Speculative decoding accelerates large language model inference by using a smaller, faster draft model to predict multiple tokens, which a larger target model then verifies in parallel. This technique reduces latency for real-time applications like chatbots and code assistants, benefiting developers and users requiring faster, cost-efficient AI responses without sacrificing output quality.
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