Show HN: Z80-μLM, a 'Conversational AI' That Fits in 40KB
Published:Dec 29, 2025 05:41
•1 min read
•Hacker News
Analysis
This is a fascinating project demonstrating the extreme limits of language model compression and execution on very limited hardware. The author successfully created a character-level language model that fits within 40KB and runs on a Z80 processor. The key innovations include 2-bit quantization, trigram hashing, and quantization-aware training. The project highlights the trade-offs involved in creating AI models for resource-constrained environments. While the model's capabilities are limited, it serves as a compelling proof-of-concept and a testament to the ingenuity of the developer. It also raises interesting questions about the potential for AI in embedded systems and legacy hardware. The use of Claude API for data generation is also noteworthy.
Key Takeaways
- •Demonstrates language model compression techniques.
- •Highlights the challenges of running AI on limited hardware.
- •Showcases innovative solutions like quantization-aware training.
Reference
“The extreme constraints nerd-sniped me and forced interesting trade-offs: trigram hashing (typo-tolerant, loses word order), 16-bit integer math, and some careful massaging of the training data meant I could keep the examples 'interesting'.”