Current AI market dynamics point to frontier models becoming commodity infrastructure as the token crunch eases, with value shifting to products built on top
There are only two things you can say with certainty about token prices: we're in a supply crunch, and this is unstable.
Context & Ripple Effects
Related coverage has already documented falling per-token prices alongside a countervailing rise in developers’ total costs as reasoning-oriented models consume more tokens. It also framed model commoditization as a competitive problem for frontier-model providers rather than a settled outcome.
The current easing of token scarcity sharpens that tension: if access to capable models becomes less constrained, differentiation shifts toward the products, private data, and judgment layers that turn model capability into reliable work.
First-order effects
- Frontier-model providers face weaker scarcity-based pricing power as token availability improves and comparable model capability becomes easier to source.
- Application builders and enterprise buyers gain more room to choose among model suppliers, while product execution becomes more important than exclusive access to a frontier model.
Second-order effects
- Model vendors are pushed to compete more on cost, reliability, distribution, and integrated product offerings; developers can increase multi-model use rather than commit to a single provider.
- Lower token prices do not automatically lower application costs: products built around reasoning-heavy workflows may still face rising usage costs, increasing pressure to optimize model routing and task design.
Third-order effects
- If this pattern persists, the model layer increasingly resembles shared infrastructure, with durable margins concentrating in software that combines models with proprietary data, verification, workflow integration, and customer relationships.
- The transition is not automatic: providers that pair models with distribution or differentiated systems may retain leverage, but raw benchmark leadership alone becomes a less dependable moat.
The trend: AI is moving from scarce frontier-model access toward a more competitive infrastructure layer, making product-level integration and defensible workflow ownership the primary sources of value.