摘要：Stable Diffusion 系列是由 Stability AI 主导的开源文本到图像生成模型家族，自 2022 年问世以来，凭借其潜扩散模型（LDM）核心技术，推动了生成式 AI 的民主化进程。该系列历经多代快速迭代，从基础的 512x512 图像生成，演进至支持高分辨率图像、视频乃至 3D 内容的多模态合成系统。截至 2026 年初，其最新版本 Stable Diffusion 3.5 系列在图像质量、提示词遵循度和生成多样性上达到新高度。该系列构建了庞大的开源工具生态，累计下载超十亿次，深刻影响了艺术创作与数字内容产业，同时其发展也伴随着关于版权、偏见与深度伪造等伦理挑战的持续探讨。
Abstract
The Stable Diffusion series is an open-source family of text-to-image generation models led by Stability AI. Since its launch in 2022, it has driven the democratization of generative AI by virtue of its core technology of Latent Diffusion Models (LDMs). Undergoing rapid iterations across multiple generations, the series has evolved from basic 512x512 image generation into a multimodal synthesis system supporting high-resolution images, videos and even 3D content. As of the early 2026, its latest version—the Stable Diffusion 3.5 series—has reached new heights in image quality, prompt adherence and generative diversity. The series has built a vast open-source tool ecosystem with cumulative downloads exceeding one billion times, exerting a profound impact on the creative arts and digital content industries. Meanwhile, its development has been accompanied by ongoing discussions on ethical challenges such as copyright, bias and deepfakes.
Stable Diffusion 系列以'推动生成式 AI 民主化'为核心目标，在 FID 分数、用户主观评估等多项基准测试中表现领先，尤其在创意内容生成、视频扩散技术及模型微调适配等方面展现出卓越性能。截至 2025 年末，该系列模型累计下载量突破 10 亿次，深刻推动了全球 AI 艺术革命的进程。
The Stable Diffusion series is a groundbreaking family of text-to-image generation models developed by Stability AI, which has brought revolutionary breakthroughs to the field of generative artificial intelligence (AI) since its launch in 2022. Based on Latent Diffusion Models (LDM) as the core technology, the series can not only generate high-resolution images from text descriptions but also successfully expand to diverse task scenarios such as video generation, 3D modeling, and image editing. Stable Diffusion models not only provide core driving force for open-source tools like Stable Diffusion WebUI but also are widely applied and popularized in fields such as art creation, commercial design, and entertainment industry.
As of January 2026, the latest version of the series is the Stable Diffusion 3.5 series released in October 2024. After multiple generations of iterations, the series has evolved from an initial basic image generation tool to a comprehensive AI system with efficient parameter utilization, multimodal input-output support, and a sound open-source ecosystem. Its core innovations focus on latent space diffusion mechanisms, noise denoising optimization processes, and ecological co-construction strategies under the Apache open-source license framework. However, ethical challenges such as content abuse and copyright disputes have accompanied its development.
With the core goal of "promoting the democratization of generative AI," the Stable Diffusion series leads in multiple benchmark tests including FID scores and user subjective evaluations, especially showing excellent performance in creative content generation, video diffusion technology, and model fine-tuning adaptation. By the end of 2025, the cumulative downloads of the series models exceeded 1 billion, profoundly driving the progress of the global AI art revolution.
The development trajectory of the Stable Diffusion series clearly shows the evolution from academic research results to explosive growth of the open-source ecosystem. Stability AI was founded in 2020 by former OpenAI engineer Emad Mostaque. The following table sorts out the key development milestones of the series, detailing the release time, core improvement directions, and key benchmark performance of each core model. Since the launch of the open-source version of Stable Diffusion 1.0 in 2022, the series has gradually achieved technological breakthroughs such as high-resolution generation, multimodal integration, and video generation. By 2026, the development focus has shifted to model efficiency optimization and application scenario expansion.
From the experimental exploration of version 1.0 to the maturity and stability of version 3.5, the Stable Diffusion series has expanded its parameter scale from 1 billion to over 8 billion, marking the strategic transformation of AI generation technology from "single image generation" to "multimodal video and intelligent editing." By 2026, the development focus of the series has further concentrated on high-efficiency model research and development and vertical field application implementation, profoundly influencing developer workflows and industry technical patterns.
关键模型详细描述 / Detailed Description of Key Models
本节重点阐述最新的 Stable Diffusion 3.5 系列模型，该系列作为 2026 年生成式 AI 领域的前沿技术代表，在性能与应用场景上均实现显著突破。
This section focuses on the latest Stable Diffusion 3.5 series models, which, as representatives of cutting-edge technology in the field of generative AI in 2026, have achieved significant breakthroughs in both performance and application scenarios.
