Pinecone error: vector dimension does not match the index dimension

TL;DR: Upserting or querying with a vector whose length differs from the index dimension fails the whole request. The fix is at the embedding model or the index, never by reshaping vectors. Cause The embedding model changed (or was never the one the index was built for). text-embedding-3-small gives 1536, text-embedding-3-large gives 3072, many open models give 768 or 1024. Confirm both sides: len(embedding) from your model, and pc.describe_index(name) for the index dimension.

The fix

Dimension mismatch: the vector and the index disagree

The error

Upsert or query fails with a message like: vector dimension 768 does not match the dimension of the index 1536. The request is rejected; nothing is written.

Cause

The embedding model changed (or was never the one the index was built for). text-embedding-3-small gives 1536, text-embedding-3-large gives 3072, many open models give 768 or 1024. The index dimension was frozen at creation.

Fix

1. Confirm both sides: len(embedding) from your model, and pc.describe_index(name) for the index dimension.
2. If the model is right and the index is wrong: create a new index with the right dimension and re-ingest. There is no alter-index.
3. If the index is right and the model is wrong: switch back to the model the index was built for.

Never do this

Truncate or zero-pad vectors to force the fit. It silently destroys recall and the damage is invisible until someone evaluates. Dimension is a contract between the model and the index; keep it explicit in config, not inferred.

When to use this

• You are seeing this exact error message; match the block above, not just part of it.
• The failing call matches the scenario in the title: Pinecone error.
• You want the fastest verified fix before digging through logs.

When not to use this

• Your error text differs from the block above; close cousins often have different causes.
• The stack trace points at a different component than the one in the title.
• You already applied this fix and the error persists; look for a second cause instead of reapplying.

Compatibility

• Not pinned to a specific version; follows current Pinecone behavior.

Pinecone's index guides define dimension as fixed at creation and matched to the embedding model. The embedding-values troubleshooting page covers numeric handling on upsert. Verified against live docs 2026-09-26.