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prayangshuuu/hummingbird

Analysis updated 2026-07-26

42CAudience · developerComplexity · 4/5Setup · moderate

TLDR

Hummingbird is a free tool that lets you run very large AI models on ordinary computers by treating your disk, RAM, and graphics memory as one combined pool.

Mindmap

mindmap
  root((repo))
    What it does
      Runs large AI models
      Uses storage as memory
      Caches frequent weights
    Supported models
      GPT-OSS 120B
      DeepSeek
      Qwen
      GLM
    Tech stack
      C language
      CMake
      CUDA
      Metal
    Use cases
      One shot text generation
      Interactive chat
      OpenAI compatible server
    Audience
      Developers
      No Python required

Code map

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What do people build with it?

USE CASE 1

Run large AI models locally on a regular computer without expensive hardware.

USE CASE 2

Serve an OpenAI-compatible API from your own machine using the hb command.

USE CASE 3

Embed high-performance AI inference directly into a C application.

USE CASE 4

Chat interactively with massive open-source models offline.

What is it built with?

CCMakeCUDAMetal

How does it compare?

prayangshuuu/hummingbirdpsbrew/micromounttermux/libandroid-support
Stars424241
LanguageCCC
Last pushed2022-12-16
MaintenanceDormant
Setup difficultymoderatehardhard
Complexity4/54/54/5
Audiencedeveloperdeveloperdeveloper

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · moderate Time to first run · 30min

Requires building from source with a C17 compiler and CMake, and choosing a backend like CUDA or Metal for GPU support.

In plain English

Hummingbird is a program written in the C programming language that lets you run very large artificial intelligence models on ordinary computers. Large AI models, some with hundreds of billions of parameters, normally require expensive hardware with enormous amounts of memory. Hummingbird tackles this problem by spreading the model across the storage your computer already has, including your solid state drive, system memory, and graphics card memory. It treats all three as one connected pool. The project is inspired by an earlier project called Colibri, which could run a 744 billion parameter model on a machine with 25 gigabytes of RAM by streaming data from disk. Hummingbird takes a different approach. Instead of being built for one specific model, it is designed as a general framework that can run many different model architectures through a flexible adapter system. It supports models like GPT-OSS 120B, DeepSeek, Qwen, and GLM. The core idea is a memory hierarchy. Weights the model needs for every single token stay resident in fast memory. The much larger pool of expert weights lives on disk and is pulled up only when needed. A learning cache keeps frequently used weights warm, so the engine gets faster with repeated use. Expert weights are read in one large sequential chunk and handed directly to computation kernels without being copied. You can install Hummingbird on Linux or macOS with a single command line script. Alternatively, you can build it from source with a C17 compiler and CMake. There are no third party runtime dependencies, no BLAS, and no Python required. The build system lets you toggle options like a CPU backend, a CUDA backend for NVIDIA GPUs, or a Metal backend for Apple Silicon. The command line tool, called hb, supports one shot text generation, interactive chat mode, and an OpenAI compatible HTTP server. The project is still in an early foundation stage. Inference is currently in development, and upcoming features include a model loader, dynamic batching, and a streaming engine. You can also embed Hummingbird into your own application using its stable C interface.

Copy-paste prompts

Prompt 1
How do I install Hummingbird on macOS and run an interactive chat session with a Qwen model using the hb command?
Prompt 2
Show me how to embed Hummingbird into a C application using its stable interface to generate text from a DeepSeek model.
Prompt 3
What is the difference between the CUDA and Metal backends in Hummingbird, and how do I toggle them when building from source?
Prompt 4
How do I start the OpenAI-compatible HTTP server with Hummingbird and send a chat completion request to it?

Frequently asked questions

What is hummingbird?

Hummingbird is a free tool that lets you run very large AI models on ordinary computers by treating your disk, RAM, and graphics memory as one combined pool.

What language is hummingbird written in?

Mainly C. The stack also includes C, CMake, CUDA.

How hard is hummingbird to set up?

Setup difficulty is rated moderate, with roughly 30min to a first successful run.

Who is hummingbird for?

Mainly developer.

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