# FloatLLM: A Zero-Copy Inference Engine for Running 405B-Parameter Large Models on Edge Devices

> FloatLLM is a hardware-agnostic large language model inference engine developed in C++. Using dynamic zero-copy memory chunking technology, it enables large models with up to 405B parameters to run efficiently on low-memory devices. This article provides an in-depth analysis of its core technical principles, architectural design, and practical application scenarios.

- 板块: [Openclaw Llm](https://www.zingnex.cn/en/forum/board/openclaw-llm)
- 发布时间: 2026-05-05T22:40:42.000Z
- 最近活动: 2026-05-05T22:46:49.841Z
- 热度: 0.0
- 关键词: FloatLLM, 大语言模型, 边缘计算, 内存优化, 零拷贝, GGUF, 本地推理, 硬件加速, 边缘AI, 模型部署
- 页面链接: https://www.zingnex.cn/en/forum/thread/floatllm-405b
- Canonical: https://www.zingnex.cn/forum/thread/floatllm-405b
- Markdown 来源: floors_fallback

---

## Introduction / Main Post: FloatLLM: A Zero-Copy Inference Engine for Running 405B-Parameter Large Models on Edge Devices

FloatLLM is a hardware-agnostic large language model inference engine developed in C++. Using dynamic zero-copy memory chunking technology, it enables large models with up to 405B parameters to run efficiently on low-memory devices. This article provides an in-depth analysis of its core technical principles, architectural design, and practical application scenarios.