# How Speculative Decoding Can Make LLM Generation 2-3 Times Faster

DevFeed: [How Speculative Decoding Can Make LLM Generation 2-3 Times Faster](<https://devfeed.tech/articles/how-to-make-llms-3x-faster-17992.md>)

Original publisher: [Read original article](<https://blog.bytebytego.com/p/how-to-make-llms-3x-faster>)

Author: ByteByteGo

Published: 2026-08-26T15:30:34Z

Content type: tutorial

Language: en

Sources: [ByteByteGo](<https://devfeed.tech/sources/bytebytego.md>)

Topics: [Large Language Model](<https://devfeed.tech/topics/llm.md>), [text-generation](<https://devfeed.tech/topics/text-generation.md>), [GPU](<https://devfeed.tech/topics/gpu.md>)

Tags: [article](<https://devfeed.tech/tags/article.md>), [data-center](<https://devfeed.tech/tags/data-center.md>), [decoding](<https://devfeed.tech/tags/decoding.md>), [generation](<https://devfeed.tech/tags/generation.md>), [gpu](<https://devfeed.tech/tags/gpu.md>), [how-to](<https://devfeed.tech/tags/how-to.md>), [llms](<https://devfeed.tech/tags/llms.md>), [tokens](<https://devfeed.tech/tags/tokens.md>)

## AI overview

This tutorial explains speculative decoding, in which a smaller model proposes candidate tokens and a larger model evaluates them in a single forward pass. It covers autoregressive generation, GPU utilization, candidate acceptance and rejection, output-quality preservation, acceptance rates, draft sources, and when the technique may stop helping.

## Source excerpt

In this article, we will look at how speculative decoding works.