Doom running on an LLM -- Hugging Face checkpoint included

There's no training anywhere in this. I ported Doom's actual rendering algorithm into transformer weights using a compiler I wrote (torchwright) -- every weight computed, none learned.

The prompt carries the level geometry, player position, and view direction; generation emits drawing commands; a 43-line host program turns them into pixels. Stock Phi3ForCausalLM architecture, loads in vanilla transformers with trust_remote_code=False.

Two checkpoints:

- 320x200 (the one in the write-up): 21B params, 85.87 GB. One frame is a 3,614-token prompt plus 53,747 generated tokens -- just under 40 minutes on a B200.
- 80x50: same prompt format, same textures, 34 GB download. This is the one to actually try.

One honest disclaimer:
I have not run this locally -- I've been using cloud GPUs (B200 and A100-80). My compiler currently requires fp32 precision in the weights, and I haven't yet explored quantization.

For the 80x50 model I'd recommend 80 GB of GPU memory; 64 GB should work in theory but I haven't tried it.

Write-up: https://ood.dev/posts/doom/

Weights (80x50): https://huggingface.co/physicsrob/torchwright-doom-e1m1-80x50

Weights (320x200): https://huggingface.co/physicsrob/torchwright-doom-e1m1

Source: https://github.com/physicsrob/torchwright_doom