Thinking Budget in New Models

1. Concept Overview & Systemic Problem

Previously, users were caught between two extremes:

1. Standard models (GPT-4o) responded instantly but often made mistakes in complex logic.
2. Reasoning models (o1) took a long time to ponder every word, even for elementary questions.

The emergence of hybrid systems with a Thinking Budget finally provided users with full control. Now you decide how much resource to allocate to the AI:

• For simple tasks: turn off reasoning entirely ➔ receive an answer in half a second.
• For complex problems: allocate a large budget ➔ the model thoroughly "digs" into the issue.

For beginners, the Thinking Budget is the ability to pay with time and tokens only when the task truly warrants it.

2. Architectural Taxonomy & Mental Model

┌─────────────────────────────────────────────────────────────┐
│                 LEVELS OF THINKING BUDGET                  │
├─────────────────────────────────────────────────────────────┤
│ ⚡ 0 tokens (Off / Instant Mode):                            │
│    • Response in 0.3 seconds                                 │
│    • Simple translations, writing emails, minor edits       │
├─────────────────────────────────────────────────────────────┤
│ 🧠 1,024 – 4,000 tokens (Medium / Quick Check):             │
│    • Reasoning 3–6 seconds                                   │
│    • Searching for logical inconsistencies in a contract    │
│    • Writing a standard script with validation               │
├─────────────────────────────────────────────────────────────┤
│ 🔬 16,000 – 64,000 tokens (High / Deep Audit):               │
│    • Reasoning 15–40 seconds                                 │
│    • Architectural audit of a complex database               │
│    • Proving mathematical theorems, quantum physics         │
└─────────────────────────────────────────────────────────────┘

3. Technical Pipeline & Internal Mechanics

01. When to Set Minimum (or Turn Off)

• When editing the style of a finished email.
• When translating text from one language to another.
• When asking for 10 blog title suggestions.
• Excessive reasoning here only wastes your time and money.

02. When to Set Maximum

• When the program produces a non-obvious bug that you've been searching for three days.
• When designing the database structure for a service with a million users.
• When solving an Olympiad problem or writing a scientific paper.
• In these cases, every second of the model's reasoning saves you hours of manual work.

4. Production Engineering Scenarios

Artificial intelligence has ceased to be "monolithic": if the model initially provides a raw answer, you don't need to write lengthy complaints. Just hit Edit, double the reasoning budget, and send the request again — the depth of analysis will increase exponentially!