A project has successfully embedded a functional Nintendo Entertainment System (NES) CPU within the weights of a Qwen3.5 language model. This feat was achieved without any additional training, by compiling the NES CPU's logic directly into the model's parameters, with approximately 98% of the weights being zero. The model, when run, can execute NES instructions and produce outputs identical to a reference CPU, achieving a speed of around 193 tokens per second. AI
IMPACT Demonstrates a novel method for embedding computational logic within LLM weights, potentially impacting future model architectures and applications.
RANK_REASON This is a novel research demonstration of embedding computational logic within LLM weights, rather than a product release or frontier model announcement. [lever_c_demoted from research: ic=1 ai=1.0]
- bfloat16
- dbreunig/nesformer
- Hugging Face
- MOS Technology 6502
- Nintendo
- Nintendo Entertainment System
- NumPy
- Qwen
- Qwen3.5 4B
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