Speculative Decoding Delivers 3x Speedups in Production vLLM & SGLang

Production benchmarks across vLLM and SGLang confirm that speculative decoding algorithms like EAGLE-3 and DSpark deliver 2.5x to 3.2x latency reductions on structured code and data generation tasks. A small, fast draft model predicts speculative token candidate sequences that the primary foundation model verifies in a single forward pass. Acceptance rates surpass 80% on predictable formats such as JSON, SQL, and Python AST trees.