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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]