Goldman Sachs data shows AI model costs fell as fast in three years as PC prices did in 15

Goldman Sachs data reveals AI model prices dropped 95% in 3 years, outpacing PC price decline

Introduction

The AI industry has experienced significant price drops in recent years, with AI model prices falling about as much in three years as personal computer prices fell over 15.

The Numbers Behind the Collapse

The a16z analysis tracks large language model pricing against a baseline index set at 100 in March 2023. By September 2026, the index had dropped to approximately 5. That works out to a decline of approximately 95%. A service that cost a dollar at the start now costs about a nickel.

The Forces Behind the Price Drop

The analysis credits three forces for the speed of the AI price drop: intense competition among model developers, growing efficiency in proprietary models, and the arrival of cheaper open-source alternatives.

Token Prices Tell the Same Story

A separate gauge points in the same direction. The Silicon Data LLM Token Expenditure Index measures how much buyers spend per million tokens. In August 2026, that index hit a record low of $0.97 per million tokens. That was a 29% fall from July. It also put the index more than 50% below its peak of roughly $2.05, set in May 2026.

What Cheaper AI Means for Companies

The overcapacity risk lands most heavily on the biggest spenders. Meta, Microsoft, Amazon, and Alphabet are racing to adjust as the economics of AI shift under their feet. Goldman's warning boils down to this: if compute supply outruns demand, margins could come under pressure. The sustainability of those infrastructure investments could face real questions unless demand catches up with supply.

Buyer Benefits

For buyers of AI services, the trend has been almost entirely favorable. Costs that would have looked absurdly low in March 2023 are now standard, and the Silicon Data index suggests the slide has not yet stopped.