Performance
Benchmarks
Independent results on public MTEB / BEIR / OMB datasets. SEMQ preserves accuracy while competitors collapse.
Dataset
banking77 (MTEB) · Model: all-MiniLM-L6-v2
| Method | Accuracy | Δ vs FP32 | Pass |
|---|---|---|---|
| FP32 | 92.26% | — | — |
| SEMQ·B | 92.23% | −0.03 pp | ✓ |
| SEMQ·A | 92.27% | +0.01 pp | ✓ |
| PQ 4-bit | 56.05% | −36.22 ppcatastrophic collapse | ✗ |
| OPQ 4-bit | ~60% | ~−32 ppcatastrophic collapse | ✗ |
⚠
PQ / OPQ collapse: −36 pp accuracy
Quantization methods that discard angular structure lose over a third of classification accuracy. SEMQ preserves the full semantic geometry — accuracy loss is statistically negligible.