{"id":892,"date":"2026-10-14T22:48:33","date_gmt":"2026-10-14T13:48:33","guid":{"rendered":"https:\/\/www.kkoc.org\/?p=892"},"modified":"2026-10-14T23:06:33","modified_gmt":"2026-10-14T14:06:33","slug":"rtx-5070-ti-vs-rtx-pro-4000-blackwell-%ec%8a%a4%ed%8e%99-%eb%b9%84%ea%b5%90-%eb%b0%8f-ai-%ed%99%9c%ec%9a%a9-%eb%b6%84%ec%84%9d","status":"publish","type":"post","link":"https:\/\/www.kkoc.org\/?p=892","title":{"rendered":"RTX 5070 Ti vs RTX PRO 4000 Blackwell \uc2a4\ud399 \ube44\uad50 \ubc0f AI \ud65c\uc6a9 \ubd84\uc11d"},"content":{"rendered":"\n\n\n

AI \ubaa8\ub378 \ud559\uc2b5\uacfc LLM \ucd94\ub860\uc6a9 GPU\ub97c \uad6c\uc131\ud560 \ub54c GeForce RTX 5070 Ti<\/strong>\uc640 NVIDIA RTX PRO 4000 Blackwell<\/strong> \uc911 \uc5b4\ub5a4 \uc81c\ud488\uc774 \ub354 \uc801\ud569\ud55c\uc9c0 \ube44\uad50\ud574 \ubcf4\uc558\uc2b5\ub2c8\ub2e4.<\/p>\n\n\n\n

\ub450 \uc81c\ud488 \ubaa8\ub450 NVIDIA\uc758 \ucd5c\uc2e0 Blackwell \uc544\ud0a4\ud14d\ucc98\ub97c \uae30\ubc18\uc73c\ub85c \ud558\uc9c0\ub9cc, \uc81c\ud488\uc758 \uc131\uaca9\uc740 \uc0c1\ub2f9\ud788 \ub2e4\ub985\ub2c8\ub2e4.<\/p>\n\n\n\n

RTX 5070 Ti\ub294 \ub192\uc740 \uc5f0\uc0b0 \uc131\ub2a5\uacfc \uac00\uaca9 \ub300\ube44 \uc131\ub2a5\uc744 \uc911\uc2dc\ud55c \uc18c\ube44\uc790\uc6a9 GPU\uc774\uba70, RTX PRO 4000 Blackwell\uc740 \ub354 \ud070 VRAM\uacfc ECC \uba54\ubaa8\ub9ac, \uc6cc\ud06c\uc2a4\ud14c\uc774\uc158 \uc548\uc815\uc131\uc744 \uc911\uc2dc\ud55c \uc804\ubb38\uac00\uc6a9 GPU\uc785\ub2c8\ub2e4.<\/p>\n\n\n\n

\n\n\n\n

1. \uc8fc\uc694 \uc0ac\uc591 \ube44\uad50<\/h2>\n\n\n\n
\uad6c\ubd84<\/th>RTX 5070 Ti<\/th>RTX PRO 4000 Blackwell<\/th><\/tr>
\uc544\ud0a4\ud14d\ucc98<\/td>NVIDIA Blackwell<\/td>NVIDIA Blackwell<\/td><\/tr>
CUDA Core<\/td>8,960<\/td>8,960<\/td><\/tr>
Tensor Core<\/td>5\uc138\ub300<\/td>5\uc138\ub300<\/td><\/tr>
RT Core<\/td>4\uc138\ub300<\/td>4\uc138\ub300<\/td><\/tr>
VRAM<\/td>16GB GDDR7<\/td>24GB GDDR7 ECC<\/td><\/tr>
\uba54\ubaa8\ub9ac \ubc84\uc2a4<\/td>256-bit<\/td>192-bit<\/td><\/tr>
\uba54\ubaa8\ub9ac \ub300\uc5ed\ud3ed<\/td>\uc57d 896GB\/s<\/td>\uc57d 672GB\/s<\/td><\/tr>
ECC \uba54\ubaa8\ub9ac<\/td>\uc9c0\uc6d0\ud558\uc9c0 \uc54a\uc74c<\/td>\uc9c0\uc6d0<\/td><\/tr>
PCIe<\/td>PCIe 5.0<\/td>PCIe 5.0<\/td><\/tr>
\uc18c\ube44\uc804\ub825<\/td>\uc57d 300W<\/td>\uc57d 140W\uae09<\/td><\/tr>
\uc8fc\uc694 \uc6a9\ub3c4<\/td>\uac8c\uc784, AI \ud559\uc2b5, CUDA<\/td>AI, CAD, \uc6cc\ud06c\uc2a4\ud14c\uc774\uc158, \uc11c\ubc84<\/td><\/tr>
\ub4dc\ub77c\uc774\ubc84<\/td>Game Ready \/ Studio<\/td>NVIDIA RTX Enterprise<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

