Question 1

Is fine-tuning worth the cost?

Accepted Answer

Fine-tuning is worth it when you need consistent output format, domain-specific knowledge, or want to reduce prompt length (saving inference costs). It's usually not worth it just for better general performance — prompting is cheaper to iterate.

Question 2

How many training examples do I need?

Accepted Answer

Start with 50-100 high-quality examples for simple tasks. Most use cases see good results with 500-1,000 examples. For complex tasks, 5,000-10,000 examples can significantly improve performance.

Question 3

Can I use fine-tuned models in production?

Accepted Answer

Yes — fine-tuned models are served via the same API as base models. You'll pay the standard inference rate (which may be slightly higher for fine-tuned models) plus the one-time training cost.

AI Fine-Tuning Cost Estimator — OpenAI Training Calculator

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