I Built the Same App With Claude Code and Codex

Why It Matters

Teams evaluating AI coding assistants should weigh faster iteration against completeness and project fitness—faster outputs may require more developer polish, while more exhaustive scaffolding can reduce manual setup time. This pragmatic comparison informs purchasing, workflow integration, and cost-of-use decisions for engineering organizations.

Summary

A developer ran a head-to-head build of a real-time collaborative Markdown editor using Claude Code (Opus 4.7) and Codex (GPT‑5.5), testing eight staged prompts from scaffolding through real‑time sync, cursor presence, and persistence. Claude produced a working scaffold faster (about six minutes by the maker’s estimate), while Codex took roughly 14 minutes but generated a more complete and extensive project structure. The tester tracked speed, token/usage costs, adherence to spec, bugs, and code quality and planned cross-review of each model’s output plus a manual engineer review. Early findings highlight a tradeoff between Claude’s speed and Codex’s more thorough scaffolding, with full verdict pending after deeper functional and quality checks.

Original Description

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Claude Code or Codex: Which one is the best for coding? Well, in this video I'm going to answer that question. I'm going to run both Claude and Codex on the exact same set of tasks, and give you my verdict on which one is better. I'll judge both tools across four criteria: speed, cost & usage, the finished result, and the code quality.

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⏳ Timestamps ⏳

00:00 | Overview

00:57 | Prompt/Task

02:38 | Model Settings

04:10 | Boot.dev

05:30 | Build Phase

14:41 | Finished Product

16:57 | Detailed Code Review

23:04 | Final Results

Hashtags

#ClaudeCode #Codex #AIDevTools

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