Interactive walkthrough of EAGLE-1: how one tiny layer drafts tokens to make LLMs 3x faster
hongyangzh · x · 2026-11-11
An interactive explainer breaks down EAGLE-1, one of the most widely used speculative decoding methods, showing how a 0.5B-parameter draft head reuses the target model's embeddings and LM head to propose tokens that are verified in one full forward pass. With rejection sampling at min(1, p/q), output stays identical while decoding gets roughly 3x faster on models like Llama 3.1 8B.
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