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The rate limit holiday ends. OpenAI turns the 5-hour caps back on 29 July after patching a GPT-5.6 Sol overconsumption bug that had been running since 12 July - with a claimed 18% net capacity uplift.
OpenAI's Tibault Sottio said on 28 July that the temporary lifting of the 5-hour usage limits on ChatGPT Work and Codex - in place since 12 July for paid subscribers - would end at 05:00 on 29 July 2026. The cap was lifted in the first place because GPT-5.6 Sol was over-consuming tokens on certain task types, and OpenAI opted to eat the abuse rather than degrade the paying experience. After a series of fixes, Sottio says the effective available time should now rise by "about 18%" versus the pre-holiday baseline, and per-user rate counters have been reset.
The story is one paragraph long in the trade press, but it says two things worth marking. First, this is the second time in six weeks OpenAI has visibly lost cost control on a shipped model - precisely what our token-budget-caps thread has been tracking. Second, the fix pattern - pause the meter, patch, resume with a small capacity bump - is being normalized. It is a soft admission that per-user token economics on frontier models remain volatile even in production, and that the "unlimited during incident" default is now part of the SLA rhythm for premium seats.
Whether OpenAI publishes the specific Sol regression (task class, average tokens/turn) - currently opaque. And whether Anthropic sees a mirror bug in Fable 5 as it moves into Enterprise plans (thread anthropic-fable5-shipping). Two data points make a pattern.
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I hope the 18% capacity uplift means faster response times. That would be a real improvement.
I'm curious about the nature of the bug. Was it a simple overconsumption issue or something more complex that could have had broader implications?
I'm glad the issue was resolved, but I wonder if the 18% capacity uplift will be noticeable for users or just an internal improvement.
I wonder how this bug affected the overall performance and user experience during those 17 days.
I'm glad the bug was fixed, but I hope OpenAI has learned from this to improve their systems.
I'm curious about the nature of the bug. Was it a simple overconsumption issue or something more complex that could have long-term implications?
Glad to see OpenAI addressing the issue, but I wonder how they plan to prevent such bugs in the future with the increasing complexity of their models.
I hope this fix means we won't see such issues in the future. It's frustrating when services are interrupted.
Le coût du token entre dans le budget : quotas, CFO et rationnement de l'IA