---
date: "2025-06-29T04:10:05Z"
categories:
  - linkedin
  - llms
description: "The duration of a model’s reasoning block can be treated as a practical measure of its independence on longer tasks."
keywords: ["ChatGPT", "thinking time", "reasoning duration", "model evaluation", "conversation history", "O3"]
---

How long have _you_ made ChatGPT think? My highest was 6m 50s, with the question: _Here are vehicle telematics stats for_ 2 _months. Unzip it and take a look. Find interesting insights from this data. Look hard until you find at least_ 5 _surprising insights from this_.

The next largest thinking block (5m 42s) was where I asked: _I would like to explore parallels to the current phenomenon where intelligence is becoming too cheap to meter. Historically, both in recent history as well as over ancient history, what technologies have made what kind of tasks so cheap that they are too cheap to meter? Give me a wide range of examples_

Completing long tasks is one measure of intelligence. **Working independently for long** is another. O3 is at ~6 minutes. While it works, I'm practicing Bubble Shooter in 6 minutes!

Completing long tasks: https://www.lesswrong.com/posts/deesrjitvXM4xYGZd/metr-measuring-ai-ability-to-complete-long-tasks

You can do try this on your history. If you managed to beat 7 minutes, could you please share your prompt?

- How to export ChatGPT history: https://help.openai.com/en/articles/7260999-how-do-i-export-my-chatgpt-history-and-data
- How to analyze thinking time: https://www.npmjs.com/package/chatgpt-to-markdown

... or run:

`npx -p chatgpt-to-markdown thinktime conversations.json`

[LinkedIn](https://www.linkedin.com/feed/update/urn%3Ali%3Ashare%3A7344940195856752642)