@zhijianliu_: DFlash for Qwen3.6-35B-A3B just dropped The community was running the day-1 preview before we even finished training. N…
Summary
Z-lab releases DFlash for Qwen3.6-35B-A3B, a model fine-tuning/compression technique, with training complete and weights now available on GitHub and HuggingFace.
Similar Articles
DFlash makes Qwen3.6 27B 2.2x faster with no quality loss
DFlash is a method that accelerates Qwen3.6 27B model inference by 2.2x without quality degradation.
z-lab/Qwen3.6-27B-DFlash
This article introduces Qwen3.6-27B-DFlash, a specialized drafter model for DFlash, a novel speculative decoding method using block diffusion to accelerate inference speed. It provides installation instructions for vLLM and SGLang to enable parallel drafting with the target Qwen3.6-27B model.
z-lab/Qwen3.6-35B-A3B-DFlash
z-lab releases DFlash, a speculative decoding drafter that uses a lightweight block-diffusion model to draft 15–16 tokens in parallel, yielding up to 2.9× speedup for Qwen3.6-35B-A3B inference.
@LottoLabs: This is awesome work Dflash for qwen 3.5/6 series
Charles Frye announces the co-release with Z Lab of six new DFlash speculators for Alibaba Qwen 3.x models, achieving over 1k output tokens per second for Qwen 3.5 122B-A10B on a B200.
@bstnxbt: DFlash v0.1.4 : custom Metal verify kernels for quantized Qwen3 hybrid models, plus significant peak memory reduction a…
DFlash v0.1.4 releases custom Metal verify kernels for quantized Qwen3 hybrid models with significant peak memory reduction and 2.2x throughput improvements at long context on M5 Max GPUs.