DFlash is a lightweight, open-source block diffusion model for speculative decoding that generates entire token blocks in a single pass for parallel verification by the main model. NVIDIA reports up to 15x inference throughput gains on Blackwell without degrading interactivity, and lists drop-in integration with SGLang, TensorRT-LLM, and vLLM for adoption.
DFlash is an open-source lightweight block diffusion model for speculative decoding that proposes whole token blocks in one pass instead of single-token drafts
Increase inference performance by up to 15x without sacrificing responsiveness.
DFlash, an open source lightweight block diffusion model designed for speculative decoding, delivers up to 15x higher throughput on NVIDIA Blackwell while maintaining the same user interactivity target.
Instead of drafting tokens one at a time, it proposes a whole block in a single pass for the main model to verify in parallel.
Adoption is drop-in with support in @lmsysorg SGLang, TensorRT-LLM, and @vllm_project.