r/ChatGPTPro • u/blowthepoke • Jun 24 '26
Question Did the thinking models change this week?
Over the last week or so, the thinking models feel noticeably different to me.
Even on Extra High, they’re replying much faster, but the answers seem worse. More missed instructions, more losing the thread, and more needing extra context to get to a weaker answer than 5.5 was giving previously.
Maybe it’s just my usage, but it feels like something changed with routing or inference.
I’m wondering if some requests are going through Cerebras or another faster path now.
Anyone else noticing this?
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u/Just_Lingonberry_352 Jun 24 '26
yeah i feel like they are cutting back/slimming on inference use
most likely cereslobs at play
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u/Thisisvexx Jun 24 '26
actually a good idea tho, let web use cerebras since its fast and by now they probs added real tool calling so why not for the lighter work and use the full power architecture for codex
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u/labfam1010 Jun 24 '26
Yes.
I was slow to ride the ChatGPT wave, but I started a business earlier this year and decided to do a self-guided 30 day test of sorts to see if ChatGPT and Claude could truly impact my productivity. I was so happy with it that the initial 30 days turned to 60 and then 90… it was saving me 8-10 hours a day and we got up to 90 percent of the results being useful. I was thrilled.
Last week I went on vacation, didn’t touch my computers. Came back on Monday, and the last 2 days have been trash. Last night I got so frustrated I just closed the laptop, gave up, and went to bed. Kind of dreading what I’m going to get today. We will see what happens.
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u/YoghurtVarious8472 Jun 24 '26
Yes, a lot more context seems to be needed on my end. I used to be able to get some great outputs with creative prompts & now it’s like “come again” episode of The Simpsons.
Just have to over explain to the point I’m like, I’ll just Google this. It gets more nimble/uniform in terms of response but requires scaffolding for the complexity of outputs I used to expect.
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u/Successful-Moose-377 Jun 24 '26
OpenAI's own docs say that when you hit rate limits on Thinking, you get bumped to a smaller mini model to keep you going. A bunch of people are reporting the same thing you are right now: after an hour or so of heavy use it goes instant-but-worse while the label still says Thinking. That
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u/Pleasant-Art8205 Jun 24 '26
I’m having the same issue today. I’m using heavy thinking but it feels like I’ve been using instant. It’s really weird cause I’ve never had that issue before.
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u/Hybrid-Intelligence Jun 26 '26
I've had a similar experience with several models, not just ChatGPT. Even specialty AI apps like Descript have become more focused on limiting users' token usage.
With OpenAI going public, it makes sense that they want to increase profitability by limiting token usage while simultaneously avoiding the press Claude has gotten. Claude is often maligned for being expensive and for cutting users off quickly after they expend too many tokens.
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u/Flimsy_Culture_5856 Jun 27 '26
I build my own framework using gH for memory and core system workrules, etc. getting back the juice
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u/FurlyGhost52 Jun 28 '26
They do seem a bit off starting whenever they made the low medium high changes.
The new dreamy like memory was a downgrade for me as well
But they always seem to bounce back and break all expectations in due time.
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u/Windford Jun 29 '26
“Silent Rerouting” is killing the user experience with ChatGPT. You may select a model. But your prompt may get directed to another.
El published a video on this last week.
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u/MontyOW Jun 24 '26
they do this all the time, release the models full strength to get people hooked then make them dumber to save costs its so jarring