I ran a language model on a PS2
The Emotion Engine has 32 MB of RAM total, so the trick is streaming weights from CD-ROM one matrix at a time during the forward pass — only activations, KV cache and embeddings live in RAM. This means models bigger than the RAM can still run, they just read more from disc. Had to build a custom quantized format (PSNT), hack endianness, write a tokenizer pipeline, and most of the PS2 SDK from scratch (releasing that separately). The model itself is also custom — a 10M param Llama-style architecture I trained specifically for this. And it works. On real hardware.
I ran a language model on a PS2 launched on March 21, 2026 with 46 votes, #727 of 23,380 launches that month and more than 95% of that year's launches.
In plain words
A language model implementation that runs on PlayStation 2 hardware despite the console's 32 MB RAM limitation. The project streams model weights from CD-ROM during inference, keeping only activations and embeddings in memory. It includes a custom quantized format, a 10-million parameter Llama-style model trained for the platform, and a rebuilt PS2 SDK. The implementation functions on actual PS2 hardware, enabling AI inference on legacy gaming consoles.
written from the facts on this page · September 2026
From the sources
Running a large language model on a PlayStation 2. Contribute to xaskasdf/ps2-llm development by creating an account on GitHub.
This project started as an experiment born from two passions: retrogaming and LLMs. Having built a complete PS2 SDK from scratch (including tools that had to be rewritten due to incompatibilities with modern software and hardware), and having extensive experience working with language models, the question after seeing a team run an LLM on a Windows 98 PC was simple: "Can I run this on a 26-year-old game console?" The answer is yes. The PS2's Emotion Engine (MIPS-III @ 294 MHz, 32 MB RAM) can run transformer inference by streaming model weights from CD-ROM one matrix at a time, keeping only activations and KV cache in memory. The current default model is brandon-tiny-10m-instruct , a custom…from github.com
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