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Sponsored by
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z-lab / Kimi-K2.5-DFlash
Model's Last Updated: April 18 2026
text-generation
Introduction of Kimi-K2.5-DFlash
Model Details of Kimi-K2.5-DFlash
Kimi-K2.5-DFlash
DFlash is a novel speculative decoding method that utilizes a lightweight block diffusion model for drafting. It enables efficient, high-quality parallel drafting that pushes the limits of inference speed.
This model is the
drafter
component. It must be used in conjunction with the target model
moonshotai/Kimi-K2.5
. It was trained with a context length of 4096 tokens.
🚀 Quick Start
SGLang
Installation
uv pip install "git+https://github.com/sgl-project/sglang.git@refs/pull/20547/head#subdirectory=python"
Inference
python -m sglang.launch_server \
--model-path moonshotai/Kimi-K2.5 \
--speculative-algorithm DFLASH \
--speculative-draft-model-path z-lab/Kimi-K2.5-DFlash \
--speculative-num-draft-tokens 16 \
--tp-size 8 \
--attention-backend fa3 \
--mem-fraction-static 0.85 \
--trust-remote-code
Note: For long-context or agentic usage, consider adding
--speculative-dflash-draft-window-size WINDOW_SIZEto enable sliding-window attention for the draft model.
vLLM
Please install the latest vLLM from source.
vllm serve moonshotai/Kimi-K2.5 \
--speculative-config '{"method": "dflash", "model": "z-lab/Kimi-K2.5-DFlash", "num_speculative_tokens": 15}' \
--attention-backend flash_attn \
--max-num-batched-tokens 32768
Early Results
- Thinking: enabled
- Max new tokens: 4096
- Block size: 16
- SGLang results. vLLM results might be different.
-
Epoch 0.5
Dataset Accept Length GSM8K N/A Math500 5.2 HumanEval 5.0 MBPP N/A MT-Bench N/A Alpaca N/A
Runs of z-lab Kimi-K2.5-DFlash on huggingface.co
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More Information About Kimi-K2.5-DFlash huggingface.co Model
Url of Kimi-K2.5-DFlash
Kimi-K2.5-DFlash huggingface.co Url
Provider of Kimi-K2.5-DFlash huggingface.co
Other API from z-lab
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