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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...

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63,946 views • 20 days ago •via X (Twitter)

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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
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 views • 7 days ago

Yeah. I have ChatGPT at home. Not a silly 7b model. A full-on 65B model that runs on my pi cluster, watch how the model gets loaded across the cluster with mmap and does round-robin inferencing 🫡 (10 seconds/token) (sped up 16x)
1:34

Yeah. I have ChatGPT at home. Not a silly 7b model. A full-on 65B model that runs on my pi cluster, watch how the model gets loaded across the cluster with mmap and does round-robin inferencing 🫡 (10 seconds/token) (sped up 16x)

Loki (cute/acc)

452,150 views • 3 years ago

FOUR DIFFERENT VENDORS ARE NOW SHIPPING GB10 MINI PCs WITH 128GB UNIFIED MEMORY, AND ONE MICROTIK CRS 804 SWITCH CAN CONNECT UP TO EIGHT OF THEM INTO A 1 TERABYTE LOCAL AI CLUSTER 00:00 he points at the MikroTik CRS 804, "you need some kind of switch that'll handle QSFP56 ports like these", the interconnect that makes the whole cluster possible the GB10 ecosystem is no longer just Nvidia. Dell Pro Max GB10, ASUS Ascent GX10, and MSI Edge Expert all ship the same Grace Blackwell Superchip with 128GB of coherent memory. same silicon, different cases, same 200 gigabit ports on the back the CRS 804 is what connects them at prosumer prices. four 400 gigabit QSFP56 ports on one 1U chassis, breakout cables that split each port into two 200 gigabit lanes. one switch drives eight GB10 units in parallel do the math. eight nodes at 128GB each equals 1024GB of pooled unified memory across the cluster. run vLLM, shard a frontier model across all eight, and inference happens locally on hardware that fits in half a rack the real limiter revealed in the stress test was never throttling. it was interconnect topology, exactly the layer this switch fixes at a fraction of enterprise switch pricing $400 a month for combined chatgpt pro and claude code max hits $4,800 a year per developer. a small team of five running through this cluster pays back inside eight months and never expires the article covers the buying ladder for a single desk. this post is proof of the cluster ladder that starts where the desk one ends save this before the GB10 lineup grows past four vendors and prosumer cluster switches move upmarket
1:05

FOUR DIFFERENT VENDORS ARE NOW SHIPPING GB10 MINI PCs WITH 128GB UNIFIED MEMORY, AND ONE MICROTIK CRS 804 SWITCH CAN CONNECT UP TO EIGHT OF THEM INTO A 1 TERABYTE LOCAL AI CLUSTER 00:00 he points at the MikroTik CRS 804, "you need some kind of switch that'll handle QSFP56 ports like these", the interconnect that makes the whole cluster possible the GB10 ecosystem is no longer just Nvidia. Dell Pro Max GB10, ASUS Ascent GX10, and MSI Edge Expert all ship the same Grace Blackwell Superchip with 128GB of coherent memory. same silicon, different cases, same 200 gigabit ports on the back the CRS 804 is what connects them at prosumer prices. four 400 gigabit QSFP56 ports on one 1U chassis, breakout cables that split each port into two 200 gigabit lanes. one switch drives eight GB10 units in parallel do the math. eight nodes at 128GB each equals 1024GB of pooled unified memory across the cluster. run vLLM, shard a frontier model across all eight, and inference happens locally on hardware that fits in half a rack the real limiter revealed in the stress test was never throttling. it was interconnect topology, exactly the layer this switch fixes at a fraction of enterprise switch pricing $400 a month for combined chatgpt pro and claude code max hits $4,800 a year per developer. a small team of five running through this cluster pays back inside eight months and never expires the article covers the buying ladder for a single desk. this post is proof of the cluster ladder that starts where the desk one ends save this before the GB10 lineup grows past four vendors and prosumer cluster switches move upmarket

NO1ennn

41,220 views • 3 days ago

THEY RAN A LOCAL AI MODEL ON A RASPBERRY PI THAT COSTS LESS THAN $300 no cloud no subscription no data center device smaller than your wallet output on a 27 year old iMac I tested local ai this week on a macbook and a phone the hardware keeps getting cheaper and the models keep getting smarter bookmark this if you’re still paying $20 a month for something your $300 raspberry pi can do
0:59

