HMCM

Hold my crypto milk

[HMCM @HMCMcrypto]

Nvidia just made the DGX Spark obsolete.

At least that's what the headline wants you to think.

Same chip. Same petaflop. Same 128GB of memory. Same 150mm cube.

Except now it lives inside the ASUS ProArt Mini PC. Running Windows. With gaming built in.

DGX Spark runs Linux and handles AI models up to 200 billion parameters. ProArt does the same - plus Adobe workflows, 12K editing, and AAA titles at 1440p, 100+ fps.

The one gap: networking. DGX Spark carries a 200Gb ConnectX-7 link for clustering. ProArt doesn't.
So no. DGX Spark isn't dead.

The AI supercomputer just got a little brother - built for people who want to work and play out of the same box.

[lagerskoy @lagerskoy]

https://t.co/TPU9kCbNtM

[HMCM @HMCMcrypto]

He was about to spend $4,000 on a DGX Spark.

Then he found a box that costs half that.

Same 128GB unified memory.

Same 70B-class local models.

One difference - the price.

NVIDIA DGX Spark vs AMD Strix Halo - who actually wins?

[KyzoroX @kyzoroX]

https://t.co/JGVBQ8PZzO

[HMCM @HMCMcrypto]

@kirillk_web3 I think Fable did a better job of conveying the idea

[HMCM @HMCMcrypto]

@higgsfield_ai In my opinion, KIMI is better

[HMCM @HMCMcrypto]

@0xKnzo Talk about an actual moat building real infrastructure in mineral oil beats theoretical whitepapers any day

[HMCM @HMCMcrypto]

@z0rynx So, how much power does my hair dryer consume, then?....

[HMCM @HMCMcrypto]

This guy built a room that pays him $4,700 a month.

Row after row of Mac Minis. No fan noise. No wasted watts.

While everyone else mines with GPUs - he's farming testnet drops.

Every Mac Mini is a node. Every node is a vote in a network that doesn't have a token yet.

Apple Silicon's performance-per-watt beats any gaming rig, hands down. Quiet, cool, built to run 24/7 across every testnet worth farming.

$4,700 a month. From a shelf of computers most people mistake for a router closet.

Nobody sees this room. But when the airdrop lands - everyone will.

#Macmini #node #testnets

[HMCM @HMCMcrypto]

https://t.co/Np4DMQdcWd

[HMCM @HMCMcrypto]

This Mac Mini farm in Hong Kong makes its young owner $28,000 a month.

No fields. No tractors. Just a room packed with racks of Mac Minis - dozens of small silver boxes wired into monitors running trading dashboards.

Each Mac Mini is its own worker. Each screen runs its own bot, trading 24/7 while the owner sleeps.

He's not sitting there clicking trades. The system do
es it for him.

Look out the window - dense Hong Kong high-rises, an ordinary apartment. But inside, there's a farm quietly printing money, no factory floor required.

$28,000. Every month. From a room you'd walk past without ever knowing what's inside.

[HMCM @HMCMcrypto]

https://t.co/Np4DMQdcWd

[HMCM @HMCMcrypto]

He didn't ask permission. He just built it.

No hype thread. No pitch deck. Just execution - and a camera rolling while it happened.

Twelve seconds. That's all it took to show what most people spend months explaining and still can't prove.

[HMCM @HMCMcrypto]

https://t.co/Np4DMQdcWd

[HMCM @HMCMcrypto]

THIS FARM RUNS ON NOTHING BUT MAC MINIS - AND IT PRINTS $450,000 IN PURE PROFIT EVERY SINGLE YEAR.

Let's break down what it actually costs to build this.

THE HARDWARE
Roughly 40 Mac minis on that rack. At current Apple pricing (2026), the M4 Mac mini starts at $799 - but for real AI workloads you need more RAM, pushing the realistic average to about $1,200 per unit once you configure for 24GB+ memory.

40 units × $1,200 = $48,000

Add racking, cabling, network switches, and a UPS for

power stability: +$4,000

Total hardware investment: ~$52,000

THE RUNNING COSTS
Each Mac mini under sustained AI inference load pulls around 40W - that's the whole point, Apple silicon is absurdly power-efficient compared to GPU rigs.

40 units × 40W = 1.6kW continuous draw
1.6kW × 24 hours × 365 days = 14,016 kWh/year
At the average US electricity rate (~$0.16/kWh): ~$2,240/year

Add internet, minor hardware maintenance, and replacement parts: ~$4,000/year
Total annual overhead: ~$6,000/year

THE MATH THAT MATTERS
Total cost to build and run this farm for one year: ~$58,000
Claimed annual profit: $450,000

That means this setup could pay for itself almost 8 times over in its first year.

