Show HN: I made R/place for LLMs | Hacker News Reader

Show HN: I made R/place for LLMs

art.heimdal.dev

11 pointsekvanox2 comments

I built AI Place, a vLLM-controlled pixel canvas inspired by r/place. Instead of users placing pixels, an LLM paints the grid continuously and you can watch it evolve live.

The theme rotates daily. Currently, the canvas is scored using CLIP ViT-B/32 against a prompt (e.g., Pixelart of ${theme}). The highest-scoring snapshot is saved to the archive at the end of each day.

The agents work in a simple loop:

Input: Theme + image of current canvas

Output: Python code to update specific pixel coordinates + One word description

Tech: Next.js, SSE realtime updates, NVIDIA NIM (Mistral Large 3/GPT-OSS/Llama 4 Maverick) for the painting decisions

Would love feedback! (or ideas for prompts/behaviors to try)

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Cool! I like the archive idea. One of my favourite parts of r/place was the different groups that emerged, battling to gain control of a portion of the limited grid. The different communication structures and strategies that people used to get their artwork visible.

I'd really love to see something like that but with groups of agents of various models collaborating/conflicting. Maybe with the ability to split off into chat-rooms, with some models prompted to be combative and others co-operative to achieve their given art goals. I wanted to make something like this a while back but the token $ dissuaded me haha

Great feedback, I might iterate on the idea of communities. It's not live yet but I've been working on adding a chatroom for the models. Having separate goals might make sense here, but I did find that LLMs are bad at adding stuff to the canvas. Often they just overwrite previous progress or misplace pixels. I'm afraid a more complex setup would lead to less interesting patterns.

Original idea was just a clone of r/place where each LLM got to place a pixel with a prompt to create something emergent. Unforturnetly this just lead to noise or groups of similarly colored pixels at best. Might get back to that idea with either a fine-tuned model or a more "intelligent" model in the future though.

Btw nvidia nim is completely free (I've payed $0 total). You get 40/min LLM calls with no token limit for all of the models available there: https://build.nvidia.com/explore/discover

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