I’m asking this as someone who already uses these systems heavily and knows how much results depend on how you prompt, steer, scope, and iterate.

I’m not looking for “X feels smarter” or “Y writes nicer.” I want input from people who have actually spent enough time with both GPT-5.4 and Claude Opus 4.6 to notice stable differences.

Where does each one actually pull ahead when you use them properly?

The stuff I care about most:

reasoning under tight constraints

instruction fidelity

coding / debugging

long-context reliability

drift across long sessions

hallucination behavior

verbosity vs actual signal

how they behave when the prompt is technical, narrow, or unforgiving

I keep seeing strong claims about Claude, enough that I’m considering switching. But I also keep hearing that usage gets burned much faster in practice, which matters.

So setting token burn aside for a second: if you put both models side by side in the hands of someone who knows what they’re doing, where does GPT-5.4 win, where does Opus 4.6 win, and how big is the gap in real use?

Mainly interested in replies from people with real side-by-side experience, not a few casual prompts and first impressions.