Qwen3.5 9B DFlash Paper GitHub Blog DFlash is a speculative decoding method that uses a lightweight block diffusion model to draft multiple tokens in parallel, achieving up to 4.4x speedup over autoregressive decoding. This is the drafter model, which must be paired with Qwen/Qwen3.5 9B. Quick Start Installation vLLM: SGLang: Launch Server vLLM: SGLang: Tip: For long context or agentic workloads, add speculative dflash draft window size WINDOW SIZE to enable sliding window attention for the drafter. Usage Benchmark Results Setup: Single NVIDIA B200, SGLang, thinking enabled, max output length 4096. We report end to end throughput, including prefill time. See our GitHub repository for reproduction scripts. Throughput and Speedup DFlash outperforms MTP across all block sizes and concurrency levels, achieving up to 4.4x speedup at concurrency 1. Tokens/sec (speedup vs. autoregressive baseline) Block Size = 16 Task Concurrency AR MTP DFlash : : : : Math500 1 197 379 (1.9x) 808 (4.1x) 8 1472 2569 (1.7x) 5114 (3.5x) 16 2831 4206 (1.5x) 7508 (2.7x) 32 4701 6028 (1.3x) 9286 (2.0x) GSM8K 1 198 342 (1.7x) 697 (3.5x) 8 1470 2331 (1.6x) 4351 (3.0x) 16 2781 3794 (1.4x) 6325 (2.3x) 32 4581 5445…
We use cookies for essential functionality and analytics. You can accept or reject analytics cookies.Cookie policy