OpenAI 承认 Sol 消耗快的问题并修复了，Codex 用户记得用量已重置，续航能多撑近两成。
OpenAI 宣布重置所有 ChatGPT Work 和 Codex 用户的用量限制。针对 GPT-5.6 Sol 消耗速度过快的反馈，团队优化后典型使用续航提升约 18%。明天将恢复此前暂停的 5 小时限制。调查发现 Sol 因更愿长时间工作和多工具调用，导致部分重度用户消耗更快。中位数用户 token 效率良好，长尾场景得到改进。
我操，Codex 又重置了！ 同时他们还说在调查体感上 GPT-5.6 Sol 的消耗速度比较快的问题。 然后在调查期间也会暂停 5 小时限额。
我操，Codex 又重置了！ 同时他们还说在调查体感上 GPT-5.6 Sol 的消耗速度比较快的问题。 然后在调查期间也会暂停 5 小时限额。 Tibo @thsottiaux Hello people of Sol! I've reset usage limits for all ChatGPT Work and Codex users. Together with that, a quick update on GPT-5.6 Sol usage limits. Over the past few weeks, many of you have told us that Sol was using your Codex limits faster than expected. To be clear, we have not reduced usage on any subscription plans. We’ve been digging into what was happening and have landed several improvements. As a result, we expect your usage to last around 18% longer during typical use of Sol. Some of you should already see significantly larger improvements from today. Tomorrow, we’ll also restore the five-hour limit that we temporarily paused while investigating. Here’s what we found: - GPT-5.6 Sol is much more willing to work for longer, make additional tool calls, and coordinate complex workflows across tools and subagents. That makes it better at solving hard problems, but some tasks were using far more than we intended. - Sol also works harder at the same reasoning effort than previous models. High on Sol can use more tokens than High did on GPT-5.5. - Programmatic tool calling, also referred to as code mode, gives Sol much more flexibility to run tool calls in parallel or continue working while waiting. But it also led to more responses per turn, more cached input tokens, and higher usage than expected. - This was particularly noticeable when Sol was waiting for tool calls to finish or running many web searches. We’ve improved how we handle both cases and are continuing to make code mode more efficient. - The impact was also very uneven. The median user actually found Sol quite token efficient, while some power users working on harder tasks saw their usage drain much faster. We were very focused on average and median usage before launch and missed some cases where the long tail could use significantly more usage. Sol is a significant step forward in what Codex can do, but capability and efficiency do not always improve at the same pace, and some issues only become clear once people are using the model at real-world scale. We should have recognized this sooner and been more upfront about it. You keep pushing the frontier and we’ll keep improving efficiency and sharing updates as we go. 🔗 View Quoted Tweet 💬 1 🔄 0 ❤️ 2 👀 659 📊 1 ⚡