{"id":2507,"date":"2026-03-04T14:03:41","date_gmt":"2026-03-04T06:03:41","guid":{"rendered":"https:\/\/www.starverse-ai.com\/guide\/archives\/2507"},"modified":"2026-03-04T14:03:41","modified_gmt":"2026-03-04T06:03:41","slug":"rtx-4090%e7%a7%92%e5%87%ba4k%e5%9b%be%ef%bc%81%e6%98%9f%e5%ae%87%e6%99%ba%e7%ae%97%e5%b9%b3%e5%8f%b0%e5%ae%9e%e6%b5%8bstable-diffusion-xl%e5%85%8d%e9%83%a8%e7%bd%b2%e4%b8%80%e9%94%ae%e5%8d%b3%e7%8e%a9","status":"publish","type":"post","link":"https:\/\/www.starverse-ai.com\/guide\/archives\/2507","title":{"rendered":"RTX 4090\u79d2\u51fa4K\u56fe\uff01\u661f\u5b87\u667a\u7b97\u5e73\u53f0\u5b9e\u6d4bStable Diffusion XL\u514d\u90e8\u7f72\u4e00\u952e\u5373\u73a9"},"content":{"rendered":"
\"RTX<\/figure>\n
\n

\u201c24 GB \u663e\u5b58\u53ea\u662f\u8d77\u8dd1\u7ebf\uff0c\u672c\u5730\u8dd1 SDXL 1.0 \u50cf\u5728\u706b\u7089\u91cc\u714e\u663e\u5361\u3002\u201d\u2014\u2014\u4e0a\u5468 Stability AI \u5b98\u65b9\u5f00\u6e90 Stable Diffusion XL 1.0 \u540e\uff0cReddit \u6700\u9ad8\u8d5e\u7684\u8bc4\u8bba\u5982\u6b64\u8c03\u4f83\u3002\u7684\u786e\uff0c\u4e00\u5f20 4K \u5168\u7cbe\u5ea6\u56fe\u5c31\u80fd\u628a RTX 3080 \u7684 10 GB \u77ac\u95f4\u5403\u6ee1\uff0c\u60f3\u8981\u6d41\u7545\u521b\u4f5c\uff0cRTX 4090 \u6210\u4e86\u4e8b\u5b9e\u4e0a\u7684\u201c\u95e8\u7968\u201d\u3002\u53ef 3 \u4e07\u5143\u4e00\u5f20\u7684\u516c\u7248\u5361\u3001\u914d\u5957\u7535\u6e90\u3001\u4e3b\u677f\u3001\u6563\u70ed\u2026\u2026\u8fd8\u6ca1\u5f00\u59cb\u753b\u753b\uff0c\u9884\u7b97\u5148\u98d9\u5230\u516d\u4f4d\u6570\u3002
\n\u6709\u6ca1\u6709\u529e\u6cd5\u628a\u201c\u95e8\u7968\u201d\u53d8\u6210\u201c\u5355\u6b21\u7968\u201d\uff1f\u6211\u4eec\u76ef\u4e0a\u4e86 GPU\u670d\u52a1\u5668\u79df\u7528<\/a><\/strong> \u8d5b\u9053\uff0c\u628a SDXL 1.0 \u642c\u5230\u4e91\u7aef\uff0c\u7ed3\u679c 30 \u79d2\u5c31\u4ea7\u51fa\u4e86\u4e00\u5f20 7680\u00d74320 \u5206\u8fa8\u7387\u7684\u8d5b\u535a\u670b\u514b Chinatown\uff0c\u663e\u5b58\u5360\u7528 22 GB\uff0c\u6e29\u5ea6\u7a33\u5728 65 \u2103\u2014\u2014\u8fd9\u5f20\u201c\u95e8\u7968\u201d\u5728\u661f\u5b87\u667a\u7b97\u5e73\u53f0\u6309\u5c0f\u65f6\u79df\uff0c\u6bcf\u5c0f\u65f6\u4e0d\u5230 4 \u5143\u3002<\/p>\n<\/blockquote>\n

\u70ed\u70b9\u56de\u987e\uff1aSDXL 1.0 \u5f00\u6e90\uff0c\u672c\u5730\u95e8\u69db\u9661\u589e<\/h2>\n

