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AI & LLM Engineering · Building with LLM APIs · Card 015/024 hard

A developer calls a reasoning model through OpenAI's Responses API with `max_output_tokens` set, and gets back a response whose `output_text` is empty even though the usage data shows a large number of billed output tokens. According to OpenAI's documentation, what is most likely happening, and how should the application detect it?

  1. the response's `status` field will be `error` with an `error.type` of `server_error`, indicating an internal fault on OpenAI's infrastructure that is unrelated to the token limit set on the request
  2. this cannot happen when `max_output_tokens` is set, since OpenAI's documentation guarantees a visible answer is always produced in full before any internal reasoning tokens are counted against the limit
  3. the response's `output` array will always still contain a text message item in this situation, so an application never needs to check anything beyond `output_text` before using the result
  4. the response's `status` field will be `incomplete`, with `incomplete_details.reason` set to `max_output_tokens`, because a reasoning model's internal reasoning tokens can consume the entire token budget before any visible answer is produced; an application should check `status` and `incomplete_details` rather than assuming `output_text` is populated, and should reserve enough budget for both reasoning and the visible answer
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