vllm-qwen35-optimization

Community

PR-driven optimization for Qwen3.5 in vLLM

AuthorBBuf
Version1.0.0
Installs0

System Documentation

What problem does it solve?

This skill provides a structured, PR-backed approach to optimizing Qwen3.5 in vLLM, covering dense and MoE variants, GDN fusion, FP8/NVFP4 quantization, LoRA, Eagle3, and associated runtime changes, so teams can track improvements and reproduce optimizations.

Core Features & Use Cases

  • PR-dossier driven optimization guides for Qwen3.5 in vLLM (dense, MoE, and Eagle3 paths).
  • Porting, validating, and documenting Qwen3.5 configs across vLLM deployments with quantization and LoRA adjustments.
  • Reproducible evidence workflow using PR histories, landed PRs, and runtime surfaces to validate changes.

Quick Start

Use the included guidelines to audit PR diffs and apply Qwen3.5 optimizations to your vLLM setup.

Dependency Matrix

Required Modules

None required

Components

references

💻 Claude Code Installation

Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.

Please help me install this Skill:
Name: vllm-qwen35-optimization
Download link: https://github.com/BBuf/AI-Infra-Auto-Driven-SKILLS/archive/main.zip#vllm-qwen35-optimization

Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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