GPT-5.4 vs Claude Opus 4.6 — An Honest Comparison After Using Both for a Month

Rick G. — Thu, 19 Mar 2026 19:45:03 +0000

I've been using GPT-5.4 and Claude Opus 4.6 daily for the past month across real projects. Not benchmarks — actual production code, debugging sessions, and architecture decisions. Here's what I found.

Context Window: GPT-5.4 Wins on Paper

GPT-5.4's 1M token context sounds incredible. In practice, I rarely needed more than 200K. But when I did — feeding it an entire codebase for a migration — GPT handled it without quality degradation. Claude starts losing coherence around 400K in my experience.

Code Quality: Claude Wins

For complex refactors and multi-file changes, Claude consistently produced better code. It understood architectural patterns, maintained consistency across files, and caught edge cases GPT missed.

GPT was faster for boilerplate and simple implementations. If I need a quick utility function, GPT-5.4 is 2x faster.

Debugging: Claude Wins (Significantly)

When I paste a stack trace and 500 lines of context, Claude finds the bug in one shot about 70% of the time. GPT-5.4 gets there eventually but often suggests 2-3 things to try first.

Claude seems to "understand" code flow better. It'll say "the issue is in line 247 where you're awaiting a non-async function" rather than "here are 5 possible causes."

Cost: GPT-5.4 Wins

GPT-5.4 is roughly 40% cheaper per token for equivalent quality tasks. For high-volume, lower-complexity work (generating tests, writing docs, simple CRUD), the cost difference adds up.

My Recommendation

Use both. Seriously. I use GPT-5.4 for:

Quick completions and boilerplate
Data transformation scripts
First-draft documentation

I use Claude Opus 4.6 for:

Complex debugging
Architecture decisions
Code review
Anything touching multiple files

The "which AI is better" debate is wrong. The right question is "which AI for which task."