"Is Claude Code already obsolete?"
"I heard Codex is the way to go lately."
Both of these are wrong. The correct approach is to use them differently because their areas of expertise vary. In this article, I—someone who uses both Claude Code and Codex extensively—will thoroughly explain how to distinguish between them.
"Claude Code is a bit underwhelming."
"Codex isn't as great as the rumors say."
If you feel this way, it's not because of the tool's performance. It's because you are assigning the wrong tasks to the wrong tool.
Do any of these sound familiar?
- You use Claude Code but have never touched Codex.
- You think they are basically the same thing.
- You want to streamline content creation or tool development with AI but don't know the best tool.
- You searched for "which one is better?" and ended up more confused.
- You think you only need to master one and ignore the other.
If even one of these applies to you, please read on.
*I am currently distributing 55 major bonuses, including the 'Claude Code and Codex Textbook' covering installation to basic operations, on my official LINE. → https://webiz-assist.com/DYu9CAKZMguw
It's a Mistake to Think "Aren't They the Same?"
"Honestly, aren't Claude Code and Codex doing the same thing?"
I get it. I thought so too at first.
Both are AI agents that run locally. Both read and write code and manipulate files. Looking only at the surface, it's natural not to see the difference.
However, when you actually use both in professional work, you realize their "preferred types of work" are completely different. In areas where Claude Code scores a 90, Codex might only score a 60. The reverse is also true. In other words, fighting with only one tool means you're only drawing out 50% of your total potential.
Today, I will discuss 5 criteria for choosing between them and 2 applications for content creation—7 points in total. By the time you finish reading, you should be able to instantly decide, "This task is for Claude Code" and "This one is for Codex."
Criterion 1: Browser and Screen Operation Accuracy
Codex is clearly stronger here.
Codex has plugins for browser operation and what is called "Computer Use." This feature allows it to operate not just browsers but desktop apps in general, even saving files in an editable state automatically.
While Claude Code has similar capabilities, there are many instances where it falls short of Codex in both accuracy and speed.
In my experience, GPT-5.5 has higher screen recognition capabilities, which leads to the difference in screen operation performance.
The judgment is simple: If you want to automate browsers or desktop apps, use Codex. If the work is completed within text-based tasks, either is fine.
Criterion 2: Construction from Scratch
This is Claude Code's specialty.
Claude Code has high autonomy and an incredible ability to generate code from zero. It has the explosive power to launch something that "just works" from a blank slate. For phases where you want to see a prototype as fast as possible, Claude Code is the only choice.
It's not that Codex can't do the same. However, for zero-base construction tasks, Claude Code is more accurate at grasping intent. In the SWE-Bench Pro benchmark, for tasks close to "new implementation," Claude Opus 4.7 scored 64.3%, while GPT-5.5 scored 58.6%.
The judgment is clear: If you want to launch a working product from a blank slate as fast as possible, use Claude Code.
Criterion 3: Fixing Broken Code
Construction and fixing are different skills. Here, Codex takes the lead.
Code generated by Claude Code tends to become redundant from a long-term maintenance perspective. It can become bloated with additive fixes, or fail to solve root causes by playing "whack-a-mole" with errors.
This is where Codex's fixing power shines. In OpenAI's Terminal-Bench 2.0, GPT-5.5 recorded 82.7%, significantly outperforming Claude Opus 4.7's 69.4%. Terminal-Bench is an indicator that measures the "ability to complete tasks automatically as an agent," a practical benchmark including code difference detection and test execution.
The most effective professional workflow is a "relay method": generate a 70-point product with Claude Code, then raise it to 90 points with Codex. For example, generate the initial app code all at once with Claude Code. Then, tell Codex to "reduce redundant processing, pass tests, and minimize API calls." Codex's fixing accuracy is overwhelmingly higher.
By the way, Codex also has a better intuition for reviews, so you can leave everything from review to fixing to Codex.
