More Qwen3.6-27B MTP success but on dual Mi50s

Running Qwen3.5 / Qwen3.6 with NextN MTP (Multi-Token Prediction) speculative decode in llama.cpp — single RTX 3090 Ti GPU guide

why llama.cpp can’t combine speculative decode methods?

Get faster qwen 3.6 27b

Qwen3.6-27B with MTP grafted on Unsloth UD XL: 2.5x throughput via unmerged llama.cpp PR

2.5x faster inference with Qwen 3.6 27B using MTP - Finally a viable option for local agentic coding - 262k context on 48GB - Fixed chat template - Drop-in OpenAI and Anthropic API endpoints

MTP on strix halo with llama.cpp (PR #22673)

My setup for running Qwen3.6-35B-A3B-UD-Q4_K_M on single RX7900XT (20GB VRAM)

I Ralph-looped Opus overnight. It reduced my local model switching with cold backfilling context of 135k+ on llama.cpp from ~165s -> 5s! TL;DR - USE SLOTS!

Qwen3.6-27B DFlash on a 24GB RTX 5090 Laptop (sm_120) — 80 t/s avg via spiritbuun's buun-llama-cpp + Q8_0 GGUF drafter