We are comparing OpenAI API costs against local open source deployment for text summarization, so which approach makes more financial sense for a company processing two million words daily?
Download run
Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
We are comparing OpenAI API costs against local open source deployment for text summarization, so which approach makes more financial sense for a company processing two million words daily?
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 GPT-4.1 mini GPT-4.1 nano input output per million tokens official pricing 2026 Google ↗
self hosted open source LLM inference GPU cloud hourly pricing H100 A100 2026 vLLM cost Google ↗
- Pricing · platform.openai.com
- Pricing · developers.openai.com
- GPT-4.1 Mini Model · developers.openai.com
- Introducing GPT-4.1 in the API · openai.com
- LLM inference cost: self-hosted GPU vs API, per 1M tokens · cloudparity.io
Queries
2 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
OpenAI API pricing GPT-4.1 mini GPT-4.1 nano input output per million tokens official pricing 2026 OBSERVED | Google ↗ AI Mode ↗ | — | — | — | — | 1x of 1 | |
self hosted open source LLM inference GPU cloud hourly pricing H100 A100 2026 vLLM cost OBSERVED | Google ↗ AI Mode ↗ | — | — | — | — | 1x of 1 |