TRANSMISSION_ID: MAC-STUDIO-PAPERWEIGHT

MAC STUDIO PAPERWEIGHT

DATE: 2025-10-XX//AUTHOR: ARCHITECT

Beautiful. Useless.

HARDWAREAESTHETIC: 10/10COMPATIBILITY: 2/10

MAC_CRUSHED_BY_NVIDIA

The "192GB RAM" Trap

Apple sells you a dream: "192GB of Unified Memory! Run huge models on your desk!"

It sounds amazing. I bought one.

Then I tried to run code.

The CUDA Monopoly

Here is the hard truth: AI is Nvidia's world. We just live in it.

99% of AI repositories on GitHub are optimized for CUDA. Apple's "Metal" (MPS) is an afterthought. It is buggy. It is slow. It is unsupported.

[GAME] :: TECH_DEATHMATCH_SIMULATOR

Mac Studio (M2 Ultra)

Nvidia Rig (4090)

◀192 GB (Huge)

Memory

24 GB (Tiny)

Beta / Broken

Software Support

Native / Instant▶

Slow

Training Speed

Blazing▶

◀High

Resale Value

Moderate

VERDICT: DRAW

SYS_READYID: UK7Y8W

Inference vs Training

If you just want to run LLMs (Ollama), the Mac is actually okay. It's quiet. It's efficient.

[EXPLOIT] :: WARNING: PYTORCH SUPPORT

MPS Backend

BETA

Flash Attention

MISSING

xFormers

UNSUPPORTED

SYS_READYID: LYQN1T

But if you want to train? If you want to finetune? If you want to use the bleeding edge tools released 5 minutes ago?

You will spend 90% of your time debugging dependencies and 10% coding.

[GAME] :: VIBE_CHECK

Q: 1/1SCORE: 0

Is this verified?

SYS_READYID: 3XS648

[SIMULATION] :: THE_SUBSCRIPTION_BLEED

YOUR_MONTHLY_RENT

Netflix$22

Spotify$12

Adobe Creative Cloud$60

Dropbox$15

ChatGPT Plus$20

Midjourney$30

TOTAL$159/mo

*Click items to cancel them.

COST OVER 5 YEARS

$9,540

IF INVESTED (S&P 500)

$13,356

LOCAL_ALTERNATIVE_COSTNAS ($400) + Plex ($0) + Obsidian ($0) + Stable Diffusion ($0)
$400 one-time

SYS_READYID: 78AUFH

[SIMULATION] :: HUMAN_VS_MODEL_LATENCY_TEST

MODEL_V5 (AUTO-REGRESSIVE)0%

YOU (BIOLOGICAL NEURAL NET)NaN%

TYPE THIS PROMPT:

SYS_READYID: E8BL4T

Conclusion

The Mac Studio is the best computer I have ever owned for video editing. For AI? It is a $5,000 aluminum paperweight.

Buy a cloud GPU. Or build a PC. Don't fight the CUDA current.