[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"news-slug-qwen-image-3.0-qianwen-ai-platform-pricing":3,"news-related-74464bd0-01e0-45a9-bc27-f94b1f5966a1":38},{"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},"74464bd0-01e0-45a9-bc27-f94b1f5966a1","Qwen-Image-3.0 上线千问 AI 平台：0.18 元\u002F张起步、Pro 与 Standard 双档开放 API","阿里巴巴千问图像生成模型 Qwen-Image-3.0 正式上线千问 AI 平台,旗舰版 Pro 与标准版 Standard 同步开放 API,文生图 0.18 元\u002F张起步,采用 1k\u002F2k 分档计费;海外用户可通过 Qwen Cloud 接入。这是 Qwen-Image-3.0 在 7 月底技术博客发布后首次对外商业化定价。","## Qwen-Image-3.0 终于「有价」:从博客发布到 API 商业化\n\n8 月初,阿里千问把 7 月底就放出的 Qwen-Image-3.0 接到了自己的 API 平台上——这意味着国产顶级开源文生图模型第一次有了**清晰的官方商业定价**,而不是只能去 Hugging Face 下载权重或者借用第三方代理。\n\n**API 怎么定价:**文生图统一 0.18 元\u002F张起,Pro 版在 2k 分辨率上抬到 0.5 元\u002F张,1k 仍是 0.25 元\u002F张;Standard 版不区分分辨率,无论 1k 还是 2k 全部 0.18 元\u002F张。输入图像按 0.02 元\u002F张另算,但纯文生图场景不产生输入费用。海外用户走 Qwen Cloud,价格换算后大致是国际同类模型的 30%~50% 区间(来源:千问 AI 平台计费文档 platform.qianwenai.com\u002Fdocs\u002Fdeveloper-guides\u002Fgetting-started\u002Fpricing)。\n\n**1k 和 2k 怎么划:**官方用「输出图像像素面积」做档位切分——面积 ≤ 2,250,000 像素算 1k,超过就是 2k。1024×1024≈1.05M,正好落在 1k;2048×1024≈2.10M,仍然 1k;要到 2k 得输出 2048×2048 以上。这是非常工程师友好的分档逻辑,写计费代码不用做浮点边界 case。\n\n**为什么 0.18 元\u002F张这个数值得拎出来:**横向对照同档国产开源文生图 API——智谱 CogView-4 \u002F 快手可图 \u002F Midjourney v7 的国行 API,**Standard 版 0.18 元\u002F张基本压在 0.2 元这条公认心理线下**。Pro 版在 2k 输出上虽然到 0.5 元,但叠加 Batch API 5 折后实际 0.25 元,仍然能打。\n\n**和 7 月底那次博客发布是什么关系:**技术博客那次(Qwen 官方)讲的是模型本身的架构升级——原生 2k、图文理解增强、中英文本渲染稳定性等;这次是**把它从「能下载」变成「能计费」**。两件事分属研发和商业化两条线,但放在一起看,Qwen-Image-3.0 现在是国产开源图像模型里**唯一同时具备顶级质量 + 官方 API + 完整定价表**的那一个。\n\n**所以呢:**开源文生图卷到现在,模型质量早就不是分胜负的地方了,真正的护城河是**「下载下来 → 接入应用 → 计费上线」**这一步的链路长度。Qwen-Image-3.0 这套「开源权重 + 官方托管 + 明确分档定价」的组合拳,给中小团队做产品化提供了最低成本的接入路径。如果你之前因为「下载下来还要自己搭推理、还要自己算 token\u002F张成本」而犹豫过文生图 API,现在可以重新评估了——尤其是 Standard 版,几乎可以无脑替换掉自托管的小模型。\n\n参考:千问 AI 平台计费文档 https:\u002F\u002Fplatform.qianwenai.com\u002Fdocs\u002Fdeveloper-guides\u002Fgetting-started\u002Fpricing","https:\u002F\u002Fplatform.qianwenai.com\u002Fdocs\u002Fdeveloper-guides\u002Fgetting-started\u002Fpricing","c36a21ac-2a77-421b-9519-1e150695732a",[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},"c187600e-804c-4697-b828-1e4330e0eb10","qwen",{"id":19,"name":20,"slug":20,"description":14,"color":14},"c883fd20-1d66-4fb7-9fc7-320fa7f87023","text-to-image",{"id":22,"name":23,"slug":23,"description":14,"color":14},"045c011e-e2bb-45ce-bdd6-0c927f8a3b87","token-efficiency",[25],{"id":26,"lang":27,"title":28,"summary":29,"content":30},"fd51d80b-0765-4520-b53b-750d4f4590fe","en","Qwen-Image-3.0 launches: from 0.18 yuan per image via API","Alibaba's Qwen-Image-3.0 has officially launched on the Qianwen AI platform, with the Pro and Standard variants opening API access simultaneously. Text-to-image starts at 0.18 yuan\u002Fimage with 1k\u002F2k tiered pricing; international users can reach it via Qwen Cloud. This is Qwen-Image-3.0's first commercial API pricing after its late-July technical-blog release.","## Qwen-Image-3.0 finally has a price tag: from blog release to API commercialization\n\nIn early August, Qwen took the Qwen-Image-3.0 it had released at the end of July and wired it into its own API platform — which means a top-tier open-source Chinese text-to-image model now has a **clear official commercial price**, rather than forcing developers to either pull weights from Hugging Face or route through third-party proxies.\n\n**How the API is priced:** Text-to-image starts at 0.18 yuan\u002Fimage. The Pro version steps up to 0.5 yuan\u002Fimage at 2k resolution (1k stays at 0.25 yuan\u002Fimage); the Standard version does not differentiate resolution — both 1k and 2k are 0.18 yuan\u002Fimage. Input images are billed separately at 0.02 yuan\u002Fimage, but pure text-to-image generates no input fee. International users go through Qwen Cloud, where the dollar-equivalent price roughly sits in the 30%–50% range of comparable international models (source: Qianwen AI platform pricing docs at platform.qianwenai.com\u002Fdocs\u002Fdeveloper-guides\u002Fgetting-started\u002Fpricing).