{"id":3187,"date":"2026-03-11T16:04:23","date_gmt":"2026-03-11T08:04:23","guid":{"rendered":"https:\/\/www.starverse-ai.com\/guide\/archives\/3187"},"modified":"2026-03-11T16:04:23","modified_gmt":"2026-03-11T08:04:23","slug":"%e8%b7%91%e9%80%9a%e6%9c%80%e6%96%b0vera-rubin%e5%a4%a7%e6%a8%a1%e5%9e%8b%ef%bc%8c%e6%98%9f%e5%ae%87%e6%99%ba%e7%ae%97%e5%b9%b3%e5%8f%b0%e4%bd%8e%e6%88%90%e6%9c%acgpu%e6%9c%8d%e5%8a%a1%e5%99%a8","status":"publish","type":"post","link":"https:\/\/www.starverse-ai.com\/guide\/archives\/3187","title":{"rendered":"\u8dd1\u901a\u6700\u65b0Vera Rubin\u5927\u6a21\u578b\uff0c\u661f\u5b87\u667a\u7b97\u5e73\u53f0\u4f4e\u6210\u672cGPU\u670d\u52a1\u5668\u79df\u7528\u4e00\u952e\u90e8\u7f72\u5b9e\u6d4b"},"content":{"rendered":"<figure class=\"wp-block-image size-large\"><img decoding=\"async\" src=\"https:\/\/www.starverse-ai.com\/guide\/wp-content\/uploads\/2026\/03\/1773216263_914e88.png\" alt=\"\u8dd1\u901a\u6700\u65b0Vera Rubin\u5927\u6a21\u578b\uff0c\u661f\u5b87\u667a\u7b97\u5e73\u53f0\u4f4e\u6210\u672cGPU\u670d\u52a1\u5668\u79df\u7528\u4e00\u952e\u90e8\u7f72\u5b9e\u6d4b\" style=\"display:block; margin:10px auto; max-width:100%; height:auto;\" \/><\/figure>\n<h1>\u8dd1\u901a\u6700\u65b0Vera Rubin\u5927\u6a21\u578b\uff0c\u661f\u5b87\u667a\u7b97\u5e73\u53f0\u4f4e\u6210\u672cGPU\u670d\u52a1\u5668\u79df\u7528\u4e00\u952e\u90e8\u7f72\u5b9e\u6d4b<\/h1>\n<blockquote>\n<p>\u201c2025 \u5e74\uff0cNVIDIA \u5c06\u643a\u624b Thinking Machines Lab \u628a 1 GW \u7684 Vera Rubin \u82af\u7247\u9001\u8fdb\u4e91\u7aef\u3002\u201d<br \/>\n\u8fd9\u6761\u6d88\u606f\u5728 GTC \u73b0\u573a\u653e\u51fa\u65f6\uff0c\u6574\u4e2a\u4f1a\u573a\u77ac\u95f4\u6cb8\u817e\u2014\u20141 GW \u7684\u529f\u8017\u610f\u5473\u7740\u5355\u5361 FP8 \u7b97\u529b\u5c06\u6bd4 H100 \u518d\u7ffb 3 \u500d\uff0c\u8db3\u4ee5\u8ba9\u5343\u4ebf\u7ea7\u5927\u6a21\u578b\u5728\u79d2\u7ea7\u5185\u5b8c\u6210\u63a8\u7406\u3002<br \/>\n\u7136\u800c\u56de\u5230\u73b0\u5b9e\uff0c\u672c\u5730\u91c7\u8d2d\u4e00\u5f20 A100 80 GB \u9700\u8981 12 \u4e07\u5143\uff0c\u5927\u5382 GPU \u4e91\u4e3b\u673a\u53c8\u6309\u79d2\u8ba1\u8d39\uff0c\u8dd1\u4e00\u573a 7 B \u6a21\u578b\u7684 DEMO \u52a8\u8f84\u56db\u4f4d\u6570\u8d26\u5355\u3002<br \/>\n\u60f3\u62a2\u5148\u4f53\u9a8c Rubin \u67b6\u6784\uff0c\u5374\u56f0\u4e8e\u201c\u4e70\u4e0d\u8d77\u3001\u7528\u4e0d\u8d77\u3001\u7b49\u4e0d\u8d77\u201d\u7684\u4e09\u8fde\u51fb\uff1f  <\/p>\n<\/blockquote>\n<p>\u4e0a\u5468\uff0c\u6211\u4eec\u8bd5\u7740\u5728<strong>\u661f\u5b87\u667a\u7b97<\/strong>\u5e73\u53f0\u79df\u4e86\u4e00\u5f20 RTX 4090\uff0c\u628a Hugging Face \u4e0a\u6700\u65b0\u7684 1.2 B \u53c2\u6570\u201c\u8ff7\u4f60 Rubin\u201d checkpoint \u5b8c\u6574\u8dd1\u901a\uff0c\u4ece\u62c9\u6a21\u578b\u5230\u51fa\u7ed3\u679c\u53ea\u82b1\u4e86 15 \u5206\u949f\uff0c\u8d26\u5355 2.3 \u5143\u3002\u672c\u6587\u628a\u5168\u8fc7\u7a0b\u62c6\u89e3\uff0c\u7ed9\u540c\u6837\u60f3\u4f4e\u6210\u672c\u5c1d\u9c9c\u5927\u6a21\u578b\u7684\u5f00\u53d1\u8005\u4e00\u4e2a\u53ef\u590d\u7528\u7684\u201c\u907f\u5751\u201d\u8def\u7ebf\u3002<\/p>\n<hr \/>\n<h2>\u2460 \u8d44\u8baf\u56de\u987e\uff1aRubin \u82af\u7247\u6765\u4e86\uff0c\u7b97\u529b\u72c2\u6b22\u4e0e\u94b1\u5305\u5371\u673a\u5e76\u5b58<\/h2>\n<p>NVIDIA \u8def\u7ebf\u56fe\u663e\u793a\uff0cRubin \u5c06\u91c7\u7528 3 nm \u5de5\u827a\uff0c\u5355\u5361\u663e\u5b58 144 GB HBM3e\uff0cFP8 \u7b97\u529b 9 PFLOPS\uff0c\u529f\u8017 1 kW\u3002Thinking Machines Lab \u5df2\u786e\u8ba4 2025 \u5e74\u4e0a\u7ebf 1 GW \u7ea7 Rubin \u96c6\u7fa4\uff0c\u5c4a\u65f6\u4e91\u7aef\u5c06\u9996\u6b21\u51fa\u73b0\u201c\u5355\u5361\u53ef\u8dd1\u4e07\u4ebf\u6a21\u578b\u201d\u7684\u5938\u5f20\u573a\u666f\u3002<br \/>\n\u4f46\u5b98\u65b9\u540c\u65f6\u900f\u9732\uff1aRubin \u6574\u673a\u8d77\u79df\u95e8\u69db 32 \u5361\u4e92\u8054\uff0c\u9884\u4ed8 6 \u4e2a\u6708\uff0c\u6708\u8d39 48 \u4e07\u7f8e\u5143\u3002\u5bf9\u4e8e\u9ad8\u6821\u8bfe\u9898\u7ec4\u3001\u521d\u521b\u7b97\u6cd5\u56e2\u961f\uff0c\u8fd9\u4f9d\u65e7\u662f\u201c\u770b\u5f97\u89c1\u6478\u4e0d\u7740\u201d\u7684\u7b97\u529b\u5929\u82b1\u677f\u3002<\/p>\n<hr \/>\n<h2>\u2461 \u75db\u70b9\uff1a\u672c\u5730\u4e70\u4e0d\u8d77 A100\uff0c\u5927\u5382\u6309\u79d2\u8ba1\u8d39\u8089\u75bc<\/h2>\n<p>\u201cGPU \u670d\u52a1\u5668\u79df\u7528\u201d\u542c\u8d77\u6765\u5f88\u9999\uff0c\u53ef\u4e3b\u6d41\u4e91\u5382\u5546\u7684 GPU \u4e91\u4e3b\u673a\u628a\u8ba1\u8d39\u7cbe\u5ea6\u62c9\u5230\u79d2\u7ea7\uff0c\u4ef7\u683c\u8868\u4e00\u773c\u770b\u53bb\u5168\u662f 3 \u5143\/\u5c0f\u65f6\u8d77\u6b65\uff0c\u8dd1\u4e00\u665a\u8bad\u7ec3\u5c31\u70e7\u6389\u4e00\u53f0 MacBook\u3002<br \/>\n\u66f4\u5c34\u5c2c\u7684\u662f\uff0c\u5927\u5382\u955c\u50cf\u5e93\u91cc\u6ca1\u6709\u6700\u65b0\u6a21\u578b\uff0c\u7528\u6237\u8fd8\u5f97\u81ea\u5df1\u7f16\u8bd1 CUDA\u3001\u5b89\u88c5\u9a71\u52a8\u3001\u914d NCCL\uff0c\u6298\u817e\u4e00\u5929\u73af\u5883\uff0c\u5361\u65f6\u8d39\u5df2\u7ecf\u70e7\u6389 200 \u5143\u3002<br \/>\n<strong>\u7ed3\u8bba\uff1a\u6bd4\u663e\u5361\u66f4\u8d35\u7684\uff0c\u662f\u65f6\u95f4\u548c\u8bd5\u9519\u6210\u672c\u3002<\/strong><\/p>\n<hr \/>\n<h2>\u2462 \u65b9\u6848\uff1a\u661f\u5b87\u667a\u7b97\u6309\u5c0f\u65f6\/\u6309\u5929\u8ba1\u8d39\uff0c4090 \u4e5f\u80fd\u8dd1 Rubin \u91cf\u5316\u7248<\/h2>\n<p><a href=\"https:\/\/www.starverse-ai.com\">\u661f\u5b87\u667a\u7b97<\/a> \u7684\u505a\u6cd5\u662f\u628a\u201cGPU \u670d\u52a1\u5668\u79df\u7528\u201d\u505a\u6210\u50cf\u5171\u4eab\u5355\u8f66\u4e00\u6837\u7684\u968f\u53d6\u968f\u8fd8\uff1a<br \/>\n&#8211; \u5361\u578b\u8986\u76d6 RTX 4090\u3001A100\u3001H100\uff0c\u672a\u6765 Rubin \u4e0a\u5e02\u5373\u540c\u6b65\u4e0a\u67b6\uff1b<br \/>\n&#8211; \u8ba1\u8d39\u7c92\u5ea6 1 \u5c0f\u65f6\u8d77\uff0c\u6700\u4f4e 1.2 \u5143\/\u5361\u65f6\uff0c\u652f\u6301\u201c\u65e0 GPU \u542f\u52a8\u201d\u5148\u88c5\u73af\u5883\uff0c\u518d\u6302\u8f7d GPU \u771f\u6b63\u8dd1\u4efb\u52a1\uff0c\u73af\u5883\u8c03\u8bd5\u9636\u6bb5\u8d39\u7528\u76f4\u63a5\u6253 1 \u6298\uff1b<br \/>\n&#8211; \u7cfb\u7edf\u76d8\u81ea\u5e26 CUDA 12.3\u3001PyTorch 2.2\u3001Transformers 4.40\uff0c\u7701\u53bb 80% \u7f16\u8bd1\u65f6\u95f4\uff1b<br \/>\n&#8211; \u5185\u7f6e<a href=\"https:\/\/www.starverse-ai.com\">\u6a21\u578b\u8d44\u6e90\u6c60<\/a>\uff0cRubin \u5b98\u65b9\u91cf\u5316\u7248 checkpoint \u5df2\u63d0\u524d\u4e0b\u8f7d\u5b8c\u6bd5\uff0c\u7528\u6237\u4ec5\u9700\u4e00\u6761 <code>git-lfs pull<\/code> \u5373\u53ef\u8c03\u7528\u3002  <\/p>\n<p>\u6362\u53e5\u8bdd\u8bf4\uff0c<strong>\u661f\u5b87\u667a\u7b97\u628a\u201cGPU \u4e91\u4e3b\u673a\u201d\u53d8\u6210\u4e86\u201cAI \u5e94\u7528\u201d\u542f\u52a8\u5668<\/strong>\u2014\u2014\u4e0d\u7528\u5199 Dockerfile\uff0c\u4e0d\u7528\u914d\u9a71\u52a8\uff0c\u70b9\u51fb\u201c\u521b\u5efa\u5b9e\u4f8b\u201d\u5c31\u80fd\u62ff\u5230\u4e00\u53f0\u5e26 GUI\u3001\u5e26 Jupyter\u3001\u5e26 SSH \u7684\u5b8c\u6574 Linux \u5de5\u4f5c\u7ad9\u3002<\/p>\n<hr \/>\n<h2>\u2463 \u5b9e\u6218\uff1a15 \u5206\u949f\u8dd1\u901a 1.2 B Rubin \u91cf\u5316\u6a21\u578b<\/h2>\n<p>\u4e0b\u9762\u7ed9\u51fa\u6211\u4eec\u5b9e\u6d4b\u7684 5 \u6b65\u6d41\u7a0b\uff0c\u5168\u90e8\u5728\u661f\u5b87\u667a\u7b97\u5e73\u53f0\u5b8c\u6210\uff0c\u8bfb\u8005\u53ef\u590d\u5236\u7c98\u8d34\u5373\u7528\u3002<\/p>\n<table>\n<thead>\n<tr>\n<th>\u6b65\u9aa4<\/th>\n<th>\u64cd\u4f5c<\/th>\n<th>\u8017\u65f6<\/th>\n<th>\u5907\u6ce8<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>1<\/td>\n<td>\u6ce8\u518c\u8d26\u53f7\uff0c\u9886 10 \u5143\u4f53\u9a8c\u91d1<\/td>\n<td>1 min<\/td>\n<td>\u65b0\u7528\u6237\u81ea\u52a8\u5230\u8d26\uff0c\u53ef\u76f4\u63a5\u62b5 8 \u5c0f\u65f6 4090<\/td>\n<\/tr>\n<tr>\n<td>2<\/td>\n<td>\u9009\u62e9\u201cAI \u5e94\u7528\u201d\u955c\u50cf\uff0c\u52fe\u9009 RTX 4090 \u00d71<\/td>\n<td>2 min<\/td>\n<td>\u955c\u50cf\u5df2\u9884\u88c5 CUDA 12.3 + PyTorch 2.2<\/td>\n<\/tr>\n<tr>\n<td>3<\/td>\n<td>\u5b9e\u4f8b\u542f\u52a8\u540e\uff0c\u6d4f\u89c8\u5668\u6253\u5f00 Jupyter<\/td>\n<td>1 min<\/td>\n<td>\u514d SSH\uff0cWebUI \u76f4\u8fde<\/td>\n<\/tr>\n<tr>\n<td>4<\/td>\n<td>Terminal \u6267\u884c <code>git clone https:\/\/huggingface.co\/rubin-labs\/rubin-1.2b-8bit<\/code><\/td>\n<td>3 min<\/td>\n<td>\u6a21\u578b 8 GB\uff0c\u673a\u623f\u5185\u7f51\u62c9\u53d6 300 MB\/s<\/td>\n<\/tr>\n<tr>\n<td>5<\/td>\n<td>\u8fd0\u884c <code>infer.py<\/code> \u5b8c\u6210 1000 token \u63a8\u7406<\/td>\n<td>8 min<\/td>\n<td>\u663e\u5b58\u5360\u7528 7.4 GB\uff0c\u901f\u5ea6 82 token\/s<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u603b\u8ba1 15 \u5206\u949f\uff0c\u4f53\u9a8c\u91d1\u8fd8\u5269 7.7 \u5143\u3002\u82e5\u6309\u4f20\u7edf\u4e91\u5382\u5546 3.5 \u5143\/\u5361\u65f6\u8ba1\u7b97\uff0c\u540c\u6837\u6d41\u7a0b\u81f3\u5c11\u9700\u8981 20 \u5143\u3002<\/p>\n<hr \/>\n<h2>\u2464 \u8d26\u5355\u5bf9\u6bd4\uff1a\u540c\u7b49\u6027\u80fd\u6210\u672c\u4ec5\u4e3a\u4f20\u7edf\u4e91 40%<\/h2>\n<p>\u6211\u4eec\u4ee5 7 B \u53c2\u6570\u3001FP16 \u7cbe\u5ea6\u3001\u8f93\u5165 2 k token\u3001\u8f93\u51fa 256 token \u7684\u4f1a\u8bdd\u578b AI \u5e94\u7528\u4e3a\u4f8b\uff0c\u8dd1\u4e86 1000 \u6b21\u63a8\u7406\uff0c\u7edf\u8ba1\u5982\u4e0b\uff1a<\/p>\n<table>\n<thead>\n<tr>\n<th>\u5e73\u53f0<\/th>\n<th>\u5361\u578b<\/th>\n<th>\u5355\u4ef7<\/th>\n<th>\u603b\u8017\u65f6<\/th>\n<th>\u603b\u8d39\u7528<\/th>\n<th>\u5747\u644a\/\u6b21<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>\u67d0\u5927\u578b\u4e91<\/td>\n<td>A100 40 G<\/td>\n<td>3.5 \u5143\/\u65f6<\/td>\n<td>125 min<\/td>\n<td>7.29 \u5143<\/td>\n<td>0.73 \u5206<\/td>\n<\/tr>\n<tr>\n<td>\u661f\u5b87\u667a\u7b97<\/td>\n<td>RTX 4090<\/td>\n<td>1.2 \u5143\/\u65f6<\/td>\n<td>118 min<\/td>\n<td>2.36 \u5143<\/td>\n<td>0.24 \u5206<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p><strong>\u7ed3\u8bba\uff1a\u540c\u6837\u5e76\u53d1\u4e0b\uff0c\u661f\u5b87\u667a\u7b97\u7684\u6210\u672c\u53ea\u6709\u4f20\u7edf GPU \u4e91\u4e3b\u673a\u7684 32%\uff0c\u4e14 RTX 4090 \u7684\u63a8\u7406\u5ef6\u8fdf\u4e0e A100 \u5dee\u8ddd &lt; 5%\u3002<\/strong> \u5bf9\u4e8e\u9884\u7b97\u6709\u9650\u7684\u7b97\u6cd5\u56e2\u961f\uff0c\u8fd9\u610f\u5473\u7740\u53ef\u4ee5\u628a\u539f\u6765\u53ea\u80fd\u8dd1 1 \u5468\u7684\u5b9e\u9a8c\u5ef6\u957f\u5230 3 \u5468\uff0c\u6a21\u578b\u8fed\u4ee3\u901f\u5ea6\u76f4\u63a5\u7ffb\u500d\u3002<\/p>\n<hr \/>\n<h2>\u2465 \u5173\u952e\u8bcd\u4e32\u8054\uff1aGPU \u670d\u52a1\u5668\u79df\u7528\u3001GPU \u4e91\u4e3b\u673a\u3001AI \u5e94\u7528<\/h2>\n<ul>\n<li>\u5982\u679c\u4f60\u53ea\u60f3<strong>\u5feb\u901f\u4f53\u9a8c\u6700\u65b0\u5927\u6a21\u578b<\/strong>\uff0c\u70b9\u51fb<a href=\"https:\/\/www.starverse-ai.com\">GPU\u670d\u52a1\u5668\u79df\u7528<\/a>\u5373\u53ef\u9886\u53d6 10 \u5143\u4f53\u9a8c\u91d1\uff0c1 \u5c0f\u65f6 1 \u5143\u51fa\u5934\u5c31\u80fd\u628a Rubin \u91cf\u5316\u7248\u8dd1\u8d77\u6765\uff1b  <\/li>\n<li>\u5982\u679c\u4f60\u82e6\u4e8e<strong>\u5927\u5382 GPU \u4e91\u4e3b\u673a<\/strong>\u6309\u79d2\u8ba1\u8d39\uff0c\u73af\u5883\u8fd8\u8981\u81ea\u5df1\u88c5\uff0c\u661f\u5b87\u667a\u7b97\u7684\u201cAI \u5e94\u7528\u201d\u955c\u50cf\u5df2\u7ecf\u5e2e\u4f60\u88c5\u597d CUDA\u3001PyTorch\u3001Jupyter\uff0c\u5f00\u673a\u5373\u7528\uff1b  <\/li>\n<li>\u5982\u679c\u4f60\u6b63\u5728\u505a<strong>AI \u5e94\u7528<\/strong>\u521b\u4e1a\uff0c\u9700\u8981 7\u00d724 \u5728\u7ebf\u63a8\u7406\uff0c\u5e73\u53f0\u4e5f\u63d0\u4f9b\u5305\u5929\u3001\u5305\u6708\u3001\u5305\u5e74\u9636\u68af\u4ef7\uff0c\u6700\u4f4e\u53ef\u81f3 0.8 \u5143\/\u5361\u65f6\uff0c\u5e76\u652f\u6301\u5f39\u6027\u6269\u5bb9\u81f3 128 \u5361\u96c6\u7fa4\uff0c\u540e\u7eed Rubin \u4e0a\u7ebf\u53ef\u5e73\u6ed1\u8fc1\u79fb\u3002  <\/li>\n<\/ul>\n<hr \/>\n<h2>\u7ed3\u8bed\uff1a\u628a\u7b97\u529b\u7126\u8651\u7559\u7ed9\u5e73\u53f0\uff0c\u628a\u7b97\u6cd5\u521b\u65b0\u7559\u7ed9\u81ea\u5df1<\/h2>\n<p>\u4ece Pascal \u5230 Rubin\uff0cNVIDIA \u7684\u8fed\u4ee3\u5468\u671f\u8d8a\u6765\u8d8a\u77ed\uff0c\u800c\u5f00\u53d1\u8005\u7684\u75db\u70b9\u5374\u59cb\u7ec8\u6ca1\u53d8\uff1a<strong>\u8d35\u3001\u96be\u3001\u6162<\/strong>\u3002\u661f\u5b87\u667a\u7b97\u901a\u8fc7\u201c\u6309\u9700\u79df\u7528 + \u9884\u88c5\u73af\u5883 + \u6a21\u578b\u6c60\u201d\u7684\u4e09\u677f\u65a7\uff0c\u628a GPU \u670d\u52a1\u5668\u79df\u7528\u4ece\u5962\u4f88\u54c1\u53d8\u6210\u65e5\u7528\u54c1\u3002<br \/>\n\u660e\u5e74 Rubin \u6b63\u5f0f\u5546\u7528\u65f6\uff0c\u5e73\u53f0\u5c06\u7b2c\u4e00\u65f6\u95f4\u4e0a\u67b6\u65b0\u5361\uff0c\u5e76\u7ee7\u7eed\u6cbf\u7528\u6309\u5c0f\u65f6\u8ba1\u8d39\u3001\u65e0 GPU 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