\uac00\uc7a5 \ub208\uc5d0 \ub744\ub294 \ucc28\uc774\ub294 VRAM \uc6a9\ub7c9<\/strong>\uc785\ub2c8\ub2e4.<\/p>\n\n\n\n

RTX 5070 Ti\ub294 16GB\uc758 GDDR7 \uba54\ubaa8\ub9ac\ub97c \uc81c\uacf5\ud558\uc9c0\ub9cc RTX PRO 4000 Blackwell\uc740 24GB GDDR7 ECC \uba54\ubaa8\ub9ac<\/strong>\ub97c \uc81c\uacf5\ud569\ub2c8\ub2e4.<\/p>\n\n\n\n

\ubc18\uba74 \uba54\ubaa8\ub9ac \ub300\uc5ed\ud3ed\uacfc \uc804\ub825 \uc81c\ud55c\uc744 \uace0\ub824\ud558\uba74 RTX 5070 Ti\ub294 \uc21c\uc218 \uc5f0\uc0b0 \uc131\ub2a5 \uce21\uba74\uc5d0\uc11c \uc0c1\ub2f9\ud788 \uac15\ub825\ud569\ub2c8\ub2e4.<\/p>\n\n\n\n

\n\n\n\n

2. \ub525\ub7ec\ub2dd \ud559\uc2b5\uc5d0\uc11c\ub294 RTX 5070 Ti\uac00 \uc720\ub9ac<\/h2>\n\n\n\n

YOLO, CNN, DETR\uacfc \uac19\uc740 Computer Vision \ubaa8\ub378\uc744 \ud559\uc2b5\ud558\ub294 \uacbd\uc6b0\uc5d0\ub294 RTX 5070 Ti\uc758 \uac00\uaca9 \ub300\ube44 \uc131\ub2a5\uc774 \ub9e4\uc6b0 \ub6f0\uc5b4\ub0a9\ub2c8\ub2e4.<\/p>\n\n\n\n

\uc608\ub97c \ub4e4\uc5b4 \ub2e4\uc74c\uacfc \uac19\uc740 \uc791\uc5c5\uc785\ub2c8\ub2e4.<\/p>\n\n\n\n

  • YOLO \uac1d\uccb4 \ud0d0\uc9c0 \ud559\uc2b5<\/li>
  • DETR \uae30\ubc18 \uac1d\uccb4 \ud0d0\uc9c0<\/li>
  • CNN \uc774\ubbf8\uc9c0 \ubd84\ub958<\/li>
  • Segmentation<\/li>
  • \uc774\ubbf8\uc9c0 \uae30\ubc18 Transformer<\/li>
  • PyTorch CUDA \ud559\uc2b5<\/li><\/ul>\n\n\n\n

