vllm-qwen35-optimization
CommunityPR-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 requiredComponents
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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