README: add credited community adopters to Run It Today table

README.md

@@ -20,6 +20,10 @@ This repository is the **research home**: the Python reference implementation, t
 | [Atlas](https://github.com/Avarok-Cybersecurity/atlas) | Rust, Metal | Integrated | turbo4 KV cache append/decode kernels |
 | [mlxcel](https://github.com/lablup/mlxcel) | Rust, MLX | Community port | [Turbo KV cache docs](https://github.com/lablup/mlxcel/blob/main/docs/turbo-kv-cache.md). Thanks to [@inureyes](https://github.com/inureyes) and the Lablup team for the careful port and upstream attribution |
 | [MLX Python fork](https://github.com/TheTom/mlx/tree/feature/turboquant-plus) | Apple Silicon, Python | Experimental | `TurboKVCache` drop-in for mlx-lm and mlx-vlm; see [docs/mlx-port.md](docs/mlx-port.md) |
+| [turboquant-pytorch](https://github.com/tonbistudio/turboquant-pytorch) | PyTorch | Independent implementation | From-scratch PyTorch TurboQuant for KV cache; applies this repo's layer-adaptive compression and Sparse V findings |
+| [turboquant-vllm](https://github.com/varjoranta/turboquant-vllm) | CUDA, vLLM package | Community package | TQ+ KV cache for vLLM with fused CUDA kernels; builds on this repo's block_size=128 and K-dominance research |
+| [Quansloth](https://github.com/PacifAIst/Quansloth) | Local server product | Community product | Air-gapped local AI server built on the TurboQuant+ stack |
+| [RotorQuant](https://github.com/scrya-com/rotorquant) | llama.cpp | Comparison codec | Block-diagonal rotation alternative; ships `turbo3`/`turbo4` alongside its own formats for side-by-side comparison |
 
 ## Key Findings