    RTX 5070 Ti\ub294 \ub192\uc740 \uba54\ubaa8\ub9ac \ub300\uc5ed\ud3ed\uacfc \ucda9\ubd84\ud55c CUDA \uc5f0\uc0b0 \uc131\ub2a5\uc744 \uac00\uc9c0\uace0 \uc788\uae30 \ub54c\ubb38\uc5d0 \uc77c\ubc18\uc801\uc778 Computer Vision \ubaa8\ub378\uc744 \ud559\uc2b5\ud558\uae30\uc5d0\ub294 \ub9e4\uc6b0 \uc88b\uc740 \uc120\ud0dd\uc785\ub2c8\ub2e4.<\/p>\n\n\n\n

    \ud2b9\ud788 16GB VRAM \uc548\uc5d0\uc11c \ubaa8\ub378\uacfc Batch Size\ub97c \uad6c\uc131\ud560 \uc218 \uc788\ub2e4\uba74 RTX PRO 4000\ubcf4\ub2e4 RTX 5070 Ti\uc758 \uac00\uaca9 \ub300\ube44 \uc131\ub2a5\uc774 \ub354 \uc88b\uc744 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n\n\n\n

    \ucd94\ucc9c<\/h3>\n\n\n\n

    YOLO, DETR, CNN \ub4f1 \uc601\uc0c1 AI \ud559\uc2b5\uc774 \uc8fc\ubaa9\uc801\uc774\ub77c\uba74 RTX 5070 Ti\ub97c \ucd94\ucc9c\ud569\ub2c8\ub2e4.<\/p><\/blockquote>\n\n\n\n

    \n\n\n\n

    3. LLM\uc5d0\uc11c\ub294 RTX PRO 4000\uc758 24GB VRAM\uc774 \ud070 \uc7a5\uc810<\/h2>\n\n\n\n

    LLM\uc5d0\uc11c\ub294 \ub2e8\uc21c\ud55c GPU \uc5f0\uc0b0 \uc131\ub2a5\ubcf4\ub2e4 VRAM \uc6a9\ub7c9\uc774 \ub9e4\uc6b0 \uc911\uc694\ud569\ub2c8\ub2e4.<\/strong><\/p>\n\n\n\n

    \ubaa8\ub378\uc758 Parameter\ubfd0\ub9cc \uc544\ub2c8\ub77c \ub2e4\uc74c \ub370\uc774\ud130\ub4e4\ub3c4 GPU \uba54\ubaa8\ub9ac\ub97c \uc0ac\uc6a9\ud558\uae30 \ub54c\ubb38\uc785\ub2c8\ub2e4.<\/p>\n\n\n\n

    • Model Weight<\/li>
    • KV Cache<\/li>
    • Activation<\/li>
    • Attention \uc5f0\uc0b0<\/li>
    • Context Length<\/li>
    • Batch Size<\/li>
    • LoRA \/ QLoRA \ud559\uc2b5 \ub370\uc774\ud130<\/li><\/ul>\n\n\n\n

      \ub530\ub77c\uc11c 16GB\uc640 24GB\uc758 \ucc28\uc774\ub294 \uc2e4\uc81c LLM \ud65c\uc6a9\uc5d0\uc11c \uc0c1\ub2f9\ud788 \ud06c\uac8c \ub290\uaef4\uc9c8 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n\n\n\n

      \ub300\ub7b5\uc801\uc778 \ud65c\uc6a9 \ubc94\uc704\ub294 \ub2e4\uc74c\uacfc \uac19\uc2b5\ub2c8\ub2e4.<\/p>\n\n\n\n

