llamaperf

Qwen3.6 27B

on 2× AMD MI50 32GB · llama.cpp

AMD hardware
May 19, 2026
Quant
Q8_0 (GGUF)
KV cache
Q8
MTP (Multi-Token Prediction)
on
VRAM reported
32 GB

Summary

User benchmarks MTP KV cache quantization at Q8_0 against no quantization on Qwen3.6-27B-Q8_0 with llama.cpp. Setup uses tensor parallelism on 2xMI50 32GB. Wall time difference is negligible at roughly 0.14s with the quantized draft KV cache. Aggregate accept rate is 0.735-0.741.