# 模型性能随计算量持续提升未见瓶颈

- 来源：Noam Brown (@polynoamial)
- 发布时间：2026-05-01 00:07
- AIHOT 分数：46
- AIHOT 链接：https://aihot.virxact.com/items/cmolop11v0147sll9e6i2b7zi
- 原文链接：https://x.com/polynoamial/status/2049883449327243413

## AI 摘要

在1亿个标记之后，性能仍在持续提升。我们在这里看到的并非能力上限。

报告指出："TLO上的性能随着推理计算量的增加而持续扩展，我们尚未在最佳模型中观察到性能平台期。"

[引用 @AISecurityInst]：OpenAI的GPT-5.5是第二个端到端完成我们多步骤网络攻击模拟的模型🧵

## 正文

After 100 million tokens， performance was still going up. What we're seeing here is not the capability ceiling.

From the report： "Performance on TLO continues to scale with the amount of inference compute spent， and we have not yet observed a plateau with the best models."

### 引用推文

> AI Security Institute：OpenAI's GPT-5.5 is the second model to complete one of our multi-step cyber-attack simulations end-to-end 🧵