      \uc791\uc5c5<\/th>RTX 5070 Ti 16GB<\/th>RTX PRO 4000 24GB<\/th><\/tr>
      7B LLM \ucd94\ub860<\/td>\ub9e4\uc6b0 \uc801\ud569<\/td>\ub9e4\uc6b0 \uc801\ud569<\/td><\/tr>
      12B~14B \ubaa8\ub378<\/td>\uac00\ub2a5<\/td>\uc5ec\uc720 \uc788\uc74c<\/td><\/tr>
      20B\uae09 Quantized \ubaa8\ub378<\/td>\uba54\ubaa8\ub9ac \uc81c\uc57d<\/td>\uc0c1\ub300\uc801\uc73c\ub85c \uc720\ub9ac<\/td><\/tr>
      30B\uae09 Quantized \ubaa8\ub378<\/td>\ub9e4\uc6b0 \uc81c\ud55c\uc801<\/td>\uc870\uac74\ubd80 \uac00\ub2a5<\/td><\/tr>
      LoRA<\/td>\uac00\ub2a5<\/td>\uc720\ub9ac<\/td><\/tr>
      QLoRA<\/td>\uac00\ub2a5<\/td>\uc720\ub9ac<\/td><\/tr>
      vLLM<\/td>\uac00\ub2a5<\/td>\ub354 \ud070 KV Cache \ud655\ubcf4<\/td><\/tr>
      Long Context<\/td>\uc81c\ud55c\uc801<\/td>\uc0c1\ub300\uc801\uc73c\ub85c \uc720\ub9ac<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n

      \ud2b9\ud788 vLLM\uc5d0\uc11c\ub294 GPU \uba54\ubaa8\ub9ac \uc77c\ubd80\ub97c KV Cache\ub85c \uc0ac\uc6a9\ud558\uae30 \ub54c\ubb38\uc5d0 8GB\uc758 VRAM \ucc28\uc774\uac00 \ub3d9\uc2dc \uc0ac\uc6a9\uc790 \uc218\ub098 Context Length\uc5d0 \uc9c1\uc811\uc801\uc778 \uc601\ud5a5\uc744 \uc904 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n\n\n\n

      \ucd94\ucc9c<\/h3>\n\n\n\n

      Gemma, Llama, Phi, GPT-OSS \uacc4\uc5f4 LLM\uc744 \uc2e4\ud589\ud558\uac70\ub098 vLLM \uae30\ubc18 \ucd94\ub860 \uc11c\ubc84\ub97c \uc6b4\uc601\ud55c\ub2e4\uba74 RTX PRO 4000 24GB\uac00 \ub354 \uc720\ub9ac\ud569\ub2c8\ub2e4.<\/p><\/blockquote>\n\n\n\n

      \n\n\n\n

      4. RTX PRO 4000\uc758 \uc911\uc694\ud55c \uc7a5\uc810: ECC Memory<\/h2>\n\n\n\n

      RTX PRO 4000 Blackwell\uc758 \ub610 \ud558\ub098\uc758 \uc7a5\uc810\uc740 ECC(Error Correcting Code) \uba54\ubaa8\ub9ac<\/strong>\uc785\ub2c8\ub2e4.<\/p>\n\n\n\n

      ECC \uba54\ubaa8\ub9ac\ub294 GPU \uba54\ubaa8\ub9ac\uc5d0\uc11c \ubc1c\uc0dd\ud560 \uc218 \uc788\ub294 \uc77c\ubd80 Bit Error\ub97c \uac10\uc9c0\ud558\uace0 \uc218\uc815\ud558\ub294 \uae30\ub2a5\uc785\ub2c8\ub2e4.<\/p>\n\n\n\n

      \uc77c\ubc18\uc801\uc778 \uac1c\uc778\uc6a9 AI \uac1c\ubc1c\uc5d0\uc11c\ub294 ECC\uac00 \ubc18\ub4dc\uc2dc \ud544\uc694\ud55c \uac83\uc740 \uc544\ub2c8\uc9c0\ub9cc \ub2e4\uc74c\uacfc \uac19\uc740 \ud658\uacbd\uc5d0\uc11c\ub294 \uc758\ubbf8\uac00 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n\n\n\n

      • 24\uc2dc\uac04 AI \uc11c\ubc84<\/li>
      • \uc7a5\uc2dc\uac04 \ubaa8\ub378 \ud559\uc2b5<\/li>
      • \uc5f0\uad6c\uc6a9 \uc6cc\ud06c\uc2a4\ud14c\uc774\uc158<\/li>
      • \uae30\uc5c5\uc6a9 AI \uc11c\ubc84<\/li>
      • \ub300\uaddc\ubaa8 \ub370\uc774\ud130 \ucc98\ub9ac<\/li>
      • \uc548\uc815\uc131\uc774 \uc911\uc694\ud55c \uc2dc\uc2a4\ud15c<\/li><\/ul>\n\n\n\n

