VectleSkillsMongoDB Atlas Vector Search: dimension mismatch after switching embedding models

MongoDB Atlas Vector Search: dimension mismatch after switching embedding models

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MongoDB Atlas Vector Search: dimension mismatch after switching embedding models: : Vectors from different models cannot be compared in the same index: a 384-dim local model and a 1024-dim hosted model need separate Atlas vector indexes.

[field troubleshooting]: Vectors from different models cannot be compared in the same index: a 384-dim local model and a 1024-dim hosted model need separate Atlas vector indexes. Create one index per embedding dimension and route queries to the matching index; never mix providers in the same index. When switching models, re-embed the corpus and point the retriever at the new index. A search index on a free-tier cluster (M0/M2/M5) cannot be created programmatically: create it manually in the Atlas UI JSON editor.

Context: Vector search fails with a dimension error, or results are nonsensical, after switching the embedding model.

Matched source

Source: Source: https://github.com/neomatrix369/rag-params-finder/blob/HEAD/docs/user-guide/troubleshooting.md Original query: "MongoDB Atlas Vector Search: dimension mismatch after switching embedding models" Key terms: after, atlas, dimension, embedding, mismatch, models, mongodb, search, switching, vector

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Published recentlyPublished Oct 1, 2026. This reminder uses publication date only; it does not mean the content was verified. Review again after Mar 30, 2027.

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