Criterion 4: Japanese Language Proficiency
Claude Code dominates here.
Claude Opus's Japanese processing capability is top-class among current models. Natural phrasing, context-aware expressions, and nuance reproduction—in every aspect, it produces Japanese a level above GPT-5.5.
For those in content creation, this difference is critically important. X post drafts, note article outlines, and newsletter bodies—in areas where "the quality of Japanese equals the quality of the product," Claude Code wins.
While Codex's writing ability improved significantly with GPT-5.5, it still feels one step behind when compared.
The judgment is clear: If generating Japanese text is the main task, use Claude Code. If code or file manipulation is the main task, use Codex.
Criterion 5: Image Generation Use Cases
This is actually where the difference is most distinct.
Claude Code simply does not have an image generation function.
Codex does.
Since it's a choice between "can" and "cannot," there's no contest.
Codex can integrate with gpt-image-2.0, released in April 2026. This model can accurately render Japanese text within images. According to official OpenAI information, it achieves over 95% character-level accuracy across 12+ languages.
It's no exaggeration to say this instantly overturned the top spot in image generation previously held by NanoBananaPro.
However, it sometimes uses the wrong model for generation, so in those cases, just say "Generate the image using the Image 2.0 model."
The judgment is clear: If you need images or visual materials, Codex is the only choice. If you only need text, Claude Code is fine.
Why is "Selective Use" Necessary?
Let's summarize the five criteria:
- Browser Operation → Codex
- Construction from Scratch → Claude Code
- Code Fixing → Codex
- Japanese Proficiency → Claude Code
- Image Generation → Codex
In short, there is no all-purpose tool. Claude Code excels at the "creativity to produce 70 points from 0," while Codex excels at the "precision to polish 70 points to 90." Only by having both can you complete a workflow from 0 to 90 points.
Next, let's look at specific application examples for each.
Application 1: Mass-Producing Text Content
X posts, note articles, newsletter bodies. Text is the heart of content creation. Use Claude Code primarily here.
For X post drafts, create a knowledge base from past high-performing posts and have it create a post based on "today's theme."
The same applies to long-form content. Have it learn your style and tone from your past content. Collect and analyze successful content from yourself and competitors, then write new themes in your own style based on that.
In both cases, Claude Code's Japanese proficiency shines. Fine-tuning nuances, unifying sentence endings, and generating phrases that resonate with the reader's psychology. If you try the same with GPT-5.5, the Japanese becomes slightly stiff, increasing the manual editing workload.
Application 2: Automating Image and Slide Material Generation
Content creation requires visual materials as well as text. This is where Codex comes in.
Usage is simple. Just instruct Codex to "create an illustration to attach to this post." You can give image generation instructions even while writing code, so the workflow isn't interrupted.
For slide creation, the key is not to generate images immediately. I recommend first brainstorming the overall structure, outline, and message for each page, then generating images for all pages at once.
By the way, using the Computer Use function, you can even do things like "put all these images into Canva" all at once. For people who want to mass-produce seminar materials or study group slides, this feature is a massive time-saver.
Summary
Claude Code is overwhelmingly strong in "0 to 70 creation" and "Japanese quality." Codex is overwhelmingly strong in "70 to 90 precision fixing," "browser operation," and "image generation." Having both and assigning them based on the nature of the task is the current optimal solution.
One word of caution: selective tool use should not become the goal itself. What matters is "what you want to deliver" and "what you want to solve"; AI agents are merely a means to that end. The moment where one gets lost in optimizing the means and loses sight of the goal comes for everyone. Whether you can stop at that moment is the turning point.
Thank you for reading this far.
I usually post the latest AI information and monetization methods using AI on X.
In my pinned post, I am distributing 55 major bonuses, including the Claude Code and Codex textbook, setup, basic operations, and monetization methods. It includes content a step further than this article, so please check it out.
Finally, if you found this article helpful, I would be happy if you let me know your thoughts in a quote post.