Stability AI \u5728 7 \u6708 26 \u65e5\u7684\u5f00\u6e90\u516c\u544a\u91cc\u660e\u786e\u5199\u9053\uff1a\u201cFull U-Net requires ~16 GB VRAM at 512 px\uff0c4K sampling needs 20 GB+.\u201d \u4e5f\u5c31\u662f\u8bf4\uff0c\u60f3\u5728\u672c\u5730\u8dd1\u5230\u5b98\u65b9\u63a8\u8350\u7684 50 \u6b65\u3001CFG 7.0\u30014K \u8f93\u51fa\uff0cRTX 4080 16 GB \u90fd\u4f1a\u76f4\u63a5\u7206\u663e\u5b58\uff0c\u53ea\u6709 RTX 4090 24 GB \u53ca\u4ee5\u4e0a\u624d\u80fd\u7a33\u4f4f\u3002\u4e8e\u662f\u4e8c\u624b\u5e02\u573a 4090 \u4e00\u591c\u4e4b\u95f4\u6ea2\u4ef7 15%\uff0c\u8d34\u5427\u91cc\u201c\u6c42\u77ff\u8001\u677f\u653e\u5361\u201d\u7684\u5e16\u5b50\u5237\u5c4f\u3002
\n\u4f46\u6bd4\u6ea2\u4ef7\u66f4\u75db\u82e6\u7684\u662f\u201c\u7a7a\u7a97\u671f\u201d\u2014\u2014\u7edd\u5927\u591a\u6570 AI \u753b\u5e08\u4e00\u5929\u53ea\u6709 1\u20132 \u5c0f\u65f6\u9ad8\u5f3a\u5ea6\u51fa\u56fe\uff0c\u5176\u4f59\u65f6\u95f4\u663e\u5361\u95f2\u7f6e\u5403\u7070\u3002\u81ea\u8d2d 4090 \u7684\u6298\u65e7\u6210\u672c\u5374\u6309 24 \u5c0f\u65f6\u8ba1\u7b97\uff0c\u8fd9\u7b14\u8d26\u7b97\u4e0b\u6765\uff0c\u5355\u65e5\u6709\u6548\u6210\u672c\u9ad8\u8fbe 60 \u5143\u3002\u53cd\u89c2 GPU\u4e91\u4e3b\u673a<\/a><\/strong> \u6309\u9700\u8ba1\u8d39\uff0c\u7528\u591a\u5c11\u4ed8\u591a\u5c11\uff0c\u6210\u4e3a\u7406\u6027\u73a9\u5bb6\u7684\u65b0\u9009\u62e9\u3002<\/p>\n

\u5b9e\u6d4b\uff1a\u661f\u5b87\u667a\u7b97 RTX 4090 \u955c\u50cf\u4e00\u952e\u62c9\u8d77<\/h2>\n

\u6211\u4eec\u5728\u661f\u5b87\u667a\u7b97\u63a7\u5236\u53f0\u9009\u62e9\u201cAI \u5e94\u7528\u2014Stable Diffusion XL\u201d\u9884\u88c5\u955c\u50cf\uff0c\u5b9e\u4f8b\u89c4\u683c\u4e3a 8 vCPU + 32 GB RAM + RTX 4090 24 GB\uff0c\u7cfb\u7edf\u76d8 50 GB\uff0c\u5e26\u5bbd 20 Mbps\uff0c\u8ba1\u8d39\u6a21\u5f0f\u6309\u5c0f\u65f6\u3002\u70b9\u51fb\u201c\u521b\u5efa\u201d\u540e 55 \u79d2\uff0c\u5b9e\u4f8b\u72b6\u6001\u53d8\u4e3a\u201c\u8fd0\u884c\u4e2d\u201d\uff0c\u6d4f\u89c8\u5668\u76f4\u63a5\u8df3\u8f6c\u81f3 WebUI \u9875\u9762\uff0c\u65e0\u9700\u624b\u52a8\u88c5 CUDA\u3001PyTorch\u3001xFormers\u3002
\n\u6d4b\u8bd5\u63d0\u793a\u8bcd\uff1a\u201ca retro-futuristic Tokyo street, 4K, ultra-sharp, cinematic lighting, by Greg Rutkowski\u201d\u3002\u53c2\u6570\uff1a\u5206\u8fa8\u7387 7680\u00d74320\uff0c\u91c7\u6837\u6b65\u6570 50\uff0cDPM++ 2M Karras\uff0cCFG 7.0\uff0c\u542f\u7528 attention slicing \u4e0e VAE tiling\u3002\u9996\u6b21\u51fa\u56fe 28 \u79d2\uff0c\u663e\u5b58\u5cf0\u503c 22.4 GB\uff0c\u6e29\u5ea6 65 \u2103\uff0c\u98ce\u6247 55%\uff0c\u566a\u97f3\u2026\u2026\u54e6\u5bf9\uff0c\u4e91\u7aef\u6ca1\u6709\u98ce\u6247\u5435\u4f60\u3002
\n\u8fde\u7eed 10 \u5f20\u56fe\u5e73\u5747\u8017\u65f6 31 \u79d2\uff0c\u663e\u5b58\u56de\u6536\u7a33\u5b9a\uff0c\u65e0 Out Of Memory\u3002\u5bf9\u6bd4\u672c\u5730 3080 Ti \u76f4\u63a5\u62a5\u9519\u30014080 \u88ab\u8feb\u964d\u5230 2K\uff0c\u4e91\u7aef\u7684 4090 \u53ef\u4ee5\u8bf4\u662f\u201c\u6ee1\u8840\u89e3\u9501\u201d\u3002<\/p>\n

