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Dev tools · June 24, 2024

Bodhi App – Run Open Source/Weights HuggingFace LLMs Locally

Hi HN, I'm excited to share Bodhi App, a tool designed to simplify running open-source Large Language Models (LLMs) locally on your laptops. While we currently support M2 Macs, we plan to support other platforms as our community grows. # Problem To use LLMs, you typically need to purchase a subscription from providers like OpenAI or Anthropic, or use OpenAI API credits with compatible Chat UIs. These options can not only burden you financially, but also raise data security and privacy concerns. Many laptops are capable of running powerful open-source LLMs, but for non-tech users, setting…

Bodhi App – Run Open Source/Weights HuggingFace LLMs Locally launched on June 24, 2024 with 21 votes, #869 of 4,672 launches that month and more than 75% of that year's launches. The site was still online in September 2026, 2 years on.

Visit github.com ↗Alternativestop 19% of June 2024

In plain words

Bodhi App is a tool that enables users to run open-source large language models locally on their laptops, starting with M2 Macs, with plans to expand to other platforms. It provides a simple chat interface designed for non-technical users, allowing them to access LLM capabilities without subscriptions or API costs while keeping data private on their own hardware. The application aims to make advanced language models accessible to everyone by removing technical barriers to local setup.

written from the facts on this page · September 2026

From the sources

Run Open Source/Open Weight LLMs locally with OpenAI compatible APIs - BodhiSearch/BodhiApp

In the maker’s words, at launch

Hi HN, I'm excited to share Bodhi App, a tool designed to simplify running open-source Large Language Models (LLMs) locally on your laptops. While we currently support M2 Macs, we plan to support other platforms as our community grows. # Problem To use LLMs, you typically need to purchase a subscription from…

Does a similar job

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    Hi HN A few folks and I have been working on this project for a couple weeks now. After previously working on the Docker project for a number of years (both on the container runtime and image registry side), the recent rise in open source language models made us think something similar needed to exist for large language models too. While not exactly the same as running linux containers, running LLMs shares quite a few of the same challenges. There are "base layers" (e.g. models like Llama 2), specific configuration to run correctly (parameters, temperature, context window sizes etc). There's…

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