Distributed Llama

Distributed Llama: Software tool that connects multiple consumer devices into a cluster to execute distributed LLM inference.

Distributed Llama is an open-source software project that accelerates large language model inference by connecting multiple consumer devices over Ethernet. The system utilizes tensor parallelism and high-speed synchronization to split both the RAM usage and the neural network processing across a root node and multiple worker nodes. Users can run models such as Llama 3.1, Llama 3.2, Llama 3.3, DeepSeek R1, and Qwen 3 on Linux, macOS, and Windows operating systems. The software includes commands for running inferences, command-line chats, worker nodes, and an API server. It is designed for developers and hardware enthusiasts who want to run large models locally by pooling the resources of multiple computers, Raspberry Pis, or GPUs.

Distributed Llama at a glance

Best for: Software engineer
Runs on: Linux, macOS, Windows, CLI, API, self-hosted, open source
Pricing: Free under the MIT license
Released: December 2023
Category: AI coding tool
Website: github.com/b4rtaz/distributed-llama

Key features

Connects multiple devices into an inference cluster
Uses tensor parallelism over Ethernet
Splits RAM usage across all nodes
Supports Llama and Qwen model families
Provides a command-line chat interface
Includes an API server for applications
Runs on Linux, macOS, and Windows

Use it for

Running large language models locally on multiple low-spec devices
Benchmarking local LLM inference performance
Hosting a local API server for language models
Executing command-line chat sessions with custom models

Alternatives to Distributed Llama

Llama Windows — It runs open models offline with zero configuration.
llm-d — Deploys production-grade LLM serving on existing hardware clusters.
LMDeploy — Accelerates inference with high-performance engines and quantization tools.
LLamaSharp — Runs large language models efficiently on local hardware using C#.
Mesh LLM — Run large local models across multiple machines through one OpenAI-compatible endpoint.
WebLLM — Runs high-performance language models directly inside web browsers.
LlamaIndex — It provides hosted APIs for parsing documents and extracting typed data with one API key.
AirLLM — Runs massive 70B+ parameter models on small 4GB consumer GPUs.
LlamaCoder — Generates functional applications directly from text descriptions.
llama-swap — It runs multiple local AI models with zero external dependencies.
OpenLLM — It simplifies infrastructure management and optimizes inference speed and cost.
LlamaFactory — Provides a code-free CLI and Web UI for training 100+ different LLMs.

All Distributed Llama alternatives