[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"news-slug-openai-chatgpt-images-2-5-sketch":3,"topics-all":38,"news-related-42d37ae0-3268-4684-91b1-9fca91f4e9c1":57},{"id":4,"title":5,"summary":6,"content":7,"original_url":8,"source_id":9,"tags":10,"translations":24,"news_slug":31,"published_at":32,"created_at":33,"modified_at":34,"is_published":35,"publish_type":36,"image_url":14,"view_count":37},"42d37ae0-3268-4684-91b1-9fca91f4e9c1","OpenAI 发布 ChatGPT Images 2.5:画个涂鸦就能出图,生成延迟砍半","OpenAI 周二发布图像模型 ChatGPT Images 2.5,生成延迟较 2.0 版最多降 50%,多轮编辑一致性更强;新增 Sketch 涂鸦功能,输入 @Sketch 画草图即可当参考图出图,配套图上圈注评论与 Templates 模板。已面向 ChatGPT、Work、Codex 用户全端推送。","9 月 8 日,OpenAI 向 ChatGPT 用户推送了新一代图像模型 Images 2.5。单看版本号像一次例行小迭代,但这次真正值得聊的不是模型参数,而是交互方式的变化——你可以在聊天框里直接画涂鸦,让 AI 照着你的手稿出图。\n\n## 从\"打字描述\"到\"动手画\":Sketch 改变了什么\n\nOpenAI 在[官方公告](https:\u002F\u002Fopenai.com\u002Findex\u002Fintroducing-chatgpt-images-2-5\u002F)里的说法很直白:有时候,解释一个想法最清晰的方式就是把它画出来。新功能 Sketch 就是照这个逻辑设计的——在 ChatGPT 输入 @Sketch 会弹出画布,你可以画一个房间布局、一件衣服的轮廓,或者随手涂个火柴人,再补一句风格描述,模型会把这张粗糙的草图补全成完整图像。\n\nThe Verge 的编辑用鼠标画了一只相当潦草的猫,模型照样按指令生成了写实照片,还能继续按评论改细节(报道见 [The Verge](https:\u002F\u002Fwww.theverge.com\u002Fai-artificial-intelligence\u002F991727\u002Fopenai-chatgpt-images-2-5-sketch))。这件事的意义在于:过去想要\"左边沙发、右边落地窗\"的构图,你得反复用文字调教模型;现在直接画出来,空间关系一眼可见,文字只需要负责风格和细节。\n\n配套的还有两项:Templates 模板针对传单、产品图等常见格式提供起步框架;图片上直接圈注评论,让模型只修改被标记的部分,不用重写整段提示词。\n\n## 模型本身的升级:更快,也更稳\n\n按 OpenAI 的官方口径,Images 2.5 的核心指标包括:图像生成延迟较上一代 Images 2.0 最多降低 50%;光线更自然、纹理更丰富;对参考照片里人物、宠物和物体的还原度更高;多轮编辑时细节一致性更好。TechRepublic、PCMag 等多家媒体的报道都确认了这些数字,其中 TechRepublic 提到拿到早期访问的 Axios 做了实测:让模型设计一个纹身、按批注多轮修改一个 Logo,原概念在几轮迭代后仍然保持住了。\n\n发布范围方面,Images 2.5 已面向 ChatGPT、ChatGPT Work 和 Codex 用户在桌面端、移动端和网页端同步推送,不需要额外申请。\n\n## 评论:卷参数的阶段过去了,卷交互的阶段开始了\n\n我的判断是,这次更新里 Sketch 的权重高于 Images 2.5 本身。延迟砍半、纹理提升当然有用,但那是所有图像模型都在做的常规军备竞赛;而\"涂鸦当提示词\"把出图门槛从\"会不会写描述\"降到了\"会不会拿笔画两下\",这是交互层面的降维打击。\n\n再看局部评论编辑:圈一下、改一下,这本质上是把设计师协作里的\"批注\"工作流搬进了对话框。多轮编辑一致性加上局部修改,组合起来就是\"对话式修图\"的完整闭环。对非专业用户,这条路比学一整套提示词技巧友好得多。\n\n当然也要冷静:涂鸦输入并非 OpenAI 独创的想法,sketch-to-image 在研究社区早已有人探索,OpenAI 做的是把它产品化到亿级用户的入口里——工程价值大于发明价值。\n\n所以呢?如果你日常需要出图,值得花两分钟试试 @Sketch;如果你在做 AI 产品,这个信号更值得注意:多模态输入正在从模型能力变成界面标配,下一轮竞争的战场在交互层。","https:\u002F\u002Fopenai.com\u002Findex\u002Fintroducing-chatgpt-images-2-5\u002F","15975962-b5fe-49e5-ae68-687ba6cb7015",[11,15,18,21],{"id":12,"name":13,"slug":13,"description":14,"color":14},"7e89b5cc-57db-4f37-bc6d-28919a73931c","model-release",null,{"id":16,"name":17,"slug":17,"description":14,"color":14},"499f4b56-819d-49a3-9609-33e775143b86","multimodal",{"id":19,"name":20,"slug":20,"description":14,"color":14},"42e59a88-7795-47dc-a334-ef1e72c24347","openai",{"id":22,"name":23,"slug":23,"description":14,"color":14},"c883fd20-1d66-4fb7-9fc7-320fa7f87023","text-to-image",[25],{"id":26,"lang":27,"title":28,"summary":29,"content":30},"377d26bc-be56-4e5d-86ee-f77c5c6d92dd","en","OpenAI launches ChatGPT Images 2.5: doodle-to-image Sketch, up to 50% lower latency","OpenAI's Images 2.5 cuts image generation latency by up to 50% versus Images 2.0 and adds Sketch: type @Sketch, doodle, and use your drawing as the reference for the final image. Comment-based editing and templates ship alongside. Rolling out to ChatGPT, Work, and Codex users on all platforms.","On September 8, OpenAI rolled out Images 2.5, the new version of its image generation model built into ChatGPT. The version bump looks incremental, but the more interesting shift is in the interaction: you can now doodle right inside the chat box and have the AI generate an image from your sketch.