        \ub530\ub77c\uc11c \uc11c\ubc84 \uc548\uc815\uc131\uc744 \uc911\uc694\ud558\uac8c \uc0dd\uac01\ud55c\ub2e4\uba74 RTX PRO \uacc4\uc5f4\uc774 \ub354 \uc801\ud569\ud569\ub2c8\ub2e4.<\/p>\n\n\n\n

        \n\n\n\n

        5. \ub450 GPU\ub97c \ud568\uaed8 \uc0ac\uc6a9\ud558\uba74 \uc5b4\ub5a8\uae4c?<\/h2>\n\n\n\n

        AI \uac1c\ubc1c\uc6a9 \uc6cc\ud06c\uc2a4\ud14c\uc774\uc158\uc5d0\uc11c\ub294<\/p>\n\n\n\n

        RTX 5070 Ti 16GB + RTX PRO 4000 24GB<\/strong><\/p>\n\n\n\n

        \uad6c\uc131\ub3c4 \uc0c1\ub2f9\ud788 \uc88b\uc740 \uc870\ud569\uc785\ub2c8\ub2e4.<\/p>\n\n\n\n

        \uc608\ub97c \ub4e4\uc5b4 \ub2e4\uc74c\uacfc \uac19\uc774 \uc5ed\ud560\uc744 \ubd84\ub9ac\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n\n\n\n

        RTX 5070 Ti 16GB\n        \u2502\n        \u251c\u2500 YOLO \ud559\uc2b5\n        \u251c\u2500 DETR \ud559\uc2b5\n        \u251c\u2500 CNN\n        \u2514\u2500 Computer Vision\n\nRTX PRO 4000 24GB\n        \u2502\n        \u251c\u2500 LLM\n        \u251c\u2500 vLLM\n        \u251c\u2500 RAG\n        \u251c\u2500 Multi-Agent\n        \u2514\u2500 AI \ucd94\ub860 \uc11c\ubc84<\/pre>\n\n\n\n
        \uc774 \ubc29\uc2dd\uc758 \uc7a5\uc810\uc740 \uc11c\ub85c \ub2e4\ub978 \uc791\uc5c5\uc774 GPU \uc790\uc6d0\uc744 \uacbd\uc7c1\ud558\uc9c0 \uc54a\ub294\ub2e4\ub294 \uc810\uc785\ub2c8\ub2e4.<\/p>\n\n\n\n
        \uc608\ub97c \ub4e4\uc5b4 RTX 5070 Ti\uc5d0\uc11c\ub294 YOLO\ub97c \ud559\uc2b5\ud558\uba74\uc11c RTX PRO 4000\uc5d0\uc11c\ub294 LLM \ucd94\ub860 \uc11c\ubc84\ub97c \ub3d9\uc2dc\uc5d0 \uc2e4\ud589\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n\n\n\n
        \n\n\n\n
        6. PyTorch\uc5d0\uc11c \ub450 GPU \ud655\uc778\ud558\uae30<\/h2>\n\n\n\n
        Ubuntu \ud658\uacbd\uc5d0\uc11c PyTorch\ub97c \uc0ac\uc6a9\ud558\ub294 \uacbd\uc6b0 \ub2e4\uc74c\uacfc \uac19\uc774 GPU\ub97c \ud655\uc778\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n\n\n\n
        import torch\n\nprint(\"GPU Count:\", torch.cuda.device_count())\n\nfor i in range(torch.cuda.device_count()):\n    print(i, torch.cuda.get_device_name(i))<\/pre>\n\n\n\n
        \uc815\uc0c1\uc801\uc73c\ub85c \uc778\uc2dd\ub418\uba74 \ub2e4\uc74c\uacfc \uac19\uc774 \ud45c\uc2dc\ub420 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n\n