Originally published at: Boost Inference Performance up to 15x on NVIDIA Blackwell Using DFlash Speculative Decoding | NVIDIA Technical Blog
As AI systems move from single-turn interactions to coordinated multiagent workflows, low-latency inference becomes increasingly important. Autoregressive LLMs generate tokens sequentially, which can limit GPU utilization and constrain throughput in latency-sensitive serving scenarios. Speculative decoding helps mitigate this bottleneck by using a lightweight model to draft future tokens, which the larger target model then verifies…
Nice work! Appreciate the thorough explanation of DFast and how it improves on previous work on speculative decoding