THEY RAN A LOCAL AI MODEL ON A RASPBERRY PI THAT COSTS LESS THAN $300 no cloud no subscription no data center device smaller than your wallet output on a 27 year old iMac I tested local ai this week on a macbook and a phone the hardware keeps getting cheaper and the models keep getting smarter bookmark this if you’re still paying $20 a month for something your $300 raspberry pi can do

leopardracer

73,534 views • 1 month ago

THIS DEVELOPER JUST RAN A TRILLION PARAMETER MODEL ON 4 MAC STUDIOS - 10X FASTER AND 5X CHEAPER THAN CLOUD CODE 19:00 he says it out loud. "we just ran a trillion parameter model. 30 something tokens per second. wow." RDMA over Thunderbolt made the cluster 10x faster than before. tensor parallelism splits the model between machines in parallel instead of sequentially DeepSeek V3 full size without quantization. 183GB per machine. still 25 tokens per second. faster than most people can read Kimi K2 with trillion parameters and 256,000 context window. loaded, responded and adapted memory usage dynamically based on prompt size 4 machines consuming 66 watts total. cloud GPU for the same workload costs $1,900/month a cluster that used to cost millions now assembled from Mac Studios in a few hours
22:35

THIS DEVELOPER JUST RAN A TRILLION PARAMETER MODEL ON 4 MAC STUDIOS - 10X FASTER AND 5X CHEAPER THAN CLOUD CODE 19:00 he says it out loud. "we just ran a trillion parameter model. 30 something tokens per second. wow." RDMA over Thunderbolt made the cluster 10x faster than before. tensor parallelism splits the model between machines in parallel instead of sequentially DeepSeek V3 full size without quantization. 183GB per machine. still 25 tokens per second. faster than most people can read Kimi K2 with trillion parameters and 256,000 context window. loaded, responded and adapted memory usage dynamically based on prompt size 4 machines consuming 66 watts total. cloud GPU for the same workload costs $1,900/month a cluster that used to cost millions now assembled from Mac Studios in a few hours

Noisy

79,437 views • 20 days ago

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 views • 1 month ago

STACKING 4 OLD NVIDIA GTX 1080s GIVES YOU LOCAL AI THAT BEATS $400/MO IN CLOUD SUBSCRIPTIONS people are pulling 4 used gtx 1080s off ebay for around $400 total and stacking them in one tower to build a local ai rig. that pools 32gb of vram across cards that originally retailed at $700 each old gaming cards became cheap when ethereum killed proof of work in 2022. miners dumped millions of them and developers picked them up to run open weight models locally ollama installs in one shell command and pulls a model in another. point claude code at localhost through one environment variable and the cli works identically without sending data to anthropic llama 3.2, mistral 7b, qwen 2.5 and phi 3 all run comfortably on a 1080 stack at 40 to 60 tokens per second. fast enough for real conversations, automation pipelines and document analysis a heavy ai user pays $200 chatgpt pro, $200 claude code and $20 cursor every month. that's $5,040 a year and a $400 rig pays itself off before month two bookmark this and read the article below
0:28

STACKING 4 OLD NVIDIA GTX 1080s GIVES YOU LOCAL AI THAT BEATS $400/MO IN CLOUD SUBSCRIPTIONS people are pulling 4 used gtx 1080s off ebay for around $400 total and stacking them in one tower to build a local ai rig. that pools 32gb of vram across cards that originally retailed at $700 each old gaming cards became cheap when ethereum killed proof of work in 2022. miners dumped millions of them and developers picked them up to run open weight models locally ollama installs in one shell command and pulls a model in another. point claude code at localhost through one environment variable and the cli works identically without sending data to anthropic llama 3.2, mistral 7b, qwen 2.5 and phi 3 all run comfortably on a 1080 stack at 40 to 60 tokens per second. fast enough for real conversations, automation pipelines and document analysis a heavy ai user pays $200 chatgpt pro, $200 claude code and $20 cursor every month. that's $5,040 a year and a $400 rig pays itself off before month two bookmark this and read the article below

starmex

369,317 views • 20 days ago

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

93,086 views • 25 days ago

Most heavy AI users pay $400-500/month in subscriptions. $200 ChatGPT, $200 Claude Code, $20 Cursor, $5,000 a year. He put a small box on his desk, two commands, free model running locally. Same chat, same answers, nothing leaves the room. Paid itself off in 4 months, now costs $3 in electricity. Most people look at this and see a workstation. one group looks at it and stops paying.
1:28

