Framework Diagram

AI Access Pyramid: Cost vs Availability

The paradox: compute gets cheaper, but frontier reasoning keeps consuming more of it. Four tiers define who can access what — and at what cost.

High cost
Low avail.
Access & Cost
Low cost
High avail.
FRONTIER REASONING Very expensive · very limited Deep research · long-horizon agents · complex planning $ $ $ $ ADVANCED PROFESSIONAL AI Expensive but available Coding agents · data analysis · legal/finance enterprise workflows $ $ $ GENERAL-PURPOSE AI Affordable and broadly available Chat · search · summarization · translation writing · basic coding · customer support $ $ COMMODITY / LOCAL AI Cheap, abundant, open to everyone Small models · open source · on-device AI classification · extraction · simple assistants $ 4 3 2 1
→   Increasing scale, efficiency, and openness  (drives cost down & availability up)
Why Expensive?
  • High compute per task
  • Best chips (GPUs / TPUs)
  • More memory & bandwidth
  • More power & cooling
  • Scarce capacity
  • High opportunity cost
Why Costly?
  • Significant compute required
  • Larger models needed
  • Paid APIs / services
  • Enterprise-grade reliability
Why Affordable?
  • More efficient models
  • Optimized inference
  • Competitive APIs
  • Economies of scale
Why Cheap?
  • Open source models
  • Can run locally
  • Low compute needs
  • High availability
Task Cost =
Unit Compute Cost × Reasoning Intensity × Scarcity Premium
Commodity tasks: low cost
Frontier reasoning: high cost
↓ Unit compute
decreasing over time
↑ Reasoning intensity
increasing for frontier
↑ Scarcity premium
rises when supply < demand
The Takeaway

AI becomes cheaper at the bottom and more compute-hungry at the top. The gap between commodity and frontier widens over time — not closes.