Cursor 2.0

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 AI News: 1x Neo Robot, Extropic TSU, Minimax M2, Cursor 2, and more!
 Matthew Berman· 2025-10-30 20:16
This video is brought to you by Vulture. More on them later. We now have a humanoid robot built for home use available for pre-sale right now.This is 1X's robot, Neo, and it is really the first mass market pre-orderable humanoid robot that we've seen. And their launch video went absolutely viral. Almost 30 million views in less than 24 hours.And yes, I already pre-ordered it. It's going to be available in early 2026. That is right around the corner.Neo is offered at a $20,000 purchase price or $4.99% a mont ...
 老黄亲自站台,英伟达编程神器,Cursor 2.0自研模型狂飙4倍
 3 6 Ke· 2025-10-30 07:33
Cursor迎来重大升级,2.0版本来了! 一直「套壳」的Cursor这次终于发布了首款自研编码模型Composer。 Composer的速度是同等模型的4倍。 Cursor说这是一款专门为低延迟智能编码打造的模型,大部分任务都可以在30秒以内完成。 在Speed一栏,Composer的速度达到了200 Tokens/秒。 【导读】这次不仅发布自研编码模型Composer,还重构了IDE交互逻辑,可以最多8个智能体同时跑,早期测试和开发者都说Cursor 2.0真的太快了。 这次2.0版本还将浏览器嵌入编辑器内,这对于前端开发非常友好。 可以直接选择元素并将DOM信息转发给Cursor。 可以看这个实测,前端开发可以直接在浏览器选定元素,Cursor自动识别对应代码。 这次更新还引入了全新的代码审查功能,更容易查看 Agent 在多个文件中的所有更改,无需在各个文件之间来回切换。 这次一个更大的更新是引入了语音模式(Voice Mode),真就是动嘴编程了。 除了自研模型,Cursor这次重构了交互逻辑,带来了多智能体模式,在单个提示下,可最多并行运行8个智能体。此功能使用git worktrees或远程机器 ...
 Cursor 2.0来了,多agent并行,自研模型30秒跑完多数任务,MXFP8训练
 3 6 Ke· 2025-10-30 04:35
智东西10月30日报道,今天,知名AI编程平台Cursor宣布升级到2.0版本,并推出了Cursor首个自研编程模型Composer,以及用于并行协作多 个Agent的新界面等15项升级。 Composer模型最大的特点就是快。Cursor称,该模型专为在Cursor中进行低延迟的Agentic编程而打造,大多数回合在30秒内即可完成,其速度 达到同等智能模型的4倍,每秒输出的token数已经超过200个。 在Cursor的内部评估中,Composer的智能水平已经超过了最佳的开源编程模型(包括Qwen Coder和GLM 4.6),速度则优于现有的前沿轻量 级模型(包括Claude Haiku 4.5和Gemini Flash 2.5),不过,其智能水平仍然低于GPT-5和Claude Sonnet 4.5。 ▲Composer与前沿开源、闭源模型的智能与速度对比 随着模型Agent能力的不断提升,Cursor的UI也随之升级。Cursor 2.0的UI界面不再以文件为核心,而是围绕Agent进行重新设计,开发者可以 聚焦想要的目标,让不同的Agent分别处理实现细节。 Cursor 2.0现已支持并行运行 ...
 刚刚,Cursor 2.0携自研模型Composer强势登场,不再只做「壳」
 机器之心· 2025-10-30 01:41
机器之心报道 机器之心编辑部 终于,Cursor 还是走上了自己训练大型语言模型的路。 Cursor 2.0 终于来了! 刚刚,Cursor 发布了两项重大更新:首个编码模型 Composer,以及用于并行协作多个智能体的新界面。 此举意义非凡。一直以来,Cursor 虽然广受欢迎,但终究免不了「AI 时代的 VS Code」的帽子,因为它此前只能使用 Claude、GPT 等第三方模型。这既是 Cursor 的起点,也成了它的瓶颈。 Composer 的发布,堪称是 Cursor 打破这个瓶颈的「独立宣言」,这也标志着 Cursor 正式从「AI 外壳」向「AI 原生平台」进化。 自研模型 Composer Composer 是一款前沿模型,虽然智能程度不敌 GPT-5 等最佳前沿模型,但速度确实遥遥领先,达到了同等智能模型的 4 倍。 在基准测试中, Composer 实现了前沿水平的编码智能,同时生成速度达到每秒 250 个 token—— 大约是领先的快速推理模型的两倍,是同类前沿系统的四倍。(注: Cursor 发布的对比将模型分为几个类 别:「最佳开源」(例如, Qwen Coder 、 GLM  ...
 Cursor发布首个编程大模型!代码生成250tokens/秒,强化学习+MoE架构
 量子位· 2025-10-30 01:06
 Core Insights - Cursor has officially released its first in-house coding model, named Composer, as part of the Cursor 2.0 update [1][2] - Composer is reported to complete complex tasks in just 30 seconds, achieving a speed increase of 400% compared to competitors [3][12]   Model Features - The new Cursor 2.0 includes a native browser tool that allows the model to test, debug, and iterate code autonomously until achieving correct results [4] - Voice code generation enables users to convert their thoughts into code without typing [5] - The interface has shifted from a file-centric to an agent-centric model, allowing multiple agents to run simultaneously without interference [6][7]   Performance Metrics - Composer generates code at a speed of 250 tokens per second, which is approximately twice as fast as the current leading models like GPT-5 and Claude Sonnet 4.5 [19][20] - The model demonstrates enhanced reasoning and task generalization capabilities, comparable to mid-tier leading models [21]   Training Methodology - Composer's performance is attributed to reinforcement learning, which allows the model to learn from real programming tasks rather than static datasets [22][26] - The training process involves the model working directly within a complete codebase, utilizing production-level tools to write, test, and debug code [27][28]   Practical Application - Cursor 2.0 is designed to provide a practical AI system that aligns closely with developers' daily workflows, enhancing its usability in real-world scenarios [35][36] - The model has shown emergent behaviors, such as running unit tests and autonomously fixing code format errors [31]   Transparency and Model Origin - There are concerns regarding the transparency of Composer's foundational model, with questions about whether it is based on pre-existing models or entirely self-trained [37][40] - Cursor has previously developed an internal model named Cheetah, which was used for testing speed and system integration [42]





