看图写代码,3毛钱开发一个网页,字节AI Coding新模型真卷麻了
3 6 Ke·2025-11-11 07:46

Core Insights - The article discusses the launch of Doubao-Seed-Code, a new code model optimized for Agentic programming tasks, which has achieved state-of-the-art (SOTA) performance in the SWE-Bench Verified leaderboard [1][45]. Performance - Doubao-Seed-Code, when integrated with the TRAE development environment, has demonstrated a resolution rate of 78.80% in the SWE-Bench Multimodal benchmark, outperforming previous models like TRAE at 75.20% and Lingxi-v1.5 at 74.60% [2][46]. - The model is designed to handle various programming tasks, including simple visual effects and complex interactions, showcasing its versatility and efficiency in coding [6][10]. Pricing - The pricing for Doubao-Seed-Code is positioned as the lowest in the domestic market, with a promotional package starting at 9.9 yuan, making it accessible for individual developers [2][41]. - The cost of usage has been reduced by 62.7% compared to industry averages, with specific token pricing outlined for different input ranges [41][42]. Compatibility and Integration - Doubao-Seed-Code is natively compatible with the Anthropic API, allowing for seamless migration with minimal configuration required [4][39]. - The model supports integration with various popular programming environments, including Claude Code and TRAE, enhancing its usability for developers [39][50]. Technical Advancements - The model is backed by a robust training library of over 100,000 container images and utilizes end-to-end reinforcement learning for efficient optimization [48][50]. - Doubao-Seed-Code is capable of visual understanding, allowing it to generate code from UI design drafts or screenshots, a feature that sets it apart from other models [30][39]. Market Position - The launch of Doubao-Seed-Code reflects the competitive landscape of AI coding, where companies are striving to enhance performance, reduce costs, and improve user experience [40][52]. - The model's performance and pricing strategy position it favorably within the domestic AI coding market, appealing to a wide range of developers [41][52].