OpenAI embeddings vs ZeroEntropy zerank and zembed

OpenAI embeddings

text-embedding-3-small at $0.02 per million tokens, $0.01 through the Batch API. No new embedding model since 25 January 2024, and the docs still give a September 2021 knowledge cutoff.

ZeroEntropy zerank and zembed

All four models now open weights under Apache 2.0 on Hugging Face. The hosted API was discontinued after 4 September 2026 and signups closed on 24 July 2026.

OpenAI embeddings

1. Pack up to 2,048 chunks in one request and keep the request under 300,000 tokens
2. Count tokens before sending. An input over 8,192 tokens is rejected, not truncated
3. Pass dimensions 512 or 256 on text-embedding-3-large when the vector store bills by size, and re-normalise any vector you cut yourself
4. Split a Batch API index job into batches of under 50,000 inputs. It's half price with a 24-hour window
5. Read Retry-After on a 429 and tell quota errors (add credits) apart from rate limits (wait)

ZeroEntropy zerank and zembed

1. Don't call api.zeroentropy.dev. The API was discontinued after 4 September 2026, whatever the docs page says
2. Self-host zerank-2 or zembed-1 from Hugging Face under Apache 2.0 if you want the same model
3. Pick a hosted reranker elsewhere if you can't self-host. ZeroEntropy's own guide names Cohere and Voyage
4. Re-embed the corpus if you move off zembed-1. Vectors from another model aren't compatible