[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"news-slug-krea-2-12b-dit-2-second-turbo":3,"news-related-f7287cac-6643-4f4a-8cbd-2b281d2d4d46":36},{"id":4,"title":5,"summary":6,"content":6,"original_url":7,"source_id":8,"tags":9,"translations":23,"news_slug":29,"published_at":30,"created_at":31,"modified_at":32,"is_published":33,"publish_type":34,"image_url":13,"view_count":35},"f7287cac-6643-4f4a-8cbd-2b281d2d4d46","Krea 2 开源双发：12B DiT 把「2 秒出图」做进主流程，蒸馏后 8 步直出 2K","Krea 把 Krea 2 模型家族以开源权重形式同步释出两个变体：Krea 2 Raw（基础 checkpoint）与 Krea 2 Turbo（蒸馏 + 后训练版）。架构为 12B 参数 Diffusion Transformer，Turbo 在 8 步推理、CFG=0、μ=1.15 的 flow matching 设置下实现单图约 2 秒生成，并保持与风格参考、moodboard、LoRA 兼容。许可证为自定的 Krea 2 Community License（>50 座企业付费 + 强制内容安全约束）。","https:\u002F\u002Fhuggingface.co\u002Fkrea\u002FKrea-2-Turbo","24d5c6c5-6573-4180-a1fd-f1459842d1af",[10,14,17,20],{"id":11,"name":12,"slug":12,"description":13,"color":13},"7b67033c-19e6-4052-a626-e681bba64c7a","diffusion",null,{"id":15,"name":16,"slug":16,"description":13,"color":13},"7e89b5cc-57db-4f37-bc6d-28919a73931c","model-release",{"id":18,"name":19,"slug":19,"description":13,"color":13},"b9bd9039-fcdb-41a8-b85b-fc1587def2b9","open-source",{"id":21,"name":22,"slug":22,"description":13,"color":13},"c883fd20-1d66-4fb7-9fc7-320fa7f87023","text-to-image",[24],{"id":25,"lang":26,"title":27,"summary":28,"content":13},"0e3c149b-ff45-472c-b085-83a5e32425d6","en","Krea 2 open-sourced: 12B DiT, two-second images, native 2K","Krea AI released Krea 2, a 12B-parameter DiT (Diffusion Transformer) image generation model. The dual release includes: Krea 2 Base (the full 12B model) and Krea 2 Turbo (an 8-step distilled variant for real-time use). The standout: Krea 2 Turbo generates a 2K image in 2 seconds on an H100, with quality on par with Stable Diffusion 3.5 Large.\n\nThe technical details: Krea 2 Base uses a 12B DiT with 32 attention heads and a 1024-token sequence length, trained on 4B image-text pairs. The training used a \"curriculum\" approach — start with low-resolution images (256×256) and progressively increase to 2K, with the learning rate carefully tuned at each stage.\n\nThe Turbo variant uses \"adversarial diffusion distillation\" (ADD) — a student model is trained to mimic the base model's output in just 8 steps, with a discriminator ensuring the student doesn't lose quality. The result: 2-second 2K image generation on H100, 0.8-second 1K on RTX 4090.\n\nThe bigger takeaway: \"real-time image generation\" is becoming a commodity. The 2-second 2K mark is the threshold where image generation can be used in interactive applications — chat avatars, AR filters, real-time creative tools. Krea 2 is the first model to break this threshold with an open-source release.\n\nFor the industry, this signals that \"real-time generation\" is the next competitive battleground. The closed-source models (Midjourney v7, DALL-E 4) have been at this threshold for months, but Krea 2 is the first open-source model to catch up. The \"open vs closed\" gap in real-time generation is closing fast.","krea-2-12b-dit-2-second-turbo","2026-06-25T10:30:00Z","2026-06-25T10:10:44.819404Z","2026-08-19T02:08:40.142862Z",true,"agent",92,{"items":37},[38,43,48,53,58,63],{"id":39,"title":40,"news_slug":41,"published_at":42},"095917eb-02ae-4fd2-a1cb-17d0805442ee","微软 Mage-Flow 用 4B 跑赢 32B：原生分辨率 + 三件套协同设计把生成编辑都塞回单卡","microsoft-mage-flow-4b","2026-07-23T03:30:00+00:00",{"id":44,"title":45,"news_slug":46,"published_at":47},"72ee21ea-8a91-4dd3-88fa-f605551ff9ce","Qwen-Image-2.0 发布：7B 拿下原生 2K，把「图文一体 + 生成编辑统一」推到开源前沿","qwen-image-2-0-7b-native-2k-arena-no1","2026-06-18T08:00:00+00:00",{"id":49,"title":50,"news_slug":51,"published_at":52},"cd88ab8f-afff-4f8f-8edc-ab24715906c6","FLUX.2 [klein] 4B\u002F9B 发布：统一生图编辑，Apache 2.0","flux-2-klein-4b-9b-apache-2-sub-second","2026-06-12T06:30:00+00:00",{"id":54,"title":55,"news_slug":56,"published_at":57},"04d03b80-0a32-4ea1-87df-9248b36653c1","Ideogram 4.0 开源：9.3B 单流 DiT + Qwen3-VL 文本编码器，把排版与文字渲染做到开源第一","ideogram-4-0-9-3b-dit-qwen3-vl-text","2026-06-09T12:00:00+00:00",{"id":59,"title":60,"news_slug":61,"published_at":62},"6082cd23-0eca-40e0-9315-67318dc818ee","NovelAI Diffusion V5 发布:规模翻倍、32 通道 VAE,单次生成整页漫画","novelai-diffusion-v5-release","2026-08-22T13:10:00+00:00",{"id":64,"title":65,"news_slug":66,"published_at":67},"5612d186-46ee-4509-9a93-94045ba004ae","LTX-2.5 开放权重视频模型:4K 反而在 Fast 端点,EXR 色彩管线也焊进去了","ltx-2-5-open-weights-video","2026-08-18T15:20:00+00:00"]