Core Insights - The launch of the Ketu 2.1 model by Keling AI significantly enhances image generation capabilities, including improved instruction adherence, stunning portrait aesthetics, and cinematic quality [1][11] - The model is available for free to all member users for a limited time, allowing creators to explore its features [11] Image Generation Capabilities - Ketu 2.1 excels in following complex instructions, accurately capturing multiple elements and details in prompts, resulting in high-quality images that showcase creative imagination [1][3] - The model demonstrates a notable improvement in image quality, including clarity, richness of elements, and realism, particularly in portrait aesthetics [3][5] Artistic and Cinematic Quality - The model can generate images with a cinematic feel, effectively recreating scenes with unique aesthetic tones and advanced composition [6] - It supports over 180 different styles, allowing creators to choose from various artistic expressions, from vintage photography to futuristic digital art [10] Text Generation Features - Ketu 2.1 also enhances text generation, producing clear and design-oriented text in both Chinese and English, facilitating smoother integration of text and images for marketing and creative projects [8] User Engagement and Growth - Keling AI has achieved significant user engagement, with a total of 344 million images and 168 million videos generated since its launch, showcasing its strength in the image generation sector [11]

5月21日，国内首个基于国产算力预训练的视觉基座大模型"橘洲"V1端侧版在长沙正式上线。该模型能 在手机端实现1024×1024分辨率图像的秒级生成，具有成本低、质量高、速度快、轻量级、可离线等特 点。"橘洲"大模型由湖南汇视威智能科技有限公司自主研发，依托中科曙光（603019）算力，在较短时 间完成了近4000万张图片训练，成为全国首个在国产算力上完成整体训练和推理过程，并实现移动端部 署的视觉基座大模型。(长沙发布) ...

长沙晚报全媒体记者 张洋子 2025年，当全球AI竞赛进入"端侧部署"新阶段之际，一款纯国产、适配智能手机端、输入文字可实现秒级出图 的视觉生成大模型首次亮相长沙。 20日，湖南汇视威智能科技有限公司（以下简称"汇视威"）发布了视觉基座大模型"橘洲"（V1端侧版本）。与 当前主流的视觉生成大模型有所区别，"橘洲"是国内基于国产算力预训练的视觉基座大模型，可在智能手机端 实现1024×1024分辨率图像的秒级生成，并能满足在移动端上的部署和推理需求。 轻量化架构优势、多项突破性技术，"橘洲"将实现在全国甚至全球行业关键性能领跑，剑指全球行业榜单。这 款"橘洲"有多"硬核"？本报记者一探究竟。 "硬核"设计：适配手机，"小身材"有"大能量" 视觉基座大模型是视觉人工智能生成的基础设施，目前的视觉基座大模型由于其参数量大、算力需求高，推理 过程大多在服务器"云端"实现，因此端侧通用视觉大模型成为破局关键。 "算力消耗巨大、高延迟、安全隐私风险、服务器维护成本高，这些都是传统视觉大模型的缺点。"汇视威创始 人、董事长顾善植介绍，这种运用方式有三大弊端：一是模型推理成本高，给服务器算力成本和运维成本带来 极高压力；二是 ...