I already came to that conclusion as you see in the gpt-5.6 announcement topic with my caution. Also, what I’ve already written:
If you read the specs the right way, past obfuscation, the model essentially has a hidden “cache writes” permanent cost, 1.25x greater than advertised. Then, upon that real price (1.25x the “input tokens” that you cannot obtain unless input is too small to cache) could have been advertised a few percent more cache discount - when you can get one.
Not sending a prompt cache key is not an avoidance technique of increased billing. You send a >1k input, you get hit with the bill. You can try to manually fudge with “explicit” cache, but there, you also do new coding that guesses and needs to know the future, the future of what will happen in the next 30 minutes on a non-shareable not arbitrarily-incomplete context.
Read docs: the 5.6 cache retention is 30 min, without 24hr. The same kind of cache breaking without any partial matches seen on prior inputs as 5.5.
Besides “too small to cache” API calls, the only exception for input tokens with increased cost seems to be a variable bit of the end of billed input context that is not sent for prompt cache. What was there? Is there an arbitray hard-to-discover granularity to what can be stored…or an OpenAI post-prompt injection counter to your user’s goal?
If you want to diagnose the actual behavior, you’d have to create a new project, unenroll it from promotional free tokens, make a single call that “usage” shows that you got a bill almost entirely at $6.25/mil instead of $5.00 by all “writes”, and then pull down the truth of that with the costs API endpoint that only gives daily buckets and might not have the decimal places needed for differentiation.