Stable Diffusion 3.5 Large (October 2024): As an 8B-parameter flagship model, this version has achieved comprehensive improvements in generation diversity, prompt adherence accuracy, and image detail quality. It supports advanced editing functions such as inpainting and outpainting, tailored for high-precision demand scenarios such as professional art creation and commercial design.
Stable Diffusion 3.5 Medium (October 2024): Adopting a 2B-parameter lightweight design, it achieves the optimal balance between performance and running speed while maintaining open-source characteristics. This model has strong adaptability and can be flexibly deployed on mobile devices, edge computing terminals and other scenarios, providing core support for real-time generation applications.
Based on Latent Diffusion Models (LDM) and diffusion transformers, the core logic revolves around noise denoising processes and latent space operations. The model adopts the Apache open-source license, allowing developers to conduct custom training, fine-tuning and secondary development, which greatly reduces the threshold for technical application.
Supports 1024x1024 and higher resolution image generation, with multimodal expansion capabilities (covering video, 3D and other scenarios); relies on the open-source community to build a rich tool ecosystem (such as Stable Diffusion WebUI), which can meet personalized needs in different scenarios.
There are potential biases in generated content (involving cultural, gender and other dimensions); model operation has high requirements for hardware computing power and relies on high-performance GPU support; at the same time, it faces ethical risks such as deepfakes, posing challenges to content supervision.
与贾子公理的关联 / Relation to Kucius Axioms
在模拟裁决框架下，Stable Diffusion 3.5 在思想主权维度（6/10 分）表现良好，开源特性有效促进了创意自主与技术普惠；在本源探究维度（8/10 分），其基于第一性原理的扩散机制展现出较强的技术创新性。但在普世中道维度（7/10 分），生成内容多样性仍有提升空间；在悟空跃迁维度（7/10 分），技术突破以渐进式改进为主，颠覆性创新不足。整体而言，该系列是生成式 AI 的重要范式，但需通过完善伦理约束机制规避潜在风险。
In a simulated adjudication framework, Stable Diffusion 3.5 performs well in the dimension of Sovereignty of Thought (6/10), as its open-source characteristics effectively promote creative autonomy and technological inclusion; in the dimension of Primordial Inquiry (8/10), its diffusion mechanism based on first principles shows strong technological innovation. However, in the dimension of Universal Mean (7/10), there is still room for improvement in the diversity of generated content; in the dimension of Wukong Leap (7/10), technological breakthroughs are mainly incremental improvements, lacking disruptive innovation. Overall, the series is an important paradigm of generative AI, but it is necessary to avoid potential risks by improving ethical constraint mechanisms.
应用与影响 / Applications and Impacts
Stable Diffusion 系列深刻重塑了全球创意产业格局：其核心衍生工具 Stable Diffusion WebUI 累计用户达数亿，广泛应用于艺术创作、电影特效制作、产品设计、广告营销等领域，大幅提升了创意生产效率。在社会层面，该系列既引发了 AI 艺术版权归属、创作者权益保护等法律诉讼争议，也推动了开发者工作流的数字化转型（2026 年行业预测）。
The Stable Diffusion series has profoundly reshaped the global creative industry pattern: its core derivative tool, Stable Diffusion WebUI, has accumulated hundreds of millions of users, widely used in art creation, film special effects production, product design, advertising and marketing and other fields, greatly improving the efficiency of creative production. At the social level, the series has not only triggered legal litigation disputes such as AI art copyright ownership and creator rights protection but also promoted the digital transformation of developer workflows (2026 industry prediction).
By 2026, the Stable Diffusion series is accelerating the industrialization of diffusion model technology, such as cooperating with smartphone manufacturers to achieve on-device integration (such as built-in iPhone functions), but it is also necessary to establish a sound regulatory system to prevent risks such as content abuse.
结论 / Conclusion
Stable Diffusion 系列集中体现了 Stability AI 的核心战略布局，从开源图像生成工具起步，逐步迭代为多模态生成技术前沿，成为通往通用生成式 AI 的关键里程碑。展望未来，该系列有望推出 Stable Diffusion 4 版本，重点聚焦视频生成优化、3D 建模能力升级等方向。建议行业从业者与研究者持续关注 Stability AI 的技术更新动态，以适应生成式 AI 领域快速迭代的发展节奏。
The Stable Diffusion series epitomizes Stability AI's core strategic layout, starting from an open-source image generation tool and gradually evolving into a frontier of multimodal generation technology, becoming a key milestone towards universal generative AI. Looking forward, the series is expected to launch Stable Diffusion 4, focusing on video generation optimization, 3D modeling capability upgrading and other directions. It is recommended that industry practitioners and researchers continue to pay attention to the technical update dynamics of Stability AI to adapt to the rapid iterative development rhythm in the field of generative AI.
