PyPI · Go
LMCache/LMCache
LMCache: Supercharge Your LLM with the Fastest KV Cache Layer
Apache-2.0Aug 15, 2026 · metrics 2.10.0
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#kv-cache
Every repository in the public record carrying this tag — from its GitHub topics or the keywords its package registries publish. Health is measured under the same versioned methodology as the rest of the record.
11 records
PyPI
kvcache-ai/Mooncake
Mooncake is the serving platform for Kimi, a leading LLM service provided by Moonshot AI.
Apache-2.0Aug 12, 2026 · metrics 2.10.0
PyPI
MemTensor/MemOS
Self-evolving memory OS for LLM & AI Agents: ultra-persistent memory, hybrid-retrieval, and cross-task skill reuse, with 35.24% token savings and DeepSeek Harness support.
Apache-2.0Aug 28, 2026 · metrics 2.10.0
PyPI · npm
rajveer43/VeloxQuant-MLX
Fast KV-cache quantization for Apple Silicon (MLX) — 43 research-adapted compression methods with Metal kernels
MITSep 5, 2026 · metrics 2.10.0
PyPI
manjunathshiva/turboquant-mlx
Extreme weight + KV cache compression for LLMs on Apple Silicon (MLX implementation of Google's TurboQuant)
Custom licenseAug 28, 2026 · metrics 2.10.0
PyPI · crates.io
ahb-sjsu/turboquant-pro
Consumer-aware compression for embedding indexes and LLM KV caches — compress by the metric the downstream consumer actually uses. PCA-Matryoshka + TurboQuant (27x @ 99.8% recall@10), asymmetric K/V, CUDA/Triton kernels, vLLM plugin, replayable CI-gated claims. MIT.
MITSep 5, 2026 · metrics 2.10.0
PyPI
varjoranta/turboquant-vllm
TurboQuant+ KV cache compression for vLLM. 3.8x smaller KV cache, same conversation quality. Fused CUDA kernels with automatic PyTorch fallback.
MITJul 22, 2026 · metrics 2.10.0
Go · PyPI
anthony-chaudhary/fak
fak — the Fused Agent Kernel: one Go binary for AI agent loops. Wrap Claude Code/Codex/Cursor, keep long sessions cache-efficient, route work per call, run local GGUF models, and adjudicate tool calls.
Apache-2.0Jul 17, 2026 · metrics 2.10.0
PyPI
jagmarques/nexusquant
Training-free KV cache compression via E8 lattice VQ. 2-bit KV that preserves retrieval (30/30 NIAH vs TurboQuant 0/30). Calibration-free, 9 architectures validated.
Custom licenseJul 16, 2026 · metrics 2.10.0
npm
jiangge/pi-cache-optimizer
Improve Pi prompt/KV cache hit rates with stable prompts, OpenAI-compatible cache keys, proxy compat warnings, and footer cache stats.
MITJul 24, 2026 · metrics 2.10.0
crates.io
RecursiveIntell/turbo-quant
Rust implementation of TurboQuant, PolarQuant, and QJL — zero-overhead vector quantization for semantic search and KV cache compression (ICLR 2026)
MITAug 22, 2026 · metrics 2.10.0