Fine-Tuning vs Prompt Engineering

Written by Jakub Rusinowski · Last updated July 10, 2026

Should you train your own model? Usually, the answer is no.

In This Guide

• Prompt Engineering (Context)
• Fine-Tuning (Training)
• Verdict

Should you train your own model? Usually, the answer is no.

Prompt Engineering (Context)

Best for: Giving the model new information (RAG) or instructions.

• Pros: Instant, free, flexible.
• Cons: Limited by context window size.

Fine-Tuning (Training)

Best for: Changing the *behavior* or *style* of the model.

• Example: Making the model speak like a pirate permanently.
• Example: Teaching the model a new medical classification format.
• Pros: Permanent behavior change, no need for long prompts.
• Cons: Expensive (requires GPU time), difficult to get right, can cause 'catastrophic forgetting'.

Verdict

Try RAG (Retrieval Augmented Generation) first. Only fine-tune if RAG fails to capture the specific style or format you need.

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