同时，Cognition 称，得益于与推理服务提供商 Cerebras 的合作，SWE-1.5 的运行速度最高可达 Anthropic 旗下 Sonnet 4.5 模型的 13 倍。 比 Sonnet 4.5 快 13 倍，编码性能近 SOTA "开发者不应在'思考速度快'与'思考质量高'的人工智能之间做选择。"Cognition 在官方声明中表示，这一理念是 SWE-1.5 的设计基础。 据介绍，SWE-1.5 经过专门设计，是一款拥有数千亿参数的前沿规模模型，旨在打破上述权衡困境的同时提供顶尖性能与一流速度。而该模型最显著的特 点是其原始速度，这一优势源于与推理领域专业机构 Cerebras 的深度合作：共同部署并优化 SWE-1.5。具体举措包括训练一个经过优化的草稿模型以实现 更快的投机解码以及构建定制化请求优先级系统，让端到端智能体交互过程更流畅。 Cognition 表示，此次合作让 SWE-1.5 实现了极佳的延迟表现，并"还树立了新的速度标准"，使其处理速度最高可达 950 token / 秒，分别是 Haiku 4.5 模型 的 6 倍、Sonnet 4.5 模型的 13 倍。"这一性能飞跃 ...

Core Insights - Cognition has launched its new high-speed AI coding model SWE-1.5, designed for high performance and speed in software engineering tasks, now available in the Windsurf code editor [2][3] - SWE-1.5 operates at a speed of up to 950 tokens per second, making it 13 times faster than Anthropic's Sonnet 4.5 model, and significantly improving task completion times [3][4][6] Performance and Features - SWE-1.5 is built on a model with hundreds of billions of parameters, aiming to provide top-tier performance without compromising speed [3][4] - The model's speed advantage is attributed to a collaboration with Cerebras, which optimized the model for better latency and performance [3][6] - In the SWE-Bench Pro benchmark, SWE-1.5 achieved a score of 40.08%, just behind Sonnet 4.5's 43.60%, indicating near-state-of-the-art coding performance [6] Development and Infrastructure - SWE-1.5 is trained on an advanced cluster of thousands of NVIDIA GB200 NVL72 chips, which offer up to 30 times better performance and 25% lower costs compared to previous models [10] - The training process utilizes a custom Cascade AI framework and incorporates extensive reinforcement learning techniques to enhance model capabilities [10][11] Strategic Vision - The development of SWE-1.5 is part of a broader strategy to integrate AI coding capabilities directly into the Windsurf IDE, enhancing user experience and performance [13][15] - Cognition emphasizes the importance of a collaborative system that includes the model, inference process, and agent framework to achieve high speed and intelligence [13][14] Market Position and Competition - The launch of SWE-1.5 coincides with Cursor's release of its own high-speed model, Composer, indicating a strategic convergence in the AI developer tools market [17] - Both companies are leveraging reinforcement learning in their models, highlighting a shared approach to creating efficient coding agents [17] User Feedback and Performance - Early user feedback on SWE-1.5 indicates a perception of high speed, although some users reported issues with task completion compared to other models like GPT-5 [18][19]