额度重置 · Sol 用量问题

Sol 的用户们，你们好！我已为所有 ChatGPT Work 和 Codex 用户重置了使用限额。与此同时，简要更新一下 GPT-5.6 Sol 的使用限额情况。 过去几周，许多人告诉我们，Sol 消耗 Codex 限额的速度比预期更快。需要明确的是，我们没有降低任何订阅套餐的用量。 我们一直在调查发生了什么，并已上线多项改进。因此，我们预计在典型使用 Sol 的情况下，你的用量会多持续约 18%。你们中的一些人从今天起应该已经能看到显著更大的提升。明天，我们还将恢复此前在调查期间暂时暂停的五小时限额。 以下是我们发现的情况： - GPT-5.6 Sol 更愿意长时间工作、进行更多工具调用，并跨工具和子代理协调复杂工作流。这使它更擅长解决难题，但某些任务消耗的量远超我们的预期。 - 在相同推理强度下，Sol 也比之前的模型更努力。Sol 上的 High 可能比 GPT-5.5 上的 High 使用更多 token。 - 程序化工具调用（也称为代码模式）让 Sol 在并行运行工具调用或在等待时继续工作方面灵活得多。但它也导致每轮响应更多、缓存输入 token 更多，以及用量高于预期。 - 当 Sol 等待工具调用完成或运行大量网络搜索时，这一点尤其明显。我们已改进对这两种情况的处理，并正在继续

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.