Are there any hidden costs or unexpected pricing spikes I should watch out for when using Pinecone vector database alongside the OpenAI embeddings API?
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Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
Are there any hidden costs or unexpected pricing spikes I should watch out for when using Pinecone vector database alongside the OpenAI embeddings API?
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
Pinecone pricing serverless read units write units storage overage pricing official 2026 Google ↗
OpenAI API embeddings pricing text-embedding-3-small text-embedding-3-large official 2026 Google ↗
- text-embedding-3-large Model · developers.openai.com
- text-embedding-3-small Model · developers.openai.com
- Pricing · pinecone.io
- Manage Serverless Costs with Read Units · pinecone.io
- AWS Marketplace: Pinecone Vector Database- PAYG · aws.amazon.com
- New embedding models and API updates · openai.com
- Vector embeddings · developers.openai.com
- OpenAI API pricing · developers.openai.com
- OpenAI embeddings guide · developers.openai.com
Queries
2 queries · click a column to sort
| Query / type | Search | Intent | Query class | Routing format | Cluster | Freq ↓ | Weight |
|---|---|---|---|---|---|---|---|
Pinecone pricing serverless read units write units storage overage pricing official 2026 OBSERVED | Google ↗ AI Mode ↗ | — | — | — | — | 1x of 1 | |
OpenAI API embeddings pricing text-embedding-3-small text-embedding-3-large official 2026 OBSERVED | Google ↗ AI Mode ↗ | — | — | — | — | 1x of 1 |