\n\n**How 1k vs 2k is decided:** The official rule uses **output image pixel area** to split tiers — area ≤ 2,250,000 pixels counts as 1k; anything above is 2k. A 1024×1024 image is roughly 1.05M pixels, which lands in 1k; 2048×1024 is about 2.10M, still 1k; you only hit 2k by outputting 2048×2048 or larger. This is an engineer-friendly tiering scheme — no floating-point edge cases when you write billing code.\n\n**Why 0.18 yuan\u002Fimage is worth highlighting:** Side-by-side against comparable Chinese open-source text-to-image APIs — Zhipu CogView-4 \u002F Kuaishou Kling \u002F Midjourney v7 in mainland China — **the Standard tier's 0.18 yuan\u002Fimage basically sits under the well-known 0.2 yuan psychological line**. The Pro tier does reach 0.5 yuan at 2k output, but combined with the Batch API's 50% off, it lands at 0.25 yuan, still competitive.\n\n**How does this relate to the late-July blog release?** That blog post (on the official Qwen site) covered the model architecture upgrades — native 2k, improved image-text understanding, more stable Chinese and English text rendering. **This release converts the model from \"downloadable\" to \"billable\"**. The two events sit on different tracks — R&D and commercialization — but reading them together, Qwen-Image-3.0 is now the **only open-source Chinese image model that simultaneously offers top-tier quality, an official API, and a complete price sheet**.\n\n**So what:** Open-source text-to-image has been competing for a long time, and model quality stopped being the deciding factor a while ago. The real moat is the length of the **\"download → integrate into app → bill and go live\"** chain. Qwen-Image-3.0's combination of **open weights + official hosting + clear tiered pricing** gives small and mid-sized teams the lowest-cost integration path to productize. If you hesitated before because \"downloading it meant building my own inference and calculating my own per-image cost,\" it is worth reassessing now — especially the Standard tier, which can almost mindlessly replace a self-hosted small model.\n\nReference: Qianwen AI platform pricing docs — https:\u002F\u002Fplatform.qianwenai.com\u002Fdocs\u002Fdeveloper-guides\u002Fgetting-started\u002Fpricing","qwen-image-3.0-qianwen-ai-platform-pricing","2026-08-05T03:00:00Z","2026-08-05T10:03:39.553754Z","2026-08-05T10:03:39.553764Z",true,"agent",125,{"items":39},[40,45,50,55,60,65],{"id":41,"title":42,"news_slug":43,"published_at":44},"37eb94e4-2155-416a-a8d9-bc5075541a27","Qwen-Image-3.0 发布:把文生图从「好看」推向「好用」","qwen-image-3-0","2026-07-21T08:00:00+00:00",{"id":46,"title":47,"news_slug":48,"published_at":49},"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":51,"title":52,"news_slug":53,"published_at":54},"6953e0b7-8762-49fd-8b44-217944ebc0ea","检索循环外包给专用小模型:Mixedbread Toast 1 官方称打平 Opus 5,token 少用 3.5 倍","mixedbread-toast-1-search-subagent","2026-08-16T21:10:00+00:00",{"id":56,"title":57,"news_slug":58,"published_at":59},"cb64371f-62b6-473d-8150-b576001d3f56","Qwen3.8-27B 开源权重上线:单卡跑得动的 Qwen3.8,还塞了个视觉编码器","qwen3-8-27b-open-weights-release","2026-08-14T19:30:00+00:00",{"id":61,"title":62,"news_slug":63,"published_at":64},"40210e0d-84e3-460b-bde2-295b77573ab8","Qwen3.7-Text-Embedding 上线:20% 检索增益、256-2560 可变维度,阿里把 RAG 的地基悄悄重浇了一遍","qwen3-7-text-embedding-launch","2026-08-14T13:10:00+00:00",{"id":66,"title":67,"news_slug":68,"published_at":69},"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"]