A small AI team is still looking at a benchmark tab late at night when the hardware decision becomes real.
Apple's M5 Ultra has posted 15,350 points in Blender Open Data.
A Mac Studio with 80 GPU cores, 96 GB of unified memory, and 1 TB of storage costs just under $6,800.
An RTX 5090 build can cost around $9,000 while GPU and RAM prices stay elevated.
The benchmark is interesting.
The real pressure is elsewhere.
Every big hardware purchase locks up budget before the team knows which model workflow deserves it.
One delayed experiment becomes two.
A launch date moves because testing had to wait.
The turning point is choosing access over ownership for the work that still needs proof.
RTX 3090 compute at $0.15/hr lets a team test the next training run, validate a workload, and ship sooner without making a full hardware bet first.
Buy Now Pay Later means zero upfront and payment after one month.
Which workload would your team test first if GPU compute cost $0.15/hr?
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Originally posted on linkedin_personal