# CLM-8B 发布：比 Jev 快 9 倍的 System One 模型

- 来源：elvis (@omarsar0)
- 发布时间：2026-09-24 23:06
- AIHOT 分数：46
- AIHOT 链接：https://aihot.news/items/cmufo5akc07fpro8wkfc467ex
- 原文链接：https://x.com/omarsar0/status/2103139055013646646

## AI 摘要

Contrastive Language Model（CLM）发布，这是一个用对比学习目标训练的 System One 模型，CLM-8B 推理速度最高比 Jev 快 9 倍，在 computer-use、游戏和工具调用任务上性能相当。

## 正文

Pay attention to this new wave of System One models if you are building custom harnesses.

First Jev. Now, Contrastive Language Model (CLM).

CLM is 9x faster than Jev.

CLM seems to be a better verifier than Jev, particularly at long-horizon tasks.

How do Jev and CLM differ?

CLM is contrastive, and Jev is trained with Reinforcement Learning for Calibrated Decisions (RLCD).

Jev receives a situation plus predefined questions, and returns typed decisions with probabilities. CLM embeds the situation and candidate actions, compares their similarity, then ranks or selects the best match.

The point is that there are several ways to attack this problem, which is exciting.

You can see my recent guide on combining System One and System Two models for building custom harnesses. https://academy.dair.ai/resources/jev-decisions-in-a-pi-sdk-harness

### 引用推文

> Jacky Kwok：Introducing Contrastive Language Model (CLM): an ultra-fast System One Model trained with a contrastive learning objective that connects states and actions. CLM...