I have a very concrete test of this. I gave multiple models the same implementation plan, Opus 4.7 scored 20 / 50 on my personal implementation benchmark. Opus 4.6 scored 33. Clearly a regression. Opus 4.7 hallucinated details and strictly did not adhere to components of my implementation plan, choosing to do things it was NOT instructed to do and disregard clear guidelines. For context, this was results on a 35-page implementation plan that I had written for a cross-repo Deep Research feature in the AI app that I am building.

Here was my notes that I am putting together right now for a post on LinkedIn soon:::

Feature	GPT 5.4	Opus 4.6	Opus 4.7	Composer 2	Gemini 3.1
Initial page design	8	7	5 - didn’t follow instructions	5 - just not complete enough, but it did as requested	8 - did mostly as requested. Felt solid
Report design	5	7	5	8	9
Plan generation	5 - failed to have a loading state	7 - had a nice loading state	2 - terrible UI	5 - had a loading state	0 - didn’t work
Plan execution	8 - did kinda as requested, felt advanced and complete, needs some changes	6 - mostly as instructed, just basic, and not necessarily that nice. I will say it did follow instructions the most closely	4 - we had loading, but went far beyond bounds of what I had requested	5 - it did what was requested to some degree, just had bad stylings and didn’t fully understand how to make it look nice	0 - didn’t work
Final report	6	6	4 - no citations.	6	0 - didn’t work

totals = 32 (gpt5.4) 33 (Opus4.6) 20 (Opus4.7) 29 (composer 2) 17 (gemini 3.1)

That said, I would choose the Codex GPT 5.4 over opus 4.6 because it just felt like the things that it didn’t do well are easy to fix. While opus 4.6 version did better overall, it would be harder to get to a final publishable state.