Most heavy AI users pay $400-500/month in subscriptions. $200 ChatGPT, $200 Claude Code, $20 Cursor, $5,000 a year. He put a small box on his desk, two commands, free model running locally. Same chat, same answers, nothing leaves the room. Paid itself off in 4 months, now costs $3 in electricity. Most people look at this and see a workstation. one group looks at it and stops paying.

ToraX

24,451 views • 17 days ago

JENSEN HUANG SOLD A $249 AI COMPUTER ON STAGE THAT KILLS YOUR $200/MONTH OPENAI BILL. THE VIDEO HAS 217,000 LIKES the box is called the jetson orin nano super. 70 trillion ai operations per second, 25 watts, smaller than a wallet. it runs llama 3, mistral, gemma and deepseek locally with no api fees and no data leaving your house a developer running automations and coding assistants pays $200 a month to openai. the same workload on this box costs $2 a month in electricity and breaks even on the hardware in 10 weeks you install ollama with one command. change one line in your code. point it at localhost instead of openai. everything else works identically 7 billion parameter models handle 80% of what people use chatgpt for. summarization, drafting, coding, document q&a, automation pipelines. the hard 20% you keep claude or gpt for. total monthly cost drops from $200 to $22 cloud subscriptions keep getting more expensive and rate limits keep getting tighter. the people who set this up in 2025 are going to look very smart in 2027 bookmark this and read the article below
1:18

JENSEN HUANG SOLD A $249 AI COMPUTER ON STAGE THAT KILLS YOUR $200/MONTH OPENAI BILL. THE VIDEO HAS 217,000 LIKES the box is called the jetson orin nano super. 70 trillion ai operations per second, 25 watts, smaller than a wallet. it runs llama 3, mistral, gemma and deepseek locally with no api fees and no data leaving your house a developer running automations and coding assistants pays $200 a month to openai. the same workload on this box costs $2 a month in electricity and breaks even on the hardware in 10 weeks you install ollama with one command. change one line in your code. point it at localhost instead of openai. everything else works identically 7 billion parameter models handle 80% of what people use chatgpt for. summarization, drafting, coding, document q&a, automation pipelines. the hard 20% you keep claude or gpt for. total monthly cost drops from $200 to $22 cloud subscriptions keep getting more expensive and rate limits keep getting tighter. the people who set this up in 2025 are going to look very smart in 2027 bookmark this and read the article below

starmex

1,995,664 views • 1 month ago

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 views • 24 days ago

Raspberry Pi gets a comeback as the Star Trek communicator with OpenClaw! Raspberry Pi was popular in the 2010s and now faces a comeback as the personification of OpenClaw in a Tamagotchi shape - it listens, it thinks and it even talks! And it is not even that expensive! Sebastian Volkl created his Raspberry Pi project with just $100. Do you want your own OpenClaw Tamagotchi? #tamagotchi #openclaw #raspberrypi #ai #tech Sebastian Völkl
0:52

Raspberry Pi gets a comeback as the Star Trek communicator with OpenClaw! Raspberry Pi was popular in the 2010s and now faces a comeback as the personification of OpenClaw in a Tamagotchi shape - it listens, it thinks and it even talks! And it is not even that expensive! Sebastian Volkl created his Raspberry Pi project with just $100. Do you want your own OpenClaw Tamagotchi? #tamagotchi #openclaw #raspberrypi #ai #tech Sebastian Völkl

This Week in Startups

16,116 views • 4 months ago

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

50,610 views • 1 month ago

Do you actually understand what's happening. He built an AI box that costs less than one month of AI subscriptions. He built his for under $200. A Raspberry Pi 5 with a touchscreen and a power bank. He almost didn't bother. It looked too simple to matter. Then he ran two commands, connected six agents, and watched it start handling work he used to pay $250/month in subscriptions for. Month two cost: $3 in electricity. Now he shows people the setup and watches their faces. It still looks like a toy. It stopped being one around the time the first invoice came in.
0:54

