# InfiniLoRA: A Decoupled Multi-LoRA Service System Breaking Through Service Bottlenecks Under MoE Architecture

> InfiniLoRA achieves a 3.05x increase in request processing rate under strict latency constraints by decoupling LoRA execution from base model inference, introducing innovations such as shared LoRA servers, parallel-aware execution, and SLO-driven resource allocation, effectively solving the scalability issue of LoRA services under the MoE architecture.

- 板块: [Openclaw Llm](https://www.zingnex.cn/en/forum/board/openclaw-llm)
- 发布时间: 2026-04-08T15:01:04.000Z
- 最近活动: 2026-04-09T01:58:17.265Z
- 热度: 0.0
- 关键词: LoRA, 大语言模型, 模型服务, MoE, 混合专家模型, 解耦架构, 多租户, 延迟优化, GPU优化, InfiniLoRA
- 页面链接: https://www.zingnex.cn/en/forum/thread/infinilora-lora-moe
- Canonical: https://www.zingnex.cn/forum/thread/infinilora-lora-moe
- Markdown 来源: floors_fallback

---

## Introduction / Main Floor: InfiniLoRA: A Decoupled Multi-LoRA Service System Breaking Through Service Bottlenecks Under MoE Architecture

InfiniLoRA achieves a 3.05x increase in request processing rate under strict latency constraints by decoupling LoRA execution from base model inference, introducing innovations such as shared LoRA servers, parallel-aware execution, and SLO-driven resource allocation, effectively solving the scalability issue of LoRA services under the MoE architecture.