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b4rtaz/distributed-llama

Distributed LLM inference. Connect home devices into a powerful cluster to accelerate LLM inference. More devices means faster inference. observed · 2026-10-08

github.com/b4rtaz/distributed-llama · C++ · MIT (permissive) observed · 2026-10-08

Health v2 · maintenance only

74/100

  • Activity 83
  • Release rhythm 61
  • Longevity 75
How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-10-21. Adoption (stars, forks) is never an input.

  • gap_med: 4.0
  • age_days: 1051
  • days_rel: 260
  • days_push: 107
  • n_releases_24m: 39

Full methodology

Adoption not part of the score

3100 stars · 255 forks observed · 2026-10-08

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A C++ application that connects multiple home devices into a cluster for distributed LLM inference using tensor parallelism. It supports Llama, DeepSeek, and Qwen models on CPU (ARM and x86_64 AVX2) and experimentally on GPU via Vulkan.

Use cases

  • run llama 3 70b across multiple mac minis
  • speed up llm inference by pooling home devices
  • serve a large language model on raspberry pi cluster
  • distributed inference of qwen 3 models
  • run deepseek r1 distilled model locally on weak hardware
  • tensor parallel llm inference over ethernet

When to choose

  • you have several networked devices and want to run models too large for any single one
  • you want CPU-only distributed inference without a GPU
  • you want a simple single-command setup for popular open LLMs

When to avoid

  • you have a single powerful GPU that fits the model
  • you need production-grade serving with APIs and batching
  • you need broad model format support beyond supported families

Facets

application · maturity active

llm-inference cli rpc large-language-models microservices artificial-intelligence windows cpp cli tensor-parallelism llama qwen vulkan raspberry-pi cluster-computing cpu-inference linux macos gpu

1 source

Member repositories

RepositoryRoleHealth v2
b4rtaz/distributed-llamamain74

For agents

markdown · JSON · MCP: product_card(name="b4rtaz/distributed-llama")

Data as of 2026-10-19T08:05:51.212177+00:00 · Report a problem