I’m creating a new topic because the recent discussion “GPT-6 & Astra are far too sanitized. Almost unusable” was automatically closed after 24 hours:
I’m experiencing the same problem, but in my case it is breaking actual production workflows in ChatGPT Work.
I use Work for website administration, development, SEO, metadata generation, moderation configuration, debugging, content analysis, and other multi-step production tasks. Some of the websites contain lawful adult material.
GPT-5.6 Sol was generally able to complete these workflows.
GPT-6 and especially GPT-6.1 Sol increasingly refuse, sanitize, reinterpret, or stop tasks simply because the source website contains sexual material — even when the requested task itself is ordinary technical or editorial work such as:
- SEO titles and descriptions
- metadata
- CMS development
- plugin development
- debugging
- moderation configuration
- content classification
- site administration
- analysis of existing material
This is not about asking the model to ignore safety policies.
The problem is false positives: an allowed production task becomes impossible because the model appears to treat the entire domain or source material as prohibited.
There is also a second major problem with the suggested workaround of switching back to GPT-5.6 Sol.
GPT-5.6 Sol consumes considerably more of the available Work/Codex resources. So, in practice, a Pro user is left with this choice:
- GPT-6.1 Sol: much better usage efficiency, but repeatedly refuses or breaks otherwise allowed workflows.
- GPT-5.6 Sol: can complete the work much more reliably, but consumes the available allowance too quickly for sustained Work usage.
That is not a workable fallback.
GPT-6.1 Sol is specifically positioned as a model for frequent complex Work/Codex tasks. If it cannot reliably distinguish prohibited content from legitimate technical, SEO, administrative, and analytical work involving a website that happens to contain adult material, that defeats the purpose of the model for this use case.
At this point the issue is serious enough that I’m questioning the value of maintaining a Pro subscription.
I would much rather see the false-positive/refusal behavior fixed than receive higher theoretical benchmark performance from a model that stops the workflow.