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项目能做什么

C 语言编写的 MoE 分层推理引擎,按热度在 GPU、RAM 与 NVMe 间调度专家权重。
来源:基于仓库元数据 · 内容以仓库实际 README 为准

使用说明 查看原始 README 原仓库文档

中文使用说明暂未生成。下面保留原仓库 README 摘录,命令与配置均以原文为准。
原始 README 摘录(英文原文,节选前 3000 字符)
<p align="center">
  <img src="assets/colibri-logo.svg" width="560" alt="colibrì: tiny engine, immense model">
</p>

<p align="center">
  <a href="https://justvugg.github.io/colibri"><img src="https://img.shields.io/badge/website-justvugg.github.io%2Fcolibri-1f6feb" alt="Website"></a>
  <a href="https://github.com/JustVugg/colibri/releases"><img src="https://img.shields.io/github/v/release/JustVugg/colibri?color=2ea043" alt="Latest release"></a>
</p>

<p align="center">
  <a href="https://justvugg.github.io/colibri"><b>Website</b></a> ·
  <a href="https://discord.gg/RXV83nSZdk"><b>Discord</b></a> ·
  English · <a href="README.zh-CN.md">简体中文</a> · <a href="README.zh-TW.md">繁體中文</a> · <a href="README.it.md">Italiano</a> · <a href="README.ja.md">日本語</a> · <a href="README.id.md">Bahasa Indonesia</a> · <a href="README.pt-BR.md">Português (Brasil)</a>
</p>

**Tiny engine, immense model.** colibri runs very large open models on the
machine you already have. A mixture-of-experts model of hundreds of billions of
parameters uses only a small part of itself for each token, so colibri keeps
that part in RAM and reads the rest, the experts, from the disk when the model
asks for them. Pure C, one file per model family, no GPU required.

Thirteen engines run today. Ten are for language models: **GLM-5.2/5.3** (which
also runs **Mistral-Large-4**), **GLM-5.3-Flash**, **Inkling**, **Kimi K3**,
**DeepSeek V4 Flash**, **DeepSeek V4.1 Flash**, **MiMo-V2.6 Flash** (and Pro),
**Qwen3.8-Flash-Next**, **Qwen3.6** (which also runs Qwen3-Coder, the dense
Qwen3.8-27B, **Flint**, **Muse Spark Open** and **LFM3-VL**) and **OLMoE**. One
draws pictures: **Qwen-Image-2.1**. Two answer decisions: **Laya** and
**GLiNER2.5-Decide**, with a third decision model, **Clef**, on the Qwen3.6
engine. The language models also run from the GGUF files already published,
read as they are ([GGUF](docs/gguf.md)), on the CPU, on any GPU through Vulkan
and on NVIDIA cards through CUDA. [Which one for my machine](#which-model-for-my-machine)

```
$ ./coli chat
  colibri v2.1.0 · GLM-5.2 · 744B MoE · int4 · streaming CPU
  ✓ ready in 32s · resident 9.9 GB
  › ciao!
  ◆ Ciao! Come posso aiutarti oggi?
```

<p align="center">
  <a href="https://www.buymeacoffee.com/justvugg"><img src="https://img.buymeacoffee.com/button-api/?text=Buy%20me%20a%20coffee&emoji=&slug=justvugg&button_colour=FFDD00&font_colour=000000&font_family=Poppins&outline_colour=000000&coffee_colour=ffffff" alt="Buy me a coffee" height="40"></a>
  <br>
  <sub>colibri is free and open source. If it has earned a place on your machine, a coffee helps pay for the next engine and the next speedup.</sub>
</p>

<a id="get-started"></a>
<a id="the-one-step-way"></a>

## Get started in one step

You need a computer with **8 GB of RAM** at the very least (16 GB or more is
better), **22 GB free on the disk** for the smallest model, and an internet
connection. A graphics card is optional.

**Windows**

1. On this page click **Code**, then **Dow
阅读完整原文

商业机会分析 规则生成(AI 未配置)

综合评分 41.0 分。该项目在“个人可实施性”维度得 30 分,“付费可能性”维度得 20.0 分,差异化空间 70.0 分(评分依据见评分卡)。

面向细分需求的二次开发产品

产品构想基于 colibri 的核心能力,聚焦一个更窄的场景(如某平台、某行业)做差异化。
目标用户该细分场景用户
难度/周期中 · 2~6 周
收费模式买断制 / 订阅制 / 广告
竞争风险细分需求规模需验证
依据 AI 推测:基于项目主题标签的判断
以上为规则引擎基于仓库公开数据生成的参考结论,包含推测成分,不构成投资或创业承诺;配置 AI 后可获得更深入的分析。
报告会保存到 个人中心

竞品与相似项目 GitHub Search 真实检索

项目中文简介Stars语言
b-ned/dbt-colibri 中文介绍暂未生成
A lightweight Python-based tool for extracting and analyzing
307 HTML
colibri-hq/colibri 中文介绍暂未生成
Colibri is a simple web application to manage, read and down
269 TypeScript
JustVugg/lumabri 中文介绍暂未生成
Run large AI models across your computers and servers. Power
219 C
arcanis/colibrijs 中文介绍暂未生成
Color extractor
157 JavaScript
proycon/colibri-core 中文介绍暂未生成
Colibri core is an NLP tool as well as a C++ and Python libr
136 C++
archseer/colibri.vim 中文介绍暂未生成
A subtle, elegant color scheme for vim.
102 Vim script
以上为通过 GitHub 官方 Search API 检索的相似项目,功能差异与优劣势需进一步人工确认,配置 AI 后可生成对比分析。

项目优势与风险

技术成熟度创建于 ,最近推送 ,发布过 21 个 Release
社区活跃Star 49,995 / Fork 0 / Issue 0(数据支持,可自行核实)
许可证未检测到(需人工确认)
主要风险上游项目方向可能变化;同赛道竞争者较多(见竞品表);热度与需求不完全等价

安装与使用

快速开始(以仓库 README 为准)
git clone https://github.com/JustVugg/colibri.git
cd colibri
# 请阅读仓库 README 获取确切安装步骤(依赖、配置、启动命令)
阅读原仓库文档
术语说明:Docker=应用容器(把程序和依赖打包运行);API Key=调用外部服务的密钥;Git Clone=把仓库代码下载到本地。常见错误:API Key 未配置 / 端口占用 / 数据库连接失败,多数项目在 README 的 Troubleshooting 章节有说明。