I got a real 320×200 Doom E1M1 gameplay frame from a standalone, fixed-weight neural CPU. The run generated 28,699,242 autonomous protocol tokens and took about 2 hours 21 minutes end-to-end. Its cumulative native Metal inference rate was 4,193.5 tokens/sec. The earlier MLX backend measured 501.5 warm tokens/sec. These are different backends and measurement scopes—not a controlled head-to-head comparison. The framebuffer was extracted from neural memory and independently verified against the expected raw pixel hash. A scope clarification: this follows Qwenputer’s core idea of compiling CPU logic into neural weights and recurrent state, but it is a separate standalone Qwen-derived checkpoint—not stock Qwen and not the same model as upstream Qwenputer. Doom’s guest program and data initialize the machine; the neural circuit autonomously executes it. This is not real-time gameplay, and 10,000 TPS remains unmet. Project and evidence: X: https://x.com/YASHWANTHSC/status/2116132140660539549?a=m_t9dDzlCV8d-qLVtII Github: https://github.com/Yashwanth-Chandrakumar/qwenputer-doom Qwenputer: https://github.com/divagr18/qwenputer submitted by /u/SalamanderFickle4315
Originally posted by u/SalamanderFickle4315 on r/ArtificialInteligence
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