this post was submitted on 03 Jul 2026
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Something I’ve been noticing recently is that while the cost per token on specific models hasn’t gone up, the provided interfaces for using those models are starting to chew up significantly larger numbers of tokens for the same tasks that used fewer tokens with older versions of the interface software just a few months ago. Likely the interfaces are applying more expensive guardrail prompts and charging the end user for those tokens — but the end result is that it costs 4x as much to get the same work done.
A very large chunk of the improvements in the last year have come not from categorically better models, but from the circumstances of the models massively improving. For example, reasoning is just automatic prompt engineering, and eats a fuckton of tokens. Harnesses give LLMs tools, making it easier to turn nondeterminism into determinism (does this code compile is a decision the compiler can answer definitely). Then there's subagents, which is just automatic context engineering.
Basically, the price per token might not have changed, but in practice, the amount of tokens used to get "SOTA" performance has massively increased.