The performance of local AI for coding, given correct setup & harness, is very good and on par for 95% of use cases compared to closed models.
Local usage for end-users is unmetered and token speeds are very fast and keep improving every few weeks due to optimizations being done in the community.
Data remains local which makes EU compliance checkboxes way easier since data never touches anything related to the CLOUD act.
Kevin_Flynn•39m ago
An RTX 5060 Ti 16GB card costs about $800 on Amazon right now. Running 18.4 hours a day ( off peak electric rate schedule ) it can process approximately 109.3 million tokens per month. The card has a 90 day return window. Credit card interest + electricity puts the cost at $80 total out of pocket, to use this card for 3 months and return it.
Paying an AI provider came out to $1,639.50 for the same 3 months of 18.4 hour a day usage.
You know its a bubble when ... $80 vs $1,639.50
I understand that if you're a major corporation, or a researcher that needs 100+ gpus for a large project, unless you have access to your own supercomputer, the economics will be different.
This was for "individual coder at home" scenarios.
rokkamokka•35m ago
akmarinov•32m ago
Kevin_Flynn•31m ago
The 5060 wasn't the fastest/$, it just provided the most VRAM / $ as of yesterday.
Im installing it in a box with a 4070 Ti to run 2 different models simultaneously. Coder + MoE via paperclip or multica.
reedf1•35m ago
embedding-shape•32m ago
I too did a cost breakdown of buying my GPU for ~10K EUR more than a year ago. It came out "Invaluable" as I use it for analyzing my diary, financials and other private things I cannot send to random 3rd parties.
But even the best of models you can run with 96GB VRAM really doesn't come close to the hosted SOTA models, sadly.
ALLTaken•30m ago
welferkj•30m ago