即梦 Seedance2.0 深度解析 20260210 摘要 CDS 2.0 通过统一多模态架构，融合文字、图像、音频和视频帧进行训 练，提升了语义理解和生成效果，尤其在初始提示词的精确度要求上有 所降低，更易于广泛应用。 CDS 2.0 采用多镜头技术，优化了分镜切换和面部主体锁定，提高了视 频的整体一致性和观感，同时引入奖励模型，增强了视觉细节的物理合 理性和美感。 与其他视频生成模型相比，CDS 2.0 在统一多模态架构、情绪控制性、 多镜头技术和奖励模型引入方面具有独特优势，提升了初次生成效果和 整体视频质量。 视频生成领域的技术挑战在于将 TIT 架构扩展为面向多模态领域的 DIT 架构，并引入时间层次，以实现对视频每一秒钟的精细控制，同时扩大 数据和参数量以提升模型规模。 降低视频生成推理成本的关键在于优化参数计算，例如通过同时处理音 频特征和画面，并结合输入提示进行变形处理，从而在不增加参数量的 情况下降低成本。 Q&A CDS 2.0 模型在视频生成领域有哪些显著进步和优势？ CDS 2.0 模型在视频生成领域的显著进步主要体现在精确控制性和生成速度上。 传统的视频生成方法通常依赖于将文本转 ...

Summary of Conference Call Records Industry Overview - The conference call discusses the rapid development of multimodal models in China, highlighting the narrowing gap with leading overseas models, particularly in understanding physical rules. The release of version 3.0 for consumer applications has significantly improved capabilities due to advancements in data production lines and infrastructure [1][2][8]. Key Points on Specific Models - **CDS 2.0**: - Utilizes a dual-branch DIT (Diffusion Transformer) architecture, allowing for synchronized video and audio generation, enhancing audio modeling and multi-shot understanding [1][3][4]. - Demonstrates strong performance in prompt understanding, shot composition, audio-visual synchronization, and clarity [2]. - Benefits from the ByteDance LLaMA ecosystem, providing advantages in prompt understanding and post-editing capabilities [5]. - **VIVO 3.1**: - Based on the Gemini Transformer architecture, it incorporates Latent Diffusion methods for 3D spatial understanding, improving character consistency and virtual reality comprehension [5]. - **CIDES 2.0**: - Excels in video generation duration (10-15 seconds of high-definition video), audio-visual synchronization, and multi-shot narrative capabilities, outperforming competitors in these areas [5][6]. Market Dynamics - The commercial prospects for multimodal large models are promising, with both domestic and international companies launching products and gradually opening them to consumer users. Pricing strategies indicate a keen understanding of market demand [6][9]. - Domestic models like JIMU and Keling show advantages in generation speed (60-80 seconds) and resolution (up to 2K), compared to international models like Sora and VO, which typically require over 100 seconds and are limited to 1080P resolution [7][8]. Future Trends - The development of multimodal large models is expected to significantly impact various industries, particularly short video production, e-commerce, and advertising, by lowering creative implementation costs and enhancing efficiency [9][10]. - The demand for computational power is projected to increase exponentially due to the large-scale application of version 3.0, prompting companies like OpenAI to accelerate the construction of computational centers [11][12]. Competitive Landscape - Major companies like Alibaba and Tencent are making strides in the multimodal field, with Alibaba launching new image generation models and Tencent maintaining a leading position with its mixed 3D models [14]. - Smaller companies can remain competitive by leveraging self-trained models or integrating with major companies' APIs, although they may face greater financing pressures [11]. Conclusion - The conference call highlights the rapid advancements in multimodal AI models, the competitive landscape, and the significant implications for various industries. The ongoing developments suggest a transformative period for content creation and AI applications in the near future [20].

从 seedance2.0 看 AI 漫剧短剧爆发趋势 20260210 摘要 Sora 2、VU 3.1、vidu、可灵 3.0 和 CDS 2.0 等国内外 AI 模型各有优 势，CDS 2.0 在综合能力和创新功能上表现突出，尤其在 AI 漫剧短剧制 作方面，能结合多种元素自动生成字幕和台词，大幅降低导演门槛。 AI 技术显著降低了 AI 漫剧的人工成本，效率提升 5 至 10 倍。C 站 3.0 版本使得每分钟优质视频的生成成本在 50 至 100 元之间，虽然模型本 身未降价，但总体制作周期缩短，节省了大量人工成本。 2025 年下半年 AI 漫剧市场爆发，市场规模估计为 200 亿元。预计 2026 年市场规模将达到 500 亿元，但随着精品视频制作效率提高，实 际市场规模有望超过此预测。 早期 AI 漫剧投资回报率（ROI）可达 2 以上，目前趋于理性，约为 1.1 至 1.2，多数公司仍处于亏损状态。头部公司如酱油文化和慢谈，市场 贡献分别占比 11%和 17%，毛利率约为 50%。 平台政策多样，包括保底模式、直接购买剧集、第三方承制和直接签约 等。选择合作平台需考虑平台属性和受众特点，早期 ...

新工具将加速其工业化进程，提高 IP 改编的重要性。 CDS 2.0 作为字节推出的 AI 视频生成模型，有哪些技术特点及应用前景？ CDS 2.0 是字节推出的一款 AI 视频生成模型，于 2026 年 2 月 7 日开始小范 围测试，并已在即梦平台上开放会员使用。CDS 2.0 最大的亮点在于其参考能 力及可控创作方式。在基础能力方面，该模型在物理规律遵循、动作表现流畅 度以及指令遵循度等方面均有显著增强。此外，多模态素材支持使得用户可以 上传文本、图片（最多 9 张）、视频（最多 3 个）及音频（最多 3 个），合计 不超过 12 个文件，用于生成视频。 CDS 2.0 的应用前景广阔，特别是在影视 内容制作领域。例如，影视飓风创始人 Tim 对该模型在复杂动作场景中的运镜 效果给予高度评价，而黑熊王悟空制作人冯骥则认为 AIGC 进入了新的时代。 CDS 2.0 不仅简化了操作流程，提高了成功率，还具备高效的 token 使用效率， 使其能够同时满足 B 端与 C 端的大规模使用需求。 多模态+游戏投资逻辑更新 20260210 摘要 字节跳动推出 AI 视频生成模型 CDS 2.0，亮点在于其参考能 ...