# Balancing Reasoning vs Output in GPT-5

**URL:** <https://community.mindstudio.ai/t/balancing-reasoning-vs-output-in-gpt-5/1478>\
**Category:** Support\
**Created:** [August 10, 2025, 7:56pm UTC](https://community.mindstudio.ai/t/balancing-reasoning-vs-output-in-gpt-5/1478 "2025-08-10T19:56:19Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![bkermen](https://yyz2.discourse-cdn.com/flex008/user_avatar/community.mindstudio.ai/bkermen/32/1287_2.png) [@bkermen](https://community.mindstudio.ai/u/bkermen)\
**Post date:** [August 10, 2025, 7:56pm UTC](https://community.mindstudio.ai/t/balancing-reasoning-vs-output-in-gpt-5/1478/1 "2025-08-10T19:56:19Z")

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I’m running into an issue with the new GPT-5 model. I’ve got a detailed prompt that needs to be followed to the letter, so I set reasoning effort to **high**. The output I want is short (around 100 words), so at first I set the max response size to **4000**. This worked fine at first… but then some runs started returning empty strings.

Looking at the profiler logs, I saw the model generating all 4000 tokens for _reasoning_ and leaving nothing for the actual output.

So, I tried bumping the max response size to **20000** - thinking that would be plenty. That fixed the empty output problem, but now almost all 20000 tokens are going into reasoning, which really drives up the cost.

Ideally, I’d like a setup where I can have something like 5000 total tokens, with ~90% going to reasoning. Claude Sonnet 3.7 lets you set both a max response size and a separate max reasoning size, but GPT-5 doesn’t seem to have that option.

Any suggestions on how to best handle this?