Title: GPT-5.6 Sol and Terra: significant regressions in speed, focus, and task completion

I want to share constructive feedback about GPT-5.6 Sol and GPT-5.6 Terra.

Over the last couple of weeks, I have experienced a clear deterioration in both models’ practical performance. Even for general tasks, they often take much longer than expected, while the final output is frequently incomplete, unfocused, or incorrect.

I am an active user of Claude, Codex, Kimi and GLM, so I regularly compare models on the same real-world coding and operational tasks. In several cases, models such as Claude Opus 5 or GLM 5.2 have solved the same problem in a fraction of the time required by Sol in Ultra mode or by Terra. They also reached the correct solution earlier and completed the relevant tests successfully.

The most serious issue appears when using /goal. The models can enter long loops of auditing and re-auditing instead of making progress. In one case, I consumed an entire week’s credit on a single prompt that ran for roughly 12 hours. The result was still wrong, and I had to redo the task with GLM 5.2.

The recurring problems I see are:

• Incorrect or incomplete output.

• Failure to follow instructions precisely.

• Major deviation from the stated goal.

• Excessive slowness and repeated errors.

• Excessive auditing or deliberation loops instead of execution and validation.

I have been a strong OpenAI supporter because its models have historically been one or two steps ahead in my workflow. That is why this feedback is disappointing rather than hostile: I genuinely want OpenAI to regain that practical advantage.

What I need from future iterations is simple: models that are effective, concise, focused on the requested goal, capable of validating their work, and able to stop reasoning when the evidence is sufficient instead of entering loops.

I do not expect a personal response. I would simply appreciate this feedback being read and considered by the product team. Thank you.