\u6559\u7a0b\uff1a\u6ce8\u518c\u5230\u51fa\u56fe 3 \u6b65\uff0cLoRA\u3001ControlNet \u90fd\u88c5\u597d\u4e86<\/h2>\n
    \n
  1. \u6ce8\u518c\uff1a\u8bbf\u95ee \u661f\u5b87\u667a\u7b97\u5b98\u7f51<\/a><\/strong>\uff0c\u624b\u673a\u9a8c\u8bc1\u7801 10 \u79d2\u5b8c\u6210\uff0c\u65b0\u7528\u6237\u76f4\u63a5\u5230\u8d26 10 \u5143\u4f53\u9a8c\u91d1\uff0c\u53ef\u8dd1 2.5 \u5c0f\u65f6 RTX 4090\u3002 <\/li>\n
  2. \u9009\u578b\uff1a\u63a7\u5236\u53f0\u9009\u201cGPU\u670d\u52a1\u5668\u79df\u7528\u2014RTX 4090\u2014AI \u5e94\u7528\u955c\u50cf\u2014Stable Diffusion XL\u201d\uff0c\u7cfb\u7edf\u5df2\u9884\u88c5 Python 3.10\u3001PyTorch 2.1\u3001CUDA 12.1\u3001WebUI 1.5\u3001LoRA \u6269\u5c55\u3001ControlNet 1.1.4\uff0c\u6a21\u578b\u5e93\u9ed8\u8ba4\u6302\u8f7d 10 GB+ \u516c\u5171\u8d44\u6e90\u5305\uff0c\u5305\u62ec JuggernautXL\u3001RealVisXL\u3001AnimeXL \u7b49 20 \u79cd\u98ce\u683c\u3002 <\/li>\n
  3. \u51fa\u56fe\uff1a\u5b9e\u4f8b\u542f\u52a8\u540e\u70b9\u51fb\u201cWebUI \u8bbf\u95ee\u5730\u5740\u201d\uff0c\u7c98\u8d34\u63d0\u793a\u8bcd\u5373\u53ef\u751f\u6210\uff1b\u9700\u8981 LoRA \u53ea\u9700\u628a lora \u6587\u4ef6\u4e0a\u4f20\u5230 \/workspace\/stable-diffusion-webui\/models\/Lora<\/code>\uff0c\u5237\u65b0\u5217\u8868\u5373\u65f6\u8c03\u7528\uff1bControlNet \u6a21\u578b\u5df2\u5185\u7f6e Canny\u3001OpenPose\u3001Depth\uff0c4K \u8fb9\u7f18\u68c0\u6d4b\u53ea\u9700 8 \u79d2\u9884\u5904\u7406\u3002 <\/li>\n<\/ol>\n

