Kloss(@kloss_xyz)

My timeline is full of builders testing Jev. At $0.042 per 1M input tokens with output effectively free, it’s insanely cost efficient. I’d bet OpenAI, Anthropic, Google & SpaceXAI are all paying close attention to this.

7.5内容质量

TL;DR · AI 摘要

Jev模型以每百万输入代币0.042美元的超低成本和20-200倍加速性能，引发OpenAI等巨头关注。

核心要点

  • Jev模型输入成本低至$0.042/百万token，输出近乎免费
  • RLCD训练方法使模型速度提升20-200倍
  • OpenAI、Anthropic等公司正在密切跟踪Jev进展

结构提纲

按章节快速跳转。

  1. §引言

    推文揭示Jev模型引发行业关注的核心原因

  2. ·Jev模型性能

    展示输入成本与输出效率的突破性数据

  3. ›RLCD训练方法

    解释新型训练框架带来的速度提升机制

  4. ·行业影响分析

    列举OpenAI等头部公司对Jev的关注背景

思维导图

用一张图看清主题之间的关系。

查看大纲文本（无障碍 / 无 JS 友好）
  • Jev模型突破
    • 成本优势
      • $0.042/百万token
    • 性能提升
      • 20-200倍加速
    • 行业影响
      • OpenAI等巨头关注

金句 / Highlights

值得收藏与分享的关键句。

#AI模型#成本效率#训练方法#AGI
打开原文

klöss on X: "My timeline is full of builders testing Jev. At $0.042 per 1M input tokens with output effectively free, it’s insanely cost efficient. I’d bet OpenAI, Anthropic, Google & SpaceXAI are all paying close attention to this." / X

klöss

@kloss_xyz

My timeline is full of builders testing Jev. At $0.042 per 1M input tokens with output effectively free, it’s insanely cost efficient. I’d bet OpenAI, Anthropic, Google & SpaceXAI are all paying close attention to this.

Diogo Almeida

@CompleteSkeptic

Sep 15

After co-inventing ChatGPT, I kept asking myself: why have superhuman chat models not led to AGI? I’ve spent the last 2 years in stealth building a new way to train models (RLCD), and a new type of frontier AI model that we are releasing today: Jev • 20-200x faster • 40-400x

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1:07 AM · Sep 18, 2026

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