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Codex 5.4 vs 5.3: What's Different and When to Upgrade

Cowrie
Cowrie
Dev @ Bswen

I’ve been using Codex for months. When OpenAI released GPT-5.4, I wondered: is this actually better, or just different naming?

After testing both extensively, here’s what I found.

The Core Difference: Surgical Edits

The most striking change isn’t in benchmarks. It’s in how 5.4 modifies code.

Previous models (including 5.3) tend to rewrite large sections when fixing issues. 5.4 High makes minimal, targeted changes:

Before (5.3 and earlier): +148 lines added, -146 lines removed
After (5.4 High):          +2 lines added, -0 lines removed

This matters because smaller diffs are easier to review and carry less risk of introducing new bugs. It feels like working with a senior engineer who understands the codebase, not a junior who rewrites everything.

Model Naming Clarification

First, some confusion I had to clear up:

  • GPT-5.4 is OpenAI’s unified model (what this post is about)
  • GPT-5.3-Codex is the specialist coding model
  • You can use GPT-5.4 through the Codex app, but it’s still a GPT family model

5.4 combines the reasoning capabilities of GPT-5.2 with the coding strengths of GPT-5.3-Codex. It’s OpenAI’s first “mainline reasoning model that combines frontier professional-work quality with frontier coding.”

Benchmarks: The Numbers

+------------------+----------+---------------+----------+
| Metric           | GPT-5.4  | GPT-5.3-Codex | GPT-5.2  |
+------------------+----------+---------------+----------+
| SWE-Bench Pro    | 57.7%    | 56.8%         | 55.6%    |
| Terminal-Bench   | 75.1%    | 77.3%         | 62.2%    |
| Context Window   | 1.05M    | 400K          | 400K     |
+------------------+----------+---------------+----------+

5.4 edges out 5.3-Codex on SWE-Bench Pro (general coding tasks). But 5.3-Codex still leads on Terminal-Bench 2.0 (terminal-heavy operations).

The 1M context window is the other big difference. I’ve loaded entire codebases that would have required chunking with 5.3.

Thinking Mode Selection

5.4 offers multiple thinking levels. Here’s when to use each:

NONE/LOW  -> Simple extraction, formatting, quick fixes
MEDIUM    -> Regular coding, debugging, feature work (default)
HIGH      -> Architecture decisions, refactoring, multi-file changes
XHIGH     -> Multi-hour autonomous workflows, deep research

Important: XHIGH is meant for long-running tasks, not everything. An OpenAI employee confirmed this. Using xhigh on basic tasks leads to overthinking, slower responses, and more issues.

Where 5.3 Still Wins

5.4 isn’t universally better:

  • Terminal/Shell work: Some users report 5.3-Codex is still stronger for terminal-heavy operations
  • Front-end development: Claude Code still has an edge for some frontend workflows

One user with 9 months of Codex experience noted: “From my limited experience (2-3 hours), it is worse in Shell commands than 5.3 Codex (both on high).”

Pricing

+------------+----------------------+-----------------------+---------+
| Model      | Input (per 1M)       | Output (per 1M)       | Context |
+------------+----------------------+-----------------------+---------+
| GPT-5.4    | $2.50                | $15.00                | 1.05M   |
| GPT-5.4Pro | $30.00               | $180.00               | 1.05M   |
| GPT-5.3    | $1.75                | $14.00                | 400K    |
+------------+----------------------+-----------------------+---------+

Note: Context above 272K tokens incurs 2x input / 1.5x output pricing.

Decision Framework

Choose GPT-5.4 when:

  • Your work mixes coding with analysis, docs, and planning
  • You need to handle large codebases or long conversations
  • You want minimal, surgical code changes
  • Your workflow involves browser automation or tool orchestration

Stick with GPT-5.3-Codex when:

  • Your work is primarily terminal/shell-based coding
  • You want the specialist model for pure coding loops

Consider Claude Code when:

  • Front-end development is your primary focus

The Verdict

After using both, I switched to 5.4 for most tasks. The surgical edits alone justify it for my workflow. I’m not constantly reviewing massive diffs wondering what else changed.

But this isn’t a clear-cut upgrade for everyone. If your work is purely terminal-focused, 5.3-Codex might still be the better choice. And the xhigh thinking mode isn’t magic - it’s specifically for long-running autonomous tasks.

The Reddit community called this a “phase change” in model behavior. I agree. It’s not just an incremental bump - it’s a different approach to how the model thinks about engineering problems.

Final Words + More Resources

My intention with this article was to help others share my knowledge and experience. If you want to contact me, you can contact by email: Email me

Here are also the most important links from this article along with some further resources that will help you in this scope:

Oh, and if you found these resources useful, don’t forget to support me by starring the repo on GitHub!

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