: a volume report and a progress diff and a tour behind a link. Mobile lives in his iPhone and hands the developer a link to the model while he drives to the next site. The site is ready as a file in about an hour and the developer rotates it in the browser himself and measures distances. No crew. No tripods. No week on site. Just him and a pickup and a drone and one API key. The whole processing pipeline lives in a folder at /Users/dev/site-capture. But he did not stop at a one time scan. The pipeline raises him by voice only when a flight misses a patch or when a sag on site goes past tolerance. And this is not made up: the DJI Matrice 350 RTK and the Zenmuse L2 are off the shelf enterprise hardware. The specs are one search away and the L2 really does write around 240,000 points per second. A crew for the same job charges $8,000 and three trips plus a week of desk work. His cost is tokens and subscriptions: one battery charge per flight and around $300 a month to host the finished models. In the end he draws one line on the map and an operator that does not exist scans the site and calculates the volumes and builds the report while he never leaves his truck. There is a huge market of everyone who needs to measure construction sites and warehouses and roofs and parking lots over and over while they still send out a photographer with a camera and wait a week. And he built this whole pipeline himself: one drone and one scanner and Claude Code that turns a flight into a file the developer pays for.

Blaze

10,744 次观看 • 2 个月前

Someone ran Claude Code on a beach where any device overheats and that spot suddenly turned out to be the best home for the most powerful AI in the world. This is the reMarkable Paper Pro. A paper tablet for notes with no browser and no social media and not a single app. He sat down right on the sand in the open sun and brought up Claude Code on Opus 4.6 over the Claude API on the paper screen and opened his project ~/repos/webs while the waves broke a few steps away. For years every device had the same trouble outside. In direct sun the screen glares and washes out and heats up and instead of your work you see your own reflection. But e-ink does not blast its own light into your face. It reflects the sunlight like the page of a book. And here is what came out of it. The very thing that kills any normal screen outside turned into fuel for this one. The brighter the sun the sharper the picture because it has nothing to glare with and nothing to wash out. And then comes the thing no laptop on a beach will give you. Your eyes do not get tired. You can watch Opus think on max effort for an hour and it reads like a book in the sun and not a backlight you squint into. The picture only comes alive. In bright light it does not fade but turns sharper and higher in contrast than it ever was in a room. The charge lasts for days. E-ink barely touches the battery so there is no outlet anywhere on the sand and the tablet does not care. It weighs as much as a notebook. The whole setup folds into a beach bag like a pad with a pen on top. Everything on the screen is for real. Claude Code v2.1.110 and Opus 4.6 on the Claude API and the project ~/repos/webs open right on the e-ink in the middle of the sand. In my opinion this is the most unexpected home for an AI this year. Not an office with the blinds drawn and not a monitor cranked to full brightness but a quiet sheet of paper on the sand that open sun only makes better and on it the most powerful Claude writes code right on the page like a pen.
0:33

Someone ran Claude Code on a beach where any device overheats and that spot suddenly turned out to be the best home for the most powerful AI in the world. This is the reMarkable Paper Pro. A paper tablet for notes with no browser and no social media and not a single app. He sat down right on the sand in the open sun and brought up Claude Code on Opus 4.6 over the Claude API on the paper screen and opened his project ~/repos/webs while the waves broke a few steps away. For years every device had the same trouble outside. In direct sun the screen glares and washes out and heats up and instead of your work you see your own reflection. But e-ink does not blast its own light into your face. It reflects the sunlight like the page of a book. And here is what came out of it. The very thing that kills any normal screen outside turned into fuel for this one. The brighter the sun the sharper the picture because it has nothing to glare with and nothing to wash out. And then comes the thing no laptop on a beach will give you. Your eyes do not get tired. You can watch Opus think on max effort for an hour and it reads like a book in the sun and not a backlight you squint into. The picture only comes alive. In bright light it does not fade but turns sharper and higher in contrast than it ever was in a room. The charge lasts for days. E-ink barely touches the battery so there is no outlet anywhere on the sand and the tablet does not care. It weighs as much as a notebook. The whole setup folds into a beach bag like a pad with a pen on top. Everything on the screen is for real. Claude Code v2.1.110 and Opus 4.6 on the Claude API and the project ~/repos/webs open right on the e-ink in the middle of the sand. In my opinion this is the most unexpected home for an AI this year. Not an office with the blinds drawn and not a monitor cranked to full brightness but a quiet sheet of paper on the sand that open sun only makes better and on it the most powerful Claude writes code right on the page like a pen.

