
Speculative Decoding
This is a template for implementing speculative decoding techniques to speed up LLM inference by 1.5 to 3.6 times without losing quality. It covers the main approaches like draft model speculation, Medusa's multiple head method, and Lookahead Decoding based on Jacobi iteration. The skill references recent papers from 2024 and gives you a starting point if you're trying to reduce latency in chatbots or code generation tools, or squeeze better throughput from limited hardware. Worth noting it's ported from ovachiever/droid-tings and sits in a template collection with 27.7K stars, so there's likely other inference optimization patterns in there too. The practical speedup range makes this relevant if you're actually serving models at scale.
- skills.sh installs
- 334
- GitHub stars
- 33.2K
- last updated
- Aug 21, 2026
Install
$ npx -y skills add davila7/claude-code-templates --skill speculative-decoding --agent claude-codeInstalls into .claude/skills of the current project.
Files
This is a template for implementing speculative decoding techniques to speed up LLM inference by 1.5 to 3.6 times without losing quality. It covers the main approaches like draft model speculation, Medusa's multiple head method, and Lookahead Decoding based on Jacobi iteration. The skill references recent papers from 2024 and gives you a starting point if you're trying to reduce latency in chatbots or code generation tools, or squeeze better throughput from limited hardware. Worth noting it's ported from ovachiever/droid-tings and sits in a template collection with 27.7K stars, so there's likely other inference optimization patterns in there too. The practical speedup range makes this relevant if you're actually serving models at scale.
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Details
- Repository
- github.com/davila7/claude-code-templates
- Categories
- AI & Agent Building, Automation & Workflows
- First seen
- Jun 3, 2026
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