Is it cheaper to fine-tune open source models like Llama or just pay per token for commercial APIs given our low monthly volume?
Download run
Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
Is it cheaper to fine-tune open source models like Llama or just pay per token for commercial APIs given our low monthly volume?
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
Queries
2 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
2026 commercial LLM API token pricing input output OpenAI Anthropic Gemini official pricing OBSERVED | Google ↗ AI Mode ↗ | — | — | — | — | 1x of 1 | |
Llama self hosting GPU inference monthly cost cloud GPU pricing 2026 official OBSERVED | Google ↗ AI Mode ↗ | — | — | — | — | 1x of 1 |