    \u5168\u7a0b\u65e0\u9700\u6572\u4e00\u884c\u547d\u4ee4\uff0c\u771f\u6b63\u201c\u4e00\u952e\u5373\u73a9\u201d\u3002\u7528\u5b8c\u76f4\u63a5\u5728\u63a7\u5236\u53f0\u201c\u91ca\u653e\u5b9e\u4f8b\u201d\uff0c\u6570\u636e\u81ea\u52a8\u8f6c\u5b58 \u4e91\u786c\u76d8<\/a><\/strong>\uff0c\u4e0b\u6b21\u5f00\u673a\u7ee7\u7eed\u521b\u4f5c\uff0c\u6a21\u578b\u548c\u8349\u7a3f\u90fd\u5728\u3002<\/p>\n

    \u6210\u672c\u8d26\uff1a\u6309\u5c0f\u65f6 3.6 \u5143 vs \u81ea\u8d2d 3 \u4e07\u5143<\/h2>\n

    \u4ee5\u4e00\u5e74 500 \u5c0f\u65f6\u9ad8\u5f3a\u5ea6\u521b\u4f5c\u8ba1\u7b97\uff1a
    \n– \u81ea\u8d2d 4090 \u6574\u673a\uff1a\u663e\u5361 3 \u4e07 + \u5e73\u53f0 5 \u5343 + \u7535\u8d39 1 \u5343 = 3.6 \u4e07\u5143\uff0c\u6bcf\u5c0f\u65f6\u6210\u672c 72 \u5143\uff1b
    \n– \u661f\u5b87\u667a\u7b97 4090     GPU\u4e91\u4e3b\u673a<\/a><\/strong>\uff1a3.6 \u5143\/\u5c0f\u65f6\uff0c500 \u5c0f\u65f6\u5408\u8ba1 1800 \u5143\uff0c\u6210\u672c\u76f4\u964d 80%\u3002
    \n\u82e5\u53ea\u8dd1 100 \u5c0f\u65f6\uff0c\u4e91\u7aef\u4ec5\u9700 360 \u5143\uff0c\u76f8\u5f53\u4e8e\u4e00\u5f20 4090 \u7684 1%\uff0c\u628a\u8d44\u91d1\u7559\u7ed9\u521b\u610f\u800c\u975e\u6298\u65e7\u3002\u5e73\u53f0\u540c\u65f6\u63d0\u4f9b\u5305\u6708 8 \u6298\u3001\u5305\u5e74 5 \u6298\u7684\u5e38\u9a7b\u4f18\u60e0\uff0c\u957f\u671f\u9879\u76ee\u4e5f\u80fd\u627e\u5230\u6700\u4f18\u89e3\u3002<\/p>\n

    \u5f69\u86cb\uff1a10 GB+ \u98ce\u683c\u6a21\u578b\u5305\uff0c\u76f4\u63a5\u8c03\u7528\u514d\u4e0b\u8f7d<\/h2>\n

    \u591a\u6570\u4e91\u5382\u5546\u53ea\u7ed9\u88f8\u673a\uff0c\u6a21\u578b\u8fd8\u5f97\u81ea\u5df1\u62c9\uff0c\u52a8\u8f84 20 GB \u7684 SDXL \u57fa\u7840\u6a21\u578b\u5148\u5360\u6389\u534a\u5c0f\u65f6\u3002\u661f\u5b87\u667a\u7b97\u628a\u516c\u5171\u6a21\u578b\u6c60\u76f4\u63a5\u6302\u8f7d\u5230 \/public\/models<\/code>\uff0c\u76ee\u5f55\u91cc\u9664\u4e86\u5b98\u65b9 sd_xl_base_1.0\u3001sd_xl_refiner_1.0\uff0c\u8fd8\u6709\u793e\u533a\u70ed\u95e8 JuggernautXL\u3001DreamShaperXL\u3001ProtoVisionXL\uff0c\u4ee5\u53ca 60 \u4f59\u6b3e LoRA\uff1a\u56fd\u98ce\u6c34\u58a8\u3001\u50cf\u7d20\u6e38\u620f\u3001\u8d5b\u535a\u673a\u7532\u30013D \u76f2\u76d2\u2026\u2026\u8c03\u7528\u65f6\u53ea\u9700\u5728 WebUI \u6a21\u578b\u680f\u4e0b\u62c9\u9009\u62e9\uff0c0 \u6d41\u91cf\u30010 \u7b49\u5f85\u3002
    \n\u6b64\u5916\uff0c\u5e73\u53f0\u8fd8\u63d0\u4f9b [\u6a21\u578b\u548c\u6570\u636e\u96c6](https:\/\/www.starverse-ai.com\/node\/019b88ac-286a-70a3-bafa-cfa47c851b4d)<\/code> \u9875\u9762\uff0c\u652f\u6301\u4e00\u952e\u8f6c\u5b58\u5230\u81ea\u5df1\u7684     \u4e91\u5b58\u50a8<\/a><\/strong>\uff0c\u540e\u7eed\u8bad\u7ec3\u6216\u5fae\u8c03\u4e0d\u7528\u518d\u5230\u5904\u627e\u8d44\u6e90\u3002\u5bf9\u4e8e\u9ad8\u6821\u56e2\u961f\uff0c\u661f\u5b87\u667a\u7b97\u8fd8\u5f00\u653e ImageNet\u3001LAION-5B \u7b49\u516c\u5f00\u6570\u636e\u96c6\u6302\u8f7d\uff0c\u8282\u7701 TB \u7ea7\u4e0b\u8f7d\u65f6\u95f4\u3002<\/p>\n

