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kv-cache-compression

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Native Windows build of vLLM 0.23.0 - no WSL, no Docker. Python 3.13 + CUDA 12.8 + PyTorch 2.11 cu128 for RTX 30/40/50-series, pre-built wheel, Windows patchset, 10 KV-cache compression dtypes, OpenAI API server fixes, and Rust frontend support.

  • Updated Jun 30, 2026
  • Python

Discrete Kakeya cover for LLM KV cache: D4/E8 nested-lattice quantisation realising a Kakeya-style tube-cover over the direction sphere. 2.4x-2.8x compression at <1% perplexity loss on Qwen3, Llama-3, DeepSeek, GLM-4, Gemma. Drop-in transformers.DynamicCache. pip install kakeyalattice.

  • Updated Jun 15, 2026
  • Python

AI agent skill implementing Google's TurboQuant compression algorithm (ICLR 2026) — 6x KV cache memory reduction, 8x speedup, zero accuracy loss. Compatible with Claude Code, Codex CLI, and all Agent Skills-compatible tools.

  • Updated Mar 28, 2026
  • Python

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