GLM-5.3-Flash-DFlash2
This repository contains the DFlash 2 draft model for
zai-org/GLM-5.3-Flash.
It is not a standalone language model: it runs inside a speculative
decoding server and drafts tokens for the target model to verify.
DFlash 2 is a block-diffusion drafter for speculative decoding. It predicts a whole block of tokens in a single pass and keeps the top candidates at every position. A lightweight selector then traces one coherent path through them. Two-tap dynamic convolutions in the backbone keep the draft from decaying toward the end of the block. Decoding is lossless: greedy output matches the target model exactly, and sampling preserves its distribution.
Quick Start
Serve with SGLang:
pip install "sglang[all] @ git+https://github.com/sgl-project/sglang.git@refs/pull/36708/head#subdirectory=python"
sglang serve \
--model-path zai-org/GLM-5.3-Flash \
--trust-remote-code \
--speculative-algorithm DFLASH \
--speculative-draft-model-path incoai/GLM-5.3-Flash-DFlash2 \
--speculative-draft-attention-backend fa4
See the blog post for more details.
Evaluation
Benchmark numbers for this checkpoint are being re-measured and will be published here once final.
License
This model is released under CC BY-NC-ND 4.0 for research and evaluation. For commercial licensing, contact contact@inco.ai.
Citation
If you find DFlash 2 useful, please cite:
@misc{inco2026dflash2,
title = {{DFlash 2: Keep Drafting Parallel}},
author = {{Inco AI}},
year = {2026},
month = {August},
url = {https://inco.ai/blog/dflash2/}
}
Please also cite the original DFlash paper:
@inproceedings{chen2026dflash,
title = {{DFlash: Block Diffusion for Flash Speculative Decoding}},
author = {Chen, Jian and Liang, Yesheng and Liu, Zhijian},
booktitle = {International Conference on Machine Learning (ICML)},
year = {2026}
}