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@no_stp_on_snek: Tested out MTP for the first time on my llamacpp fork last night with turbo4 sym. GX10 hardware. using MoE model: llmfa…

X AI KOLs Following · 2026-05-22 Cached

Tested Multi-Token Prediction on a llamacpp fork with a Qwen-based MoE model, achieving +0.41% PPL improvement over fp16 baseline.

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#ppl

Here are my KV cache quantization benchmarks: TurboQuant is overrated but saved by TCQ, q5 deserves more attention, and symmetric q8 might be a waste of VRAM

Reddit r/LocalLLaMA · 2026-05-19

A detailed benchmark comparing KV cache quantization methods (TurboQuant, TCQ, q4, q5, q8) using PPL and KLD metrics on Qwen 3.6 27B, finding that TCQ improves low-bit quantization, asymmetric KV beats symmetric at same size, and q8 is often overkill. Includes analysis and data in linked article.

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