Anthropic 的 Claude Fable 5.2 用代码画图：70 万次笔刷模拟绘画
Anthropic's Claude Fable 5.2 doesn't generate images, it paints them
Anthropic 把图像生成换成了写 Python 代码模拟 70 万次真实笔刷，连鬃毛质感都有。和 DALL·E、Midjourney 的像素路线完全不同，做创意工具或研究图像生成的开发者值得看看这个思路。
Anthropic 推出 Claude Fable 5.2，其图像呈现方式与主流扩散模型不同：模型不直接计算像素，而是编写 Python 代码，在虚拟画布上模拟真实笔刷作画。据 Anthropic 员工 Jake Eaton 介绍，一幅写实风格的停车场场景大约需要 70 万次笔刷操作。
具体机制上，每次笔刷都带有鬃毛质感和颜料堆叠效果，模拟真实绘画中刷毛分叉、颜料厚薄等物理细节。Claude Fable 5.2 本质上仍是语言模型，它通过生成代码来控制笔刷的位置、力度与颜色，最终渲染出成品图像。
这种做法与 DALL·E、Midjourney 等像素级生成路线形成明显区分，代价是单幅图像的计算量极大。对开发者而言，这是一种新的图像生成思路，但如何在实际产品中控制成本和生成时间仍是关键问题。
Anthropic's Claude Fable 5.2 doesn't generate images, it paints them
Anthropic's Claude Fable 5.2 doesn't generate images the way other AI models do. Instead of computing pixels, the language model writes Python code that places hundreds of thousands of simulated brushstrokes on a virtual canvas, complete with bristle texture and paint application. A single photorealistic parking garage scene took roughly 700,000 strokes, according to Anthropic employee Jake Eaton. The article Anthropic's Claude Fable 5.2 doesn't generate images, it paints them appeared first on The Decoder .
This report is categorized under AITOP's "Models" desk, focusing on US frontier AI labs and Silicon Valley technology leaders. Within our cross-regional analytical framework, it directly maps to AI developer toolchains, coding agents, and engineering workflows and US-China foundation model benchmarks and commercialization comparison. Key entities and technical topics under continuous tracking include Claude, Anthropic, image generation, Python.
Source attribution: curated from Decoder (@Manuel Uth).
