Z80-μLM, a 'Conversational AI' That Fits in 40KB
How small can a language model be while still doing something useful? I wanted to find out, and had some spare time over the holidays. Z80-μLM is a character-level language model with 2-bit quantized weights ({-2,-1,0,+1}) that runs on a Z80 with 64KB RAM. The entire thing: inference, weights, chat UI, it all fits in a 40KB .COM file that you can run in a CP/M emulator and hopefully even real hardware! It won't write your emails, but it can be trained to play a stripped down version of 20 Questions, and is sometimes able to maintain the illusion of having simple but terse conversations…
Z80-μLM, a 'Conversational AI' That Fits in 40KB launched on December 29, 2025 with 514 votes, #15 of 11,628 launches that month and more than 99% of that year's launches.
In plain words
Z80-μLM is a character-level language model compressed into a 40KB file that runs on a Z80 processor with 64KB RAM, executable in CP/M emulators or on vintage hardware. It uses 2-bit quantized weights and integer math to enable conversational AI on severely constrained systems. The model can be trained for simple games like 20 Questions and maintain brief, personality-driven conversations, though it is not designed for complex tasks like email writing.
written from the facts on this page · September 2026
From the sources
Z80-μLM is a 2-bit quantized language model small enough to run on an 8-bit Z80 processor. Train conversational models in Python, export them as CP/M .COM binaries, and chat with your vintage computer. - HarryR/z80ai
Z80-μLM is a 'conversational AI' that generates short character-by-character sequences, with quantization-aware training (QAT) to run on a Z80 processor with 64kb of ram. The root behind this project was the question: how small can we go while still having personality, and can it be trained or fine-tuned easily? With easy self-hosted distribution? The answer is Yes! And a 40kb .com binary (including inference, weights & a chat-style UI) running on a 4MHz processor from 1976. It won't pass the Turing test, but it might make you smile at the green screen. For insight on how to best train your own model, see TRAINING.md . A conversational chatbot trained on casual Q&A pairs. Responds to…from github.com
In the maker’s words, at launch
How small can a language model be while still doing something useful? I wanted to find out, and had some spare time over the holidays. Z80-μLM is a character-level language model with 2-bit quantized weights ({-2,-1,0,+1}) that runs on a Z80 with 64KB RAM. The entire thing: inference, weights, chat UI, it all fits in…
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