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arXiv cs.LG
arXiv cs.LG
5/12/2026
Statistical Inference and Quality Measures of KV Cache Quantisations Inspired by TurboQuant

Statistical Inference and Quality Measures of KV Cache Quantisations Inspired by TurboQuant

Short summary

Research analyzing three KV cache quantization schemes reveals KQV outperforms alternatives at 4-bit budget across all metrics. Jensen's inequality amplification through softmax explains performance variations at different bit budgets. Opens rate-distortion optimization problem for asymmetric K-V quantization.

  • •KQV quantization wins at 4-bit budget on every metric (KL divergence, geometric error, distance)
  • •K-V asymmetry is unconditional: QKQV consistently worse than KQV in KL divergence across all budgets
  • •Jensen mechanism through softmax is likely operative cause of performance crossover at different bit budgets

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