Qwen3.5 4B 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 3.7x speedup over autoregressive decoding. This is the drafter model, which must be paired with Qwen/Qwen3.5 4B. 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 3.7x speedup at concurrency 1. Tokens/sec (speedup vs. autoregressive baseline) Block Size = 16 Task Concurrency AR MTP DFlash : : : : : Math500 1 274 458 (1.7x) 959 (3.5x) 8 1971 3032 (1.5x) 5851 (3.0x) 16 3663 4827 (1.3x) 8563 (2.3x) 32 5836 6873 (1.2x) 10713 (1.8x) GSM8K 1 271 432 (1.6x) 840 (3.1x) 8 1939 2778 (1.4x) 4945 (2.6x) 16 3599 4388 (1.2x) 7103 (2.0x) 32 5655 62…
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