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NES CPU embedded in Qwen language model weights

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]

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

NES CPU embedded in Qwen language model weights

How we ranked this

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44 / 100
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Newsworthiness bucket
Tool
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]
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Single-source cluster
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model release, product
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High
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Breaking (< 6h)
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COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · frank chu ·

    A working Nintendo lives in 1GB of Qwen weights. I ran it and counted the nonzero ones.

    <h1> A working Nintendo lives in 1GB of Qwen weights. I ran it and counted the nonzero ones. </h1> <p>Today's Show HN is the kind of project that sounds like a joke until you read the mechanism: an NES CPU compiled into the weights of a stock Qwen3.5 model. No training. A compile…