AI cost curves: efficiency beats brute force (Nov 2025)

Nov 2025

The hype cycle focuses on “bigger models”, but real adoption often follows cost curves. In 2025, teams measure quality per unit cost and adjust tooling accordingly.

That drives three trends: quantization and optimization, smarter routing across models, and on-device inference for latency-sensitive tasks.

How this changes creative workflows

Efficiency isn’t just a finance concern—it changes output quality. When iteration is cheap and fast, teams explore more and choose better. When it’s slow, teams settle early.

Practical implication

Design workflows that can swap engines. If your system assumes one model forever, you’ll pay a tax every time the market shifts.

A simple budgeting model

Allocate spend by phase: 60% exploration (fast models), 30% refinement (best‑fit engines), 10% finals (upscale + retouch). This keeps budgets predictable and quality high.

The winners will be teams that treat models as interchangeable components and invest in evaluation + routing, not in hero-model dependency.