    \u5c3e\u58f0\uff1a\u628a\u521b\u610f\u4ece\u786c\u4ef6\u67b7\u9501\u91cc\u89e3\u653e<\/h2>\n

    Stable Diffusion XL 1.0 \u53ea\u662f\u5f00\u59cb\uff0c\u540e\u7eed\u8fd8\u5c06\u6709 8K \u89c6\u9891 Diffusion\u3001LLM+Diffusion \u8054\u5408\u751f\u6210\uff0c\u6bcf\u4e00\u6b21\u8fed\u4ee3\u90fd\u5728\u628a\u663e\u5b58\u9700\u6c42\u63a8\u5411\u65b0\u9ad8\u5ea6\u3002\u4e0e\u5176\u8ffd\u7740\u663e\u5361\u6da8\u4ef7\u8dd1\uff0c\u4e0d\u5982\u628a\u91cd\u8d44\u4ea7\u4ea4\u7ed9\u4e91\u7aef\uff0c\u8ba9\u521b\u610f\u968f\u65f6\u4e0a\u7ebf\u3002
    \n\u73b0\u5728\u6ce8\u518c     \u661f\u5b87\u667a\u7b97<\/a><\/strong>\uff0c10 \u5143\u4f53\u9a8c\u91d1\u76f4\u63a5\u5230\u8d26\uff0cRTX 4090 \u8dd1 2.5 \u5c0f\u65f6\uff0c4K \u5927\u56fe\u60f3\u753b\u5c31\u753b\u3002
    \n\u70b9\u51fb\u201c\u514d\u8d39\u6ce8\u518c\u201d\uff0c\u4e0b\u4e00\u5f20 4K \u795e\u56fe\uff0c30 \u79d2\u540e\u5c31\u662f\u4f60\u7684\u58c1\u7eb8\u3002<\/p>\n","protected":false},"excerpt":{"rendered":"

    \u201c24 GB \u663e\u5b58\u53ea\u662f\u8d77\u8dd1\u7ebf\uff0c\u672c\u5730\u8dd1 SDXL 1.0 \u50cf\u5728…<\/p>\n","protected":false},"author":2,"featured_media":2506,"comment_status":"","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-2507","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-zixun"],"views":141,"_links":{"self":[{"href":"https:\/\/www.starverse-ai.com\/guide\/wp-json\/wp\/v2\/posts\/2507","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.starverse-ai.com\/guide\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.starverse-ai.com\/guide\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.starverse-ai.com\/guide\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/www.starverse-ai.com\/guide\/wp-json\/wp\/v2\/comments?post=2507"}],"version-history":[{"count":0,"href":"https:\/\/www.starverse-ai.com\/guide\/wp-json\/wp\/v2\/posts\/2507\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.starverse-ai.com\/guide\/wp-json\/wp\/v2\/media\/2506"}],"wp:attachment":[{"href":"https:\/\/www.starverse-ai.com\/guide\/wp-json\/wp\/v2\/media?parent=2507"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.starverse-ai.com\/guide\/wp-json\/wp\/v2\/categories?post=2507"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.starverse-ai.com\/guide\/wp-json\/wp\/v2\/tags?post=2507"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}