Unverified50% confidenceFactExact time
The core of the Eagle series of methods is a variant of speculative decoding: a lightweight draft model generates candidate tokens, which are then verified by the target large model.
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10/21/2026
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UnverifiedThe core idea of speculative decoding is: use a smaller draft model to quickly generate multiple candidate tokens, then have the target large model verify in parallel in one pass whether these tokens are acceptable.76% similarUnverifiedTesting the model separately before writing the agent code can confirm whether the underlying model's grounding capability meets the standard and measure the token usage of a single call, providing a baseline for quota planning and cost budgeting.68% similarVerifiedSpeculative decoding submits the candidate sequence generated by the draft model to the target model as a whole for one-shot batch verification, requiring only a single forward pass to determine whether each candidate token is correct.68% similarUnverified朱雀检测工具采用类似生成对抗网络（GAN）判别器的架构，通过人工标注的真人写作与AI生成样本进行有监督训练67% similarUnverifiedSpeculative decoding uses a lightweight draft model to generate candidate tokens that are then verified in parallel by a large model; it is a strictly lossless acceleration method that typically delivers a 2–3× speedup.67% similar
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