LostRuins/koboldcpp 源码下载_部署教程

项目概述

Run GGUF models easily with a KoboldAI UI. One File. Zero Install.

项目地址

https://github.com/LostRuins/koboldcpp

项目页面预览

LostRuins/koboldcpp preview

关键指标

Stars：9248
主要语言：C++
License：GNU Affero General Public License v3.0
最近更新：2026-01-13T15:31:16Z
默认分支：concedo

本站高速下载（国内可用）

源码压缩包下载：点击下载（本站镜像）
SHA256：0d440dcaafe2f2e0ed7abc55727a2153889124dfd3507e6ae09c832cefb4f8ad

安装部署要点（README 精选）

Windows Usage (Precompiled Binary, Recommended)

Windows binaries are provided in the form of koboldcpp.exe, which is a pyinstaller wrapper containing all necessary files. Download the latest koboldcpp.exe release here
To run, simply execute koboldcpp.exe.
Launching with no command line arguments displays a GUI containing a subset of configurable settings. Generally you dont have to change much besides the Presets and GPU Layers. Read the --help for more info about each settings.
Obtain and load a GGUF model. See here
By default, you can connect to http://localhost:5001
You can also run it using the command line. For info, please check koboldcpp.exe --help

Linux Usage (Precompiled Binary, Recommended)

On modern Linux systems, you should download the koboldcpp-linux-x64 prebuilt PyInstaller binary on the releases page. Simply download and run the binary (You may have to chmod +x it first). If you have an older device, you can also try the koboldcpp-linux-x64-oldpc instead for greatest compatibility.

Alternatively, you can also install koboldcpp to the current directory by running the following terminal command:

curl -fLo koboldcpp https://github.com/LostRuins/koboldcpp/releases/latest/download/koboldcpp-linux-x64-oldpc && chmod +x koboldcpp

After running this command you can launch Koboldcpp from the current directory using ./koboldcpp in the terminal (for CLI usage, run with --help).
Finally, obtain and load a GGUF model. See here

Run on Colab

KoboldCpp now has an official Colab GPU Notebook! This is an easy way to get started without installing anything in a minute or two. Try it here!.
Note that KoboldCpp is not responsible for your usage of this Colab Notebook, you should ensure that your own usage complies with Google Colab’s terms of use.

Run on RunPod

KoboldCpp can now be used on RunPod cloud GPUs! This is an easy way to get started without installing anything in a minute or two, and is very scalable, capable of running 70B+ models at afforable cost. Try our RunPod image here!.

常用命令（从 README 提取）

curl -fLo koboldcpp https://github.com/LostRuins/koboldcpp/releases/latest/download/koboldcpp-linux-x64-oldpc && chmod +x koboldcpp

./koboldcpp.sh # This launches the GUI for easy configuration and launching (X11 required).
./koboldcpp.sh --help # List all available terminal commands for using Koboldcpp, you can use koboldcpp.sh the same way as our python script and binaries.
./koboldcpp.sh rebuild # Automatically generates a new conda runtime and compiles a fresh copy of the libraries. Do this after updating Koboldcpp to keep everything functional.
./koboldcpp.sh dist # Generate your own precompiled binary (Due to the nature of Linux compiling these will only work on distributions equal or newer than your own.)

curl -sSL https://raw.githubusercontent.com/LostRuins/koboldcpp/concedo/android_install.sh | sh