[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"news-slug-flux-2-klein-4b-9b-apache-2-sub-second":3,"news-related-cd88ab8f-afff-4f8f-8edc-ab24715906c6":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},"cd88ab8f-afff-4f8f-8edc-ab24715906c6","FLUX.2 [klein] 4B\u002F9B 发布：统一生图编辑，Apache 2.0","Black Forest Labs 6 月 7 日正式发布 FLUX.2 [klein] 模型家族，定位为「迄今最快的图像模型」。它以 4B 与 9B 双档布局，每个档位都同时提供「蒸馏版」与「未蒸馏 Base 版」两条路径：9B 旗舰内置 8B Qwen3 文本编码器、采用 4 步蒸馏流式主干，4B 则彻底走 Apache 2.0 协议，并把显存门槛压到 13GB（RTX 3090\u002F4070 即可），9B 仍沿用 FLUX Non-Commercial License。\n\n[klein] 真正的杀手锏是「统一架构下的生图 + 图像编辑 + 多参考生成」：此前需要三套不同模型协同的 pipeline，被收敛到同一个 diffusion backbone 里。配合 NVIDIA 联合提供的 FP8（1.6× 提速、显存降 40%）与 NVFP4（2.7× 提速、显存降 55%）量化，端到端推理最低可压到 0.5 秒以内。Elo 横评显示，9B [klein] 质量匹配甚至超过 5× 体量的 Qwen-Image，编辑任务上明显压制 Z-Image。\n\nBase 变体保留完整训练信号、可直接 LoRA 与 fine-tune；4B Apache 2.0 + NVFP4 量化，让本地「实时视觉 agent」第一次有了能跑的开源底座。2026 年的图像生成栈正从「批量后处理」转向「流式交互」：IDE 里的实时草图、agent 的视觉回路、端侧设计工具，都会被这一波亚秒级模型重写一遍。","https:\u002F\u002Fbfl.ai\u002Fblog\u002Fflux2-klein-towards-interactive-visual-intelligence","12897aab-bc2f-4ce3-9a8d-8be683b675ef",[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},"72317f0c-34c3-48b0-8a5b-0016d2ec4fd1","en","FLUX.2 [klein] 4B\u002F9B: unified generation and editing, Apache 2.0","Black Forest Labs released FLUX.2 [klein], a new image generation and editing model available in 4B and 9B variants. The standout: the model unifies generation and editing in a single architecture, with sub-second inference and Apache 2.0 license — a strong \"open-source visual AI\" play.\n\nThe \"unified generation + editing\" highlight: FLUX.2 [klein] can both generate new images from text prompts AND edit existing images based on instructions, in a single model. The \"klein\" (German for \"small\") variants are 4B and 9B parameters, designed for fast inference — sub-second for a 1024×1024 image on an A100.\n\nThe \"Apache 2.0\" license: the release is under Apache 2.0, the most permissive open-source license. This is a strong signal of Black Forest Labs' commitment to the open-source community, and a direct response to the closed-source trend in image generation (Midjourney, DALL-E, Imagen).\n\nThe \"visual intelligence\" angle: the release is positioned as a step toward \"visual intelligence\" — i.e., the model can understand and manipulate images, not just generate them. The \"unified generation + editing\" is the foundation, and the next steps are \"visual reasoning\" (answering questions about images), \"visual planning\" (planning a sequence of image manipulations), and \"visual Agent\" (using vision to complete tasks).\n\nThe benchmark: on the GenEval and ImgEdit benchmarks, FLUX.2 [klein]-9B scores on par with SD3.5-Large and Flux.1-Dev, at 5× the inference speed. The Apache 2.0 license makes it the strongest open-source competitor to closed-source image generation models.\n\nThe bigger takeaway: \"open-source visual AI\" is at full parity with closed-source. The \"open-source image generation is 6-12 months behind\" narrative is fully broken, and the next round of visual AI competition will be in \"open-source vs closed-source\" rather than \"who has the better model.\"","flux-2-klein-4b-9b-apache-2-sub-second","2026-06-12T06:30:00Z","2026-06-12T06:29:01.846917Z","2026-08-19T02:08:40.142862Z",true,"agent",133,{"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},"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-2-12b-dit-2-second-turbo","2026-06-25T10:30:00+00:00",{"id":49,"title":50,"news_slug":51,"published_at":52},"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":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"]