What the F**k Is OpenAI's o1 Model? Reasoning vs. Predicting Explained

The AI That Thinks Before It Speaks

You might have noticed some AI models take 10 seconds to answer. They are thinking. This is not a bug. It is a fundamental shift in how AI works.

The Difference

Previous models like GPT-4 were intuitive. They answered immediately based on pattern matching. The o1 model uses "Chain of Thought" reasoning to verify its own logic before outputting a response.

When to Use Each

Use GPT-4 class models for:

• Writing emails and marketing copy
• Summarizing documents
• Simple Q&A and customer support

Use reasoning models (o1, o3, Claude with extended thinking) for:

• Analyzing contracts and legal documents
• Writing complex architecture code
• Multi-step mathematical or logical problems
• Any task where getting it wrong has serious consequences

The Cost Tradeoff

Reasoning models use more tokens (and cost more) because they "think out loud" internally before producing a final answer. This means you should not use them for everything. Route simple tasks to fast models and complex tasks to reasoning models.

What This Means for Production Systems

Smart AI applications use model routing. They assess the complexity of each request and send it to the appropriate model. This saves money and delivers better results simultaneously.

We switch between models automatically in our apps depending on the difficulty of the task to save you money and time. The user never knows which model handled their request — they just get the right answer.