4-bit quantized embeddings are near-lossless for search; 1-bit works with re-ranking
mgostIH · x · 2026-11-04
A developer shares hands-on findings on quantizing embedding vectors for search:
- Storing embeddings at 4-bit quantization is essentially lossless for search with new methods
- 1-bit or below also works well if you re-rank a larger pool of retrieved media, at higher inference cost
- Reference throughput: 78 img/s with DINOv3 on an RX 9070 XT
A practical storage-vs-accuracy tradeoff reference for large-scale media retrieval and local deployment.
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