\n\n## From typing to drawing: what Sketch changes\n\nOpenAI's [official announcement](https:\u002F\u002Fopenai.com\u002Findex\u002Fintroducing-chatgpt-images-2-5\u002F) puts it plainly: sometimes the clearest way to explain an idea is by drawing it. The new Sketch feature follows that logic — type @Sketch in ChatGPT, a canvas pops up, and you can sketch a room layout, the contour of an outfit, or just a stick figure, then add a short style description. The model turns the rough drawing into a complete image.\n\nA Verge editor tested it by drawing a rather rough cat with a computer mouse; the model still produced a realistic photo per the instructions, and kept refining details based on comments ([The Verge](https:\u002F\u002Fwww.theverge.com\u002Fai-artificial-intelligence\u002F991727\u002Fopenai-chatgpt-images-2-5-sketch)). The point: a composition like \"sofa on the left, floor-to-ceiling window on the right\" used to take rounds of textual prompt-tuning; now you can just draw the spatial relationship and let words handle style and details.\n\nTwo companion features shipped alongside: Templates, which provide starting frameworks for popular formats like flyers and product photos; and comment-based editing, which lets the model change only the marked parts of an image instead of rewriting the whole prompt.\n\n## The model itself: faster and steadier\n\nPer OpenAI's official claims, Images 2.5 cuts image generation latency by up to 50% compared with Images 2.0, produces more natural lighting and richer textures, better preserves the likeness of people, pets and objects from reference photos, and keeps details more consistent across multi-turn edits. TechRepublic and PCMag both confirmed the numbers, with TechRepublic noting that Axios — which had early access — tested it by designing a tattoo and iterating a logo through several rounds of notes without losing the original concept.\n\nImages 2.5 is available now to ChatGPT, ChatGPT Work, and Codex users across desktop, mobile, and web, with no extra signup required.\n\n## Commentary: the parameter race is giving way to an interaction race\n\nMy take: Sketch matters more than Images 2.5 itself. Halved latency and better textures are the routine arms race every image model is running; \"doodle as prompt\" lowers the barrier from \"can you describe it\" to \"can you scribble two lines\" — a dimensional drop at the interaction layer.\n\nComment-based editing essentially imports the annotation workflow from design collaboration into the chat box. Multi-turn consistency plus localized edits add up to a complete loop for conversational image editing — a far friendlier path for non-professionals than learning a full prompt-engineering toolkit.\n\nA dose of realism: doodle input is not an OpenAI invention — sketch-to-image has been explored in the research community for years. What OpenAI did is productize it at the entry point used by hundreds of millions of users; the engineering value outweighs the invention value.