EAGLE drafts from the target model's hidden states. Why does that raise acceptance, and what did EAGLE-3 change?
A one-layer drafter that beats an 8B model on acceptance sounds wrong until you ask what it is reading. The answer prices the EAGLE head on Llama 3.3 70B, explains the feature trick, and names the three changes in EAGLE-3.
Updated Oct 2026 · Worked answers on inference mechanisms, with calculations, implementation details, and follow-up questions.
A one-layer drafter that beats an 8B model on acceptance sounds wrong until you ask what it is reading. The answer prices the EAGLE head on Llama 3.3 70B, explains the feature trick, and names the three changes in EAGLE-3.
At batch 1 the step reads every weight once to produce one token per sequence, so arithmetic intensity sits near 1 FLOP per byte and the tensor cores idle.