Note: in order to turn off a cache write at the end of a final user message (total length of input), include:

    "prompt_cache_options": {  # New for gpt-5.6 family [sol, terra, luna]
        "mode": "explicit",  # default "implicit", for only one total cache write
        "ttl": "30m",  # only one default parameter "30m" for 30 minutes
    },

Larger issue: no cache writes at developer messages

Testing json_schema - chat completions - implicit cache

All calls against “gpt-5.6-terra”, default (null) reasoning/verbosity

Sending developer-only message: the AI has to infer an empty schema:

req_20570db7f5e24ff2939357f799bd5ae4

In implicit default, the issue: there is no cache write on only a developer message that is significantly in excess of the threshold.

  "usage": {
    "prompt_tokens": 1374,
    "completion_tokens": 320,
    "total_tokens": 1694,
    "prompt_tokens_details": {
      "cached_tokens": 0,
      "cache_write_tokens": 0,
      "audio_tokens": 0
    },
    "completion_tokens_details": {
      "reasoning_tokens": 98,
      "audio_tokens": 0,
      "accepted_prediction_tokens": 0,
      "rejected_prediction_tokens": 0
    }
  }

Making no implicit cache writes, when there is a structured response schema, might be reasonable default if one assumes that a JSON output will never be a growing response like a “chat”. You’ll see they didn’t do that, the API is messed up.

Testing json_object - chat completions - implicit cache

Turning off json_schema, for instead json_object (and the developer message already had high enough quality to operate alone):

req_cdac18a83fc84b97bfc78b81f21d9a42

  "usage": {
    "prompt_tokens": 1297,
    "completion_tokens": 318,
    "total_tokens": 1615,
    "prompt_tokens_details": {
      "cached_tokens": 0,
      "cache_write_tokens": 0,
      "audio_tokens": 0
    },
    "completion_tokens_details": {
      "reasoning_tokens": 114,
      "audio_tokens": 0,
      "accepted_prediction_tokens": 0,
      "rejected_prediction_tokens": 0
    }
  }

Then we still have “cache_write_tokens”: 0 in json object mode

Testing no response_format - chat completions - implicit cache

Final implicit test: using developer language only

req_7dbda6406a3b4a29a1dcf8cc27fed223

  "usage": {
    "prompt_tokens": 1297,
    "completion_tokens": 329,
    "total_tokens": 1626,
    "prompt_tokens_details": {
      "cached_tokens": 0,
      "cache_write_tokens": 0,
      "audio_tokens": 0
    },
    "completion_tokens_details": {
      "reasoning_tokens": 42,
      "audio_tokens": 0,
      "accepted_prediction_tokens": 0,
      "rejected_prediction_tokens": 0
    }
  }

No cache write was made on 1297 tokens sent - “cache_write_tokens”: 0,

I doubled up the developer message language: still no cache write:
req_81309862dfe7416394c227ebb87b70a7

  "usage": {
    "prompt_tokens": 2600,
    "completion_tokens": 96,
    "total_tokens": 2696,
    "prompt_tokens_details": {
      "cached_tokens": 0,
      "cache_write_tokens": 0,
      "audio_tokens": 0
    },
    "completion_tokens_details": {
      "reasoning_tokens": 0,
      "audio_tokens": 0,
      "accepted_prediction_tokens": 0,
      "rejected_prediction_tokens": 0
    }
  }

• The API is not fulfilling its promise of the amount for cache - PERIOD.*

Test with a “user” message included to actually get an instructed schema - THEN we get a cache write:

  "usage": {
    "prompt_tokens": 1334,
    "completion_tokens": 224,
    "total_tokens": 1558,
    "prompt_tokens_details": {
      "cached_tokens": 0,
      "cache_write_tokens": 1331,
      "audio_tokens": 0
    },
    "completion_tokens_details": {
      "reasoning_tokens": 0,
      "audio_tokens": 0,
      "accepted_prediction_tokens": 0,
      "rejected_prediction_tokens": 0
    }
  }

Switch that to a developer message as the second message, again NO implicit cache write at the end.

req_49447dea43f64c7b822525d7c7cf97de

“cache_write_tokens”: 0

Conclusion: OpenAI is not storing at developer message at end of input, as an automatic “prompt_cache_breakpoint”, or an explicit specification.

They expect “chat” patterns and can’t imagine anything else?

I think both of us have done plenty of free work for OpenAI, that this must be explained or fixed.

Symptom: A naive pattern of “preload” or “warm up” call will not generate a cache write where desired, and the first post shows failure even on explicit use mid-messages. An explicit use is also shown not to (didn’t test that myself).

Workaround: add a 1-part user message as an explicit write, and then use a 2-part user message in production of the next 30 minutes of calls. There, you can just send a linefeed as the first part. Alternately, a standalone “preprompt” user message 1 of no impact.