What is this about and how do I use it? 🤔
What is this?
Imagine asking an AI (like ChatGPT) to solve a complex problem. If you give it more time and space to "think" through the steps, it can often produce a more detailed and accurate answer. This "thinking time" is measured in tokens (pieces of words).
This simulator demonstrates that concept. It shows how the quality of an AI's reasoning changes when we give it a different "thinking budget."
How to use this demo:
- Select a Problem: On the left, pick a problem for the AI to solve from the dropdown menu.
- Choose a Thinking Level: Select a "Low," "Medium," or "High" thinking budget.
- Observe the Results: On the right, you'll see the AI's step-by-step "thought process" and its final answer for the budget you selected.
Play around with the levels to see how a bigger budget can change the AI's path to the answer!
Here's related scientific research in the area of budget-aware LLM reasoning and problem solving:
Li, J., Zhao, W., Zhang, Y., & Gan, C. (2025). Steering LLM Thinking with Budget Guidance. arXiv:2506.13752.
Configuration
Problem: Solve a grade-school math word problem that requires a step-by-step reasoning process.
LLM's Reasoning & Response
The Key Takeaway: The "Cost of Thinking" in AI
What's the practical lesson from this simulator?
The quality of an AI's answer is directly tied to its "thinking budget." This simulation makes that abstract idea tangible.
- Not All AI Answers Are Equal: A quick, low-budget answer from an AI might be sufficient for a simple query, but it could be superficial or even incorrect for a complex problem. As you saw in the "Capital City Finder" example, a low budget might miss the final step of the reasoning process.
- There's a Cost-Quality Trade-off: Running large language models costs money, and that cost is proportional to the computational budget (measured in tokens). In the real world, developers and companies constantly have to balance this: Do we want a fast, cheap answer, or a more thoughtful, accurate, and expensive one? This simulator puts you in the driver's seat of that trade-off.
- Become a More Critical User: By understanding this principle, you can become a more discerning consumer of AI. When you get a response from an AI tool, you can now ask yourself: "How much 'thought' went into this? Is this a surface-level answer, or a deeply reasoned one?"
Ultimately, this demo reveals that AI reasoning is not magic—it's a resource-intensive process. The more resources we allocate, the better the potential outcome.