analiza aiqbench
The article estimates that the cost of a fixed level of AI performance has fallen about 47% per quarter since 2023, with faster declines for math benchmarks and slower ones for game-based puzzles. Costs drop fastest just after a capability first reaches state of the art and then slow sharply. For readers, the key caveat is that these are cost-per-capability figures on five benchmarks, not a measure of what frontier models cost to train or serve.
The plunging price of thought

AI has gotten cheaper more quickly than any other transformative technology in history. The cost of achieving a given level of AI performance has fallen about 47% per quarter since 2023, or 13× per year. That price drop is four times faster than DNA sequencing, six times faster than compute, 18 times faster than lithium batteries, and (in the century up to 1973) 54 times faster than electricity. Coarser evidence suggests that the price of thought has been falling at least this fast since the dawn of commercial LLM inference in November 2021, when OpenAI fully released GPT-3. The speed of price drop varies by domain: slower on game-based puzzles, at 39–43% per quarter, faster on math problems, at 50–52% per quarter. The cost of a given level of performance often falls fastest right after that level is first achieved, that is, when it is state of the art (SOTA). We see this pattern on three of our five main benchmarks of AI capability. Averaging across all five, cost falls 66% per quarter (75× per year) for performance that has just debuted as SOTA. Two years later, prices fall half as fast, at 32% per quarter (4.7× per year). Data…
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