Join us for a full day of building with open-source AI. This Hacktoberfest 2026 Hack Day brings students, developers, and open-source enthusiasts together to explore open-weight models, open-source tools, and hands-on hacking.
Whether you're writing your first line of code or you're an experienced developer, there's a place for you here. No prior AI experience needed.
Your laptop, charger, and a GitHub account. Bring your curiosity too, you don't need to be an AI expert to take part.
Come build, learn, and celebrate open source with us. Happy hacking!
Sponsors
Proudly supported by CodeCrafters. Winning teams receive CodeCrafters VIP memberships (1st place: 2-year VIP, 2nd place: 1-year VIP, 3rd place: 6-month VIP), giving full access to all CodeCrafters challenges including Git, Redis, and SQLite.
Also supported by n8n, the open-source workflow automation tool. Every participant gets a voucher for one month of n8n, redeemable until one week after the event. The team that wins the "Best Use of n8n" challenge receives one year of n8n Cloud Pro for every team member.
Locations have different requirements for who can attend. This location is open to the following:
| Time | Activity |
|---|---|
| 11:15 | Check-In |
| 11:30 – 12:00 | Welcome & Orientation |
| 12:00 | Hacking starts! |
| 13:30 – 14:00 | Lunch break |
| 16:45 | Hacking ends |
| 16:45 – 17:00 | Final submission |
| 17:00 | Presentations start |
| 18:00 | Judging time |
| 18:30 | Prize ceremony |
| 19:00 | End of event |
A simple introduction to the difference between closed AI, open-weight models, and genuinely open-source AI.
The official Open Source Initiative definition of what an AI system needs to provide to qualify as open source.
An overview of the benefits, risks, and broader implications of releasing powerful AI models openly.
Open link →The easiest way to download and run open-weight language models locally on your own computer.
Open link →A practical introduction to using pretrained open models for text, vision, audio, and other AI tasks with Python.
Open link →A popular open-source project for efficiently running LLMs locally, including on consumer laptops and CPUs.
Open link →Learn how to customize and fine-tune large models efficiently without retraining the entire model.
Open link →A guide to documenting a model's purpose, training, limitations, datasets, and evaluation results.
Open link →Explains how AI model licenses work and why downloadable weights do not automatically mean unrestricted use.
Open link →Research measuring how transparent major AI developers are about training data, models, evaluation, and deployment.
Open link →Follow the guide given below Redeem code: 2026-COMMUNITY-HACKATHON-BERLIN-5E53612B
START HERE IF NEW! An example project using python to get you started with Ollama and a local gemma4.
Open link →