how do I estimate the cost of fine tuning a custom model via the openai api compared to using prompt engineering with few shot examples
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Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
how do I estimate the cost of fine tuning a custom model via the openai api compared to using prompt engineering with few shot examples
2 real searches · 1 real-search pass
Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.
Query classes
Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.
Classifying 2 queries…
Searches and sources
ChatGPT2 real searches · gpt-6
OpenAI API pricing fine-tuning training token prices and model input output token pricing 2026 Google ↗
OpenAI fine-tuning guide training tokens epochs pricing API documentation Google ↗
- Pricing · developers.openai.com
- Pricing · developers.openai.com
- Supervised fine-tuning · developers.openai.com
- Fine-tuning best practices · developers.openai.com
Queries
2 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
OpenAI API pricing fine-tuning training token prices and model input output token pricing 2026 OBSERVED | Google ↗ AI Mode ↗ | — | — | — | — | 1x of 1 | |
OpenAI fine-tuning guide training tokens epochs pricing API documentation OBSERVED | Google ↗ AI Mode ↗ | — | — | — | — | 1x of 1 |