DFlash makes Qwen3.6 27B 2.2x faster with no quality loss

We ran the same Qwen3.6-27B locally three ways on one RTX 6000: baseline, MTP, DFlash. The tasks were: quicksort, write a Steam library in JSON, solve a logic puzzle and write a sci-fi story.

Outputs:

Baseline: 44 tok/s · 1.00x

MTP: 65 tok/s · 1.45x · 71% accepted

DFlash: 98 tok/s · 2.20x · 30% accepted

DFlash drafts 15 tokens in a row, so it flies through repetitive or structured stuff where long runs actually stick, like JSON (152 tok/s, 3.4x). On creative text most of the guesses are wrong, so it wastes the work and can dip below baseline, 42 vs 44. MTP only guesses 3 in parallel from inside the model, so a wrong guess costs almost nothing and it never drops below baseline.

All three have the same output. DFlash is therefore a great pick for stuff like coding, while MTP is better for chat or creative writing.

Qwen 3.6 27B model : https://huggingface.co/Qwen/Qwen3.6-27B
local ai models hosting app: Atomic.Chat (I'm from Atomic team, happy to hear your feedback)