Blaze

89,575 次观看 • 2 个月前

CLAUDE TOOK A FULL PC GAME, REBUILT IT FROM THE GROUND UP, AND GOT IT RUNNING NATIVELY ON ANDROID IN 6 HOURS a guy pointed claude at slay the spire 2, a game he owns on steam, and it ported the whole thing to his phone almost completely on its own here's what claude did: > it pulled apart the game and recompiled it to native arm, no emulator, wine, or proton used > wrote the code, ran the build loop, and debugged it directly on the device itself > added full touch controls that feel like a real mobile game, not awkward on screen buttons > and he even built a tool on top to sync save files between his desktop and phone a couple prompts and 6 hours. it handled the extraction, the cross compile, the building and the on device debugging by itself. fully playable, not a single crash yet
0:39

CLAUDE TOOK A FULL PC GAME, REBUILT IT FROM THE GROUND UP, AND GOT IT RUNNING NATIVELY ON ANDROID IN 6 HOURS a guy pointed claude at slay the spire 2, a game he owns on steam, and it ported the whole thing to his phone almost completely on its own here's what claude did: > it pulled apart the game and recompiled it to native arm, no emulator, wine, or proton used > wrote the code, ran the build loop, and debugged it directly on the device itself > added full touch controls that feel like a real mobile game, not awkward on screen buttons > and he even built a tool on top to sync save files between his desktop and phone a couple prompts and 6 hours. it handled the extraction, the cross compile, the building and the on device debugging by itself. fully playable, not a single crash yet

Om Patel

28,504 次观看 • 2 个月前

Noah Brier (Noah Brier) uses Claude Code as his second brain—it’s the coolest notetaking setup I’ve ever seen. He has Claude running on a server in his basement hooked up to a VPN. It stores, reads, and writes to thousands of notes in his Obsidian (Obsidian) vault. He does it all from his phone. I had him on the show to tell us exactly how he’s pulling this off. We get into: - The nuts and bolts of the Claude Code-Obsidian setup: Noah set up Claude Code on top of his Obsidian root directory, and he walked me through how he uses it to prep for an upcoming speech—creating a project folder, pulling in relevant research from his notes, saving transcripts from chats with other LLMs, and generating daily progress updates. - The “thinking partner” that lives inside Noah’s second brain: Noah points out that in the hype around AI’s ability to write, the fact that it can read is overlooked. That’s why he has an agent inside Claude Code with strict guardrails to stay in “thinking mode.” It logs his questions, tracks insights, and catches him up on research if he returns to a project after a few days away. - How Noah does deep work on his phone: Noah rigged a home server in his basement, put his Obsidian vault in it—and then runs Claude Code on top. Noah says that being able to think, write, research, and ship code from his phone has fundamentally changed the way he works. This episode of Every 📧’s AI & I is a must-watch for anyone curious about who wants to learn how to use Claude Code to build a true second brain. Watch below! Timestamps: Introduction: 00:01:19 How you can do deep work on your phone: 00:04:28 Why Noah thinks Grok has the best voice AI: 00:06:14 The nuts and bolts of Noah’s Claude Code-Obsidian setup: 00:11:39 Using an agent in Claude Code as a “thinking partner”: 00:23:59 Noah’s Thomas’ English Muffin theory of AI: 00:35:07 The white space still left to explore in AI: 00:44:04 How Noah is preparing his kids for AI: 00:50:41 How he brought his Claude Code setup to mobile: 01:01:54
1:11:52

Noah Brier (Noah Brier) uses Claude Code as his second brain—it’s the coolest notetaking setup I’ve ever seen. He has Claude running on a server in his basement hooked up to a VPN. It stores, reads, and writes to thousands of notes in his Obsidian (Obsidian) vault. He does it all from his phone. I had him on the show to tell us exactly how he’s pulling this off. We get into: - The nuts and bolts of the Claude Code-Obsidian setup: Noah set up Claude Code on top of his Obsidian root directory, and he walked me through how he uses it to prep for an upcoming speech—creating a project folder, pulling in relevant research from his notes, saving transcripts from chats with other LLMs, and generating daily progress updates. - The “thinking partner” that lives inside Noah’s second brain: Noah points out that in the hype around AI’s ability to write, the fact that it can read is overlooked. That’s why he has an agent inside Claude Code with strict guardrails to stay in “thinking mode.” It logs his questions, tracks insights, and catches him up on research if he returns to a project after a few days away. - How Noah does deep work on his phone: Noah rigged a home server in his basement, put his Obsidian vault in it—and then runs Claude Code on top. Noah says that being able to think, write, research, and ship code from his phone has fundamentally changed the way he works. This episode of Every 📧’s AI & I is a must-watch for anyone curious about who wants to learn how to use Claude Code to build a true second brain. Watch below! Timestamps: Introduction: 00:01:19 How you can do deep work on your phone: 00:04:28 Why Noah thinks Grok has the best voice AI: 00:06:14 The nuts and bolts of Noah’s Claude Code-Obsidian setup: 00:11:39 Using an agent in Claude Code as a “thinking partner”: 00:23:59 Noah’s Thomas’ English Muffin theory of AI: 00:35:07 The white space still left to explore in AI: 00:44:04 How Noah is preparing his kids for AI: 00:50:41 How he brought his Claude Code setup to mobile: 01:01:54

Dan Shipper 📧

30,792 次观看 • 1 年前