Minima-KV: Retention-Preserving KV Cache Compression with Mixed-Format Paged Attention
The key-value (KV) cache is a primary capacity and bandwidth bottleneck in long-context LLM serving. We present Minima-KV, a retention-preserving hierarchy for mixed-format paged attention. Recent and protected Anchor pages remain in FP8, while older non-anchor pages move to packed TQ3; every live-request page remains addressable. Format-specific kernels compute partial attention states and combine them through a globally normalized online-softmax merge, enabling direct heterogeneous decode without a cache-sized dense shadow. Across separate, configuration-bound Qwen3.6-27B profiles on a single 96-GB NVIDIA RTX PRO 6000 Blackwell GPU, deployment accounting reports 18.3 KiB of attention KV...
| Authors | Sergii Kozyrev, Davyd Maiboroda |
|---|---|
| Primary category | cs.AI |
| Published | 24 August 2026 |
| Last updated at source | 24 August 2026 |
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