NOW COMPARE IT TO A REGULAR JOB
The average annual salary in the US in 2026 is $63,795.

Building this entire farm costs less than one year of the average American's salary.

The farm's yearly profit ($450,000) equals roughly 7 years of the average American's salary - earned in 12 months, by machines that don't sleep, don't take vacation, and don't ask for a raise.

While most people trade 40 hours a week for a paycheck, this room of Mac minis is quietly out-earning the median American worker by 7x - with a starting investment smaller than a single year's salary.

The AI gold rush isn't just about GPUs. Sometimes it's about knowing where nobody else is looking.

[HMCM @HMCMcrypto]

https://t.co/Np4DMQdcWd

[HMCM @HMCMcrypto]

https://t.co/Np4DMQdcWd

[HMCM @HMCMcrypto]

One box replaces a whole rack of hardware.

Four DGX Sparks. Zero extra switches.

The VIVIBIT E1001 links them directly - built-in 4×50G Ethernet instead of a separate networking switch.

Fewer boxes in the rack means less power burned on cooling, less power burned on networking gear. The E1001 itself runs on <100W.

4 PFLOPS of compute, room for models up to 671B parameters - all without the extra hardware that usually sits plugged in right next to it.

Fewer boxes. Same firepower.

[HMCM @HMCMcrypto]

https://t.co/0ZNKfryXT9

[HMCM @HMCMcrypto]

He didn't build a data center. He built a farm on his kitchen table.

150 Mac minis. Stacked. Silent. Running 24/7.
He put in $119,850: the hardware, the racks, the networking, six months of rent, upkeep.

Electricity is almost a joke to calculate - the whole fleet of 150 machines burns less than $3,000 over six months. That's what Apple silicon efficiency looks like at scale.

Over six months, the farm generated $260,000 in revenue.

After every expense - hardware, rent, power, maintenance - about $140,000 was left as clean profit.

No GPUs screaming at the edge of their limits. No electricity bill that makes you want to cry. Just dozens of small boxes, quietly doing the work.

While everyone chased the next Nvidia card, he chose efficiency. Small footprint. Massive output.
The farm doesn't sleep. Neither does the profit.

[HMCM @HMCMcrypto]

@NVIDIARTXSpark I'll be waiting)

[NVIDIA RTX Spark @NVIDIARTXSpark]

Ready to get started with a local AI agent workflow on DGX Spark? 👀

We've got agentic playbooks covering NemoClaw, OpenClaw, Hermes, and OpenShell, from setting up agents to securing long-running workflows, all running on locally. 👇

[HMCM @HMCMcrypto]

@AMD Well, the thing in the photo looks like it will change the world

[HMCM @HMCMcrypto]

@mikenevermiss hah that changes everything it's just a crazy thing

[HMCM @HMCMcrypto]

This is the AMD Ryzen AI Halo. And once you actually hold it, you get why people are obsessed.

Inside: the Ryzen AI Max+ 395 processor. 128GB of unified RAM. Enough to run AI models most machines can't even load.

But specs aren't the interesting part. This is.
He pulls up Hermes - an open-source AI agent, MIT licensed, installed as a desktop app in seconds. No terminal required on Windows. It just runs.

And it's not hitting someone else's servers. It's not routing through a data center you don't control.
It's on your network.

That's the entire pitch of this machine in one sentence: real AI agents, running locally, on hardware you own - private by default, not by promise.

Best local AI setup? Might be the easiest yes we've said all year.

[HMCM @HMCMcrypto]

https://t.co/Rr83kqw1KX

[HMCM @HMCMcrypto]

This guy just unboxed the console Valve swore it would never make again.

Eleven years after the first Steam Machine flopped, this black cube just landed - and it's not playing around.

Inside: a semi-custom AMD Zen 4 CPU. A RDNA 3 GPU pushing six times the power of the Steam Deck. 16GB of RAM. Up to 2TB of storage.

No Windows. No bloat. Just SteamOS booting straight into your entire library - on a TV, with a controller, in seconds.

$1,049 to start. Not cheap. Not trying to be.
Valve isn't chasing PS5 buyers. Valve is chasing PC gamers who are done building rigs.

This is what "it just works" looks like when a hardware company finally means it.

[HMCM @HMCMcrypto]

This girl just plugged in a $3,999 box the size of a book - and it's running AI models that used to need a data center.

No cloud. No subscriptions. No waiting in line for GPU credits.

Just raw, local horsepower - sitting on her desk, humming quietly while it does the work.

This is the NVIDIA DGX Spark. And she's already three steps ahead of everyone still asking ChatGPT for help.

The future of AI isn't in the cloud. It's on your desk.

[HMCM @HMCMcrypto]

https://t.co/0ZNKfryXT9