# Laguna S 2.1 以 1/6 参数量匹敌 GLM-5.2

- 来源：Rohan Paul (@rohanpaul_ai)
- 发布时间：2026-07-22 11:24
- AIHOT 分数：40
- AIHOT 链接：https://aihot.virxact.com/items/cmrvjqxrv030ibihb9v95787d
- 原文链接：https://x.com/rohanpaul_ai/status/2079769553844978081

## AI 摘要

Laguna S 2.1（118B 参数）在游戏编程任务中达到与 753B 的 GLM-5.2 同等的质量，参数量仅为后者的 1/6。在构建三款自玩街机游戏时，Laguna S 2.1 仅用 10.3K tokens 完成，而 GLM-5.2 需要 26.4K tokens。Laguna S 2.1 是三者中唯一能在 128GB MacBook 上本地运行的模型。

## 正文

Laguna S 2.1 （118B param） looks so great for intelligence per token.

It matched the 753B GLM-5.2 on game coding with 6x fewer parameters.

Both models faced the same job， alongside a third contender named Hy3.

Test was done on atomic【.】chat， a desktop app that runs LLMs locally.

Each had to build 3 arcade games as self-contained HTML files.

The targets were Geometry Dash， Doodle Jump， and Air Hockey. Every game also had to play itself through a built-in bot. So no human touches the controls once the file opens.

The smaller Laguna S 2.1 produced its solutions using just 10.3K tokens total. GLM-5.2 needed 26.4K tokens to reach roughly the same result.

### 引用推文

> atomic.chat：Laguna S 2.1 performs at GLM-5.2 level on building popular games with 6x fewer params! We gave three local models the same task: build three popular arcade game...