TokenSkim

Why your embeddings bill is high — and how to cut it

Embeddings are priced low per token, which is exactly why the bill sneaks up: teams re-embed the same content, pick a larger model than they need, and embed data that never gets queried.

Stop re-embedding unchanged content

Re-embedding your whole corpus on every deploy or nightly job is the most common embeddings waste. Embed on change only, keyed by a content hash.

Right-size the embedding model

The largest embedding model is rarely worth its price for retrieval. A smaller model often gives near-identical recall at a fraction of the cost — measure before defaulting to the big one.

Turn this into your number

Drop your usage export into the free analyzer and see how much of this applies to your account — provable savings separated from estimates. Nothing is uploaded.

Analyze my usage — free