Comparing open source LLM fine tuning costs versus using proprietary APIs for my local real estate business
Download run
Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
Comparing open source LLM fine tuning costs versus using proprietary APIs for my local real estate business
3 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.
ChatGPT real searches (3)
Classes come from the query-classifier (a local Laya model). 3 of 3 calls are low-confidence (under 50%) — hover a query in the table to see its confidence.
Searches and sources
ChatGPT3 real searches · gpt-6
2026 LLM API pricing OpenAI GPT fine tuning pricing official Google ↗
2026 open source LLM fine tuning GPU cloud hourly pricing NVIDIA H100 A100 official Google ↗
Anthropic API pricing 2026 official Google ↗
- Pricing · huggingface.co
- blog/train-dgx-cloud.md at main · huggingface/blog · github.com
- Pricing · developers.openai.com
Queries
3 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
2026 LLM API pricing OpenAI GPT fine tuning pricing official OBSERVED | Google ↗ AI Mode ↗ | — | Other / navigational | — | — | 1x of 1 | |
2026 open source LLM fine tuning GPU cloud hourly pricing NVIDIA H100 A100 official OBSERVED | Google ↗ AI Mode ↗ | — | Reason | — | — | 1x of 1 | |
Anthropic API pricing 2026 official OBSERVED | Google ↗ AI Mode ↗ | — | Yes / no | — | — | 1x of 1 |