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AI · February 26, 2026

Codex builds a working NES Emulator in one hour

Hi folks! I know NES emulators have been implemented countless times, in practically every language imaginable. However, having an LLM fully replicate the spec purely from memory—without referencing existing code—is still a significant challenge. It requires the underlying model to have strong anti-hallucination capabilities and solid long-term planning to keep from going astray. Because of this, building an NES emulator makes for an excellent LLM stress test. Here is how the emulator was built: Data Gathering: I asked Codex to download the necessary developer manuals and test suites. It was…

Codex builds a working NES Emulator in one hour launched on February 26, 2026 with 6 votes, #1,572 of 16,627 launches that month and more than 75% of that year's launches.

Visit github.com ↗Alternativestop 9% of February 2026

What it does

Vibe coded NES emulator by Codex, few shots. Contribute to kaonashi-tyc/codex-nes-emulator development by creating an account on GitHub.

This repository contains a from-scratch Python NES emulator implementation guided by NESDoc.pdf . This emulator was built mostly from scratch with the Codex app (GPT 5.3 Codex, xhigh). I asked Codex to find test suites and developer documentation (including NESDoc.pdf ) and save them locally. Codex was explicitly told not to look at other emulator implementations. Codex iterated on the emulator until the test suites passed. This took multiple prompts, but most of them were simply “continue”. The first Python implementation was too slow, so with some manual guidance I profiled it (flamegraph) and asked Codex to rewrite the PPU in Cython using pre-allocation to speed up rendering. The whole…from github.com

In the maker’s words, at launch

Hi folks! I know NES emulators have been implemented countless times, in practically every language imaginable. However, having an LLM fully replicate the spec purely from memory—without referencing existing code—is still a significant challenge. It requires the underlying model to have strong anti-hallucination…

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