# 开源模型网络能力差距缩至4-7个月

- 来源：Rohan Paul (@rohanpaul_ai)
- 发布时间：2026-07-18 07:29
- AIHOT 分数：56
- AIHOT 链接：https://aihot.virxact.com/items/cmrpkp6ct02rsbisr07snp7jk
- 原文链接：https://x.com/rohanpaul_ai/status/2078260807310479695

## AI 摘要

领先开源模型在长周期网络能力上已追近闭源前沿，差距从2025年大部分时间的6-10个月缩至4-7个月。GLM-5.2在长周期网络靶场中匹配了约7个月前发布的Claude Opus 4.5。OpenAI的GPT-5.6 Sol在32步“The Last Ones”靶场中10次尝试完成7次，且性能随推理token增加而提升。

## 正文

On long-horizon cyber capability， leading open-weight models now trail the closed frontier by only 4 to 7 months， down from 6 to 10 months through much of 2025.

GLM-5.2 matched closed models released about 4 months earlier.
On long-horizon cyber ranges， GLM-5.2 matched Claude Opus 4.5， released roughly 7 months earlier.

And also that long-horizon cyber capability can now be scaled with compute.

On the AI Security Institute's 32-step "The Last Ones" range， GPT-5.6 Sol completed the full 32-step range in 7 of 10 attempts.

With a 100M-token budget for each run.

Performance continued improving as the model received more inference tokens. i.e. operators can gain materially stronger cyber capability simply by spending more runtime compute， without retraining the model.

### 引用推文

> OpenAI：GPT-5.6 Sol sets a new state of the art in cybersecurity on "The Last Ones" cyber range. We're already seeing that capability translate into defensive outcomes:...