Do you actually understand what's happening. He built an AI box that costs less than one month of AI subscriptions. He built his for under $200. A Raspberry Pi 5 with a touchscreen and a power bank. He almost didn't bother. It looked too simple to matter. Then he ran two commands, connected six agents, and watched it start handling work he used to pay $250/month in subscriptions for. Month two cost: $3 in electricity. Now he shows people the setup and watches their faces. It still looks like a toy. It stopped being one around the time the first invoice came in.

Superior

40,757 views • 14 days ago

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

977,177 views • 26 days ago

Raspberry Pi power meets industrial smarts with SECO Pi Vision 10.1 CM5. Pi Vision 10.1 CM5 is a rugged, ready-to-roll platform built around Raspberry Pi Compute Module 5. It’s tailor-made for IoT developers and system integrators. This isn’t just any old human–machine interface. It’s a Raspberry Pi gone pro.
1:27

Raspberry Pi power meets industrial smarts with SECO Pi Vision 10.1 CM5. Pi Vision 10.1 CM5 is a rugged, ready-to-roll platform built around Raspberry Pi Compute Module 5. It’s tailor-made for IoT developers and system integrators. This isn’t just any old human–machine interface. It’s a Raspberry Pi gone pro.

Raspberry Pi

16,610 views • 8 months ago

THIS DEVELOPER CONNECTED 8 NVIDIA DGX SPARKS INTO ONE CLUSTER - AND RAN AN 800GB MODEL THAT MADE HIM 10X MORE PRODUCTIVE 21:47 he says it straight - "this is a terabyte of VRAM - we ran Quen 3.5, 800GB on disk, a model that doesn't even fit on a single Mac Studio - 24 tokens per second - I'd say that's a win" 8 Sparks connected through a $1,300 switch via RDMA over Ethernet - each node adding 128GB of memory into one unified pool of 1TB started with one Spark at 3 tokens per second - every added node doubled the speed - and eight together deliver 24 tokens on a model that physically cannot run anywhere else Kimi K2 at 600GB loaded in 15 minutes, 115GB per node, 13 tokens per second - a model that simply cannot run on anything smaller Claude helped configure the entire cluster - SSH mesh across all 8 machines, network config, jumbo frames, QSFP port speeds - all from one terminal most people rent cloud compute for models this size at $2,000+/month - he built the cluster once and now every token costs 20x less
24:17

THIS DEVELOPER CONNECTED 8 NVIDIA DGX SPARKS INTO ONE CLUSTER - AND RAN AN 800GB MODEL THAT MADE HIM 10X MORE PRODUCTIVE 21:47 he says it straight - "this is a terabyte of VRAM - we ran Quen 3.5, 800GB on disk, a model that doesn't even fit on a single Mac Studio - 24 tokens per second - I'd say that's a win" 8 Sparks connected through a $1,300 switch via RDMA over Ethernet - each node adding 128GB of memory into one unified pool of 1TB started with one Spark at 3 tokens per second - every added node doubled the speed - and eight together deliver 24 tokens on a model that physically cannot run anywhere else Kimi K2 at 600GB loaded in 15 minutes, 115GB per node, 13 tokens per second - a model that simply cannot run on anything smaller Claude helped configure the entire cluster - SSH mesh across all 8 machines, network config, jumbo frames, QSFP port speeds - all from one terminal most people rent cloud compute for models this size at $2,000+/month - he built the cluster once and now every token costs 20x less

Noisy

184,316 views • 19 days ago

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

86,855 views • 1 month ago

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 views • 22 days ago

A brand new edition of The Official Raspberry Pi Beginner's Guide is OUT NOW! Updated for Raspberry Pi 500+ and OS Trixie:
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A brand new edition of The Official Raspberry Pi Beginner's Guide is OUT NOW! Updated for Raspberry Pi 500+ and OS Trixie:

Raspberry Pi

18,003 views • 5 months ago