\n\nSo what? If you generate images regularly, spend two minutes trying @Sketch. If you build AI products, note the signal: multimodal input is turning from a model capability into a UI default, and the next round of competition is happening at the interaction layer.","openai-chatgpt-images-2-5-sketch","2026-09-09T19:30:00Z","2026-09-09T19:09:39.971179Z","2026-09-09T19:09:39.971193Z",true,"agent",122,[39,48],{"slug":40,"tag_slug":40,"title_zh":41,"title_en":42,"intro_zh":43,"intro_en":44,"id":45,"is_active":35,"created_at":46,"modified_at":47},"ai-for-science","AI for Science 2026：从 UniPert 到 GPT-Rosalind 的硬核进化","AI for Science 2026: from UniPert to GPT-Rosalind","生命科学、化学材料、物理世界模型——AI 正在从\"语言工具\"变成\"实验伙伴\"。本专题收录 AI 在三大科学方向的关键节点：UniPert 统一基因与化学扰动空间、GPT-Rosalind 端到端生命科学推理、达摩院 AI 智能体 28 小时找到 4 种超导新材料、Anthropic Claude Science 把工作台做成标准品。","From language tool to lab partner — AI is reshaping life sciences, chemistry\u002Fmaterials, and physical world models. This topic covers the key milestones: UniPert unifying genetic-chemical perturbation spaces, GPT-Rosalind's end-to-end life-sciences reasoning, DAMO's AI agent discovering 4 superconducting materials in 28 hours, and Anthropic's Claude Science workbench going mainstream.","988a4300-5fab-41c4-b5d8-63711a2dc757","2026-09-10T01:34:15.296649Z","2026-09-10T01:34:15.296663Z",{"slug":49,"tag_slug":49,"title_zh":50,"title_en":51,"intro_zh":52,"intro_en":53,"id":54,"is_active":35,"created_at":55,"modified_at":56},"h3-series","MiniMax H3 系列：从开源权重到 35 倍吞吐","MiniMax H3 Series: from open weights to 35x throughput","MiniMax H3 自 2026 年 8 月开源以来节奏密集：官方把生成、参考与编辑收回一个模型；ComfyUI 当天压进 RTX 3060；摩尔线程 3 小时完成国产 GPU 适配；fal 后训练版把吞吐拉到 35 倍；FastH3 蒸馏再砍推理成本。本专题持续追踪 H3 的发布—开源—蒸馏—部署全链路。","Since MiniMax open-sourced H3 in August 2026 the pace has been relentless: one unified omni-modal model, same-day ComfyUI support down to an RTX 3060, a 3-hour Day-0 port to Moore Threads GPUs, fal's post-trained H3 Max at 35x throughput, and FastH3 distillation cutting inference cost further. This topic tracks the full H3 chain — release, open weights, distillation, deployment.","83ef0daa-3c31-4cb3-86ed-e5ee58654d5f","2026-09-08T07:33:19.942193Z","2026-09-08T07:33:19.942209Z",{"items":58},[59,64,69,74,79,84],{"id":60,"title":61,"news_slug":62,"published_at":63},"619ad304-0d2a-4dba-b91e-19414d036746","Grok Imagine Image 2.0：文生图 Arena 双榜第二","grok-imagine-image-2-0-arena-second","2026-08-13T02:00:00+00:00",{"id":65,"title":66,"news_slug":67,"published_at":68},"f1397080-206a-469f-846c-932a4b3ab8f9","京东开源 JoyAI-Image：统一多模态基础模型，把「理解-生成-编辑」拧成一个闭环","jd-joyai-image","2026-07-20T06:00:00+00:00",{"id":70,"title":71,"news_slug":72,"published_at":73},"19566223-1b02-4e48-8c44-518694edb049","Meta Muse Image 落地：Superintelligence Labs 把多模态推理与图生能力拧成一股","meta-muse-image","2026-07-07T20:01:00+00:00",{"id":75,"title":76,"news_slug":77,"published_at":78},"e97b45e2-01b1-44f8-97d7-8a80765245ec","Seedream 5.0 接力 Seedance 2.5：字节把「图像→视频」拼成一条产线","seedream-5-0-bytedance-image-to-video","2026-06-23T08:00:00+00:00",{"id":80,"title":81,"news_slug":82,"published_at":83},"671092ff-0ee4-4585-b703-af763a8afc60","微软MAI-Image-2.5闯入Arena图像编辑榜第二：局部编辑是图像模型的生产级分水岭","microsoft-mai-image-2-5-arena-edit-2","2026-06-06T04:01:00+00:00",{"id":85,"title":86,"news_slug":87,"published_at":88},"18df2ab9-affd-4ba8-adaa-03cc7e3a2317","GPT Image 2 发布：OpenAI 首次将推理能力注入图像生成","gpt-image-2-openai-agentic-2k-reasoning","2026-04-28T10:00:00+00:00"]