vLLM — User Demand Report

Week: 2026-W15 Generated: 2026-04-06 Issues analyzed: 35 (35 included) Need clusters: 1

Top 10 User Needs

Rank	Need	Issues	Score	Category	Examples
1	MoE Performance, Quantization, and Backend Stability Fixes	35	4.5	Performance	#39060, #39030, #39025

Rising Needs

Need	Rising Score	This Week	Category
MoE Performance, Quantization, and Backend Stability Fixes	36.0x	35	Performance

Category Breakdown

Performance: 1 clusters

All Need Clusters

1. MoE Performance, Quantization, and Backend Stability Fixes

Users are reporting critical issues with Mixture of Experts (MoE) model performance including significant decode throughput regressions, quantization-related accuracy problems with new models like Gemma 4 and Qwen3, and CUDA/ROCm backend stability issues causing crashes and hangs. These fixes are essential for running large-scale MoE deployments reliably and efficiently.

Volume: 35 issues (31 open, 4 closed)
Demand Score: 4.5
Avg Reactions: 0.1 | Avg Comments: 1.3
Example issues: #39060, #39030, #39025, #39010, #39004

This report analyzes public GitHub issues only. It represents a signal from public issue discussions, not the full user base.