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modal-labs/GLM-5.3-Flash-DFlash
GLM-5.3-Flash-DFlash is a text generation model from modal-labs. Use it when you need the model to write or continue text. It is set up for transformers. The card lists the license as mit.
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From the Hugging Face model README
This repository contains a DFlash draft model for zai-org/GLM-5.3-Flash. It is not a standalone language model. It is intended to be paired with the target model in a speculative decoding server.
DFlash uses a lightweight block diffusion draft model to propose multiple tokens in parallel. The target model verifies those proposals, improving serving throughput while preserving the target model's output distribution.
GLM-5.3-Flash needs the DFlash capture hooks in the glm5_next model, available on SGLang main. An example deployment is:
python -m sglang.launch_server \
--model-path zai-org/GLM-5.3-Flash \
--tp-size 4 \
--trust-remote-code \
--speculative-algorithm DFLASH \
--speculative-draft-model-path modal-labs/GLM-5.3-Flash-DFlash \
--speculative-dflash-block-size 8 \
--speculative-draft-model-quantization unquant \
--speculative-draft-attention-backend trtllm_mha \
--speculative-draft-kv-cache-dtype fp8_e4m3 \
--host 0.0.0.0 \
--port 30000
Keep the draft model unquantized. Quantizing it lowers the accept length.
Distributed under the MIT License, inherited from the target model.
If you find DFlash useful, please cite the original paper:
@article{chen2026dflash,
title = {{DFlash: Block Diffusion for Flash Speculative Decoding}},
author = {Chen, Jian and Liang, Yesheng and Liu, Zhijian},
journal = {arXiv preprint arXiv:2602.06036},
year = {2026}
}