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incoai/GLM-5.3-Flash-DFlash2

sourceHugging Facecc-by-nc-nd-4.0updated 22d agoView on Hugging Face
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GLM-5.3-Flash-DFlash2

Blog | GitHub

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.

<div align="center"> <img src="assets/dflash2-figure.png" alt="DFlash 2: parallel block drafting with a candidate path selector" width="100%"> </div>

Quick Start

Serve with SGLang:

bash
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:

bibtex
@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:

bibtex
@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}
}