Hacktoberfest Open-Source AI Challenge: Week 4 - DEV Challenge - DEV Community

Challenge 5 of 5 in our Hacktoberfest DEV Challenges. One prompt, a new theme every week.
This year's Hacktoberfest is not about open source pull requests. There's no PR count to hit and no repos to hunt for. Instead, you build a brand-new project with open-source AI at its core, and write about it on DEV. Here's everything you need to know about Hacktoberfest 2026.
Week 4 of our five Hacktoberfest DEV Challenges starts today, and it's our final challenge of the series! Running through October 31, the Hacktoberfest Open-Source AI Challenge: Week 4 gives you the week to build, wrapping up on Halloween night just as Día de los Muertos begins.
Missed Week 3: Slow and Steady? No problem. Every challenge is a fresh start, so you're competing on the same footing as everyone else.
This week, we'll select one overall winner and a winner in each of our 20 partner categories. See all the challenges and current partner categories on the HF26 DEV Challenge Hub.
Free partner credits
Several partners are giving participants credits and promo codes, including Tinker, Render, Backboard, and a free .tech domain. Claim yours at hacktoberfest.com/my/promos.
Ask questions and share your ideas on the Hacktoberfest Open-Source AI Challenge: Week 4 Launch Post.
Build something with open-source AI at its core.
That can mean running an open-weight model, building on an open-source agent harness or framework, running inference locally, or all three. Whatever you pick, the open pieces should be what makes your project work.
In your post, tell us why open innovation matters for what you built. Does it run on a laptop with no internet? Keep someone's data off a server they don't control? Let you fine-tune, swap models, or change how your agent behaves? Cost nothing to run? Tell us where your open-based approach worked better than a closed one.
Build something spooky, or something that honors the past in the spirit of Día de los Muertos, with open-weight models or open-source AI.
This week brings us Halloween on October 31 and Día de los Muertos on November 1 and 2, a stretch of the calendar when the line between past and present feels a little thinner. Whether that brings to mind things that go bump in the night, ofrendas glowing with candlelight and marigolds, or the memories and stories we carry with us, we want to see what it inspires you to build. The theme is intentionally broad, so interpret it however you'd like!
That can mean running an open-weight model, building on an open-source agent harness or framework, running inference locally, or all three. Whatever you pick, the open pieces should be what makes your project work.
A few ideas to get you going:
A haunted terminal that "possesses" your shell and whispers back eerie commentary on the commands you run
A virtual ofrenda builder that helps you write a remembrance for a loved one and gather their favorite foods, songs, and stories
An offline séance chatbot that channels the spirit of a long-dead programming language
A local oral history tool that records and transcribes family stories so they're never lost
A ghost story generator that weaves your smart home's sensor logs into a creepy tale of what happened while you were asleep
A project that brings an abandoned open-source tool or a forgotten corner of internet history back to life
In your post, tell us why open innovation matters for what you built. Does running your own model mean your project works with the lights (and the internet) off? Keep your family's photos and stories private and on your own machine? Make sure what you build isn't locked inside a service that might disappear someday? Tell us where your open-based approach worked better than a closed one.
Show your work. We'd love to see how you built it. Save your agent session with DevRelay and embed it in your post, or link to it. It's optional, but it helps the judges understand your process.
$200 for each winner
Use Render as your project's AI runtime, to host an agent's front end, or to run Hermes or OpenClaw.
Use TabPFN, Prior Labs' tabular foundation model, to forecast, predict, classify, or spot anomalies from historical data like a CSV. Prior Labs strongly recommends the latest version, TabPFN-3.5: it's open-weight and free to use once you sign the non-commercial license at platform.priorlabs.ai, and you can then run it locally. The API adds features like Thinking Mode. Prior Labs favors projects that use TabPFN inside a wider prediction agent (with or without the MCP server).
Use Thinking Machines' Tinker to fine-tune a model for a specific task, and show a clear improvement in performance, latency, or cost over a baseline.
Build with an Arduino UNO Q: run a model on the board, build a physical agent that senses and acts, or optimize a model for it with Qualcomm AI Hub. Open to anyone building with an UNO Q, whether you got one at an in-person Fest or have your own.
Build or deploy your project on DigitalOcean: host your app or agent, run an open-weight model on a GPU Droplet (1-Click Models make this quick), or build an agent on the Gradient AI Platform.
Use Gemma, Google's open-weight model, in building your project: run it locally, fine-tune it, or serve it through Google Cloud or another provider.
$100 for each winner
Use Auth0 for AI Agents: sign users in to an agent, call tools on a user's behalf with Token Vault, ask a person to approve a risky action before the agent takes it, or limit what a RAG pipeline can retrieve with fine-grained authorization.
Build with R-CLI, Backboard's open-source terminal coding agent, compare open-weight models through a single Backboard API key, or give an open-source project's assistant memory and RAG.
Give an open-source agent a voice, transcribe audio for a local model, or generate narration for your demo.
Give your agent a real browser: drive a live site end to end using Stagehand's SDK, pull the context an open-weight model reasons over, or turn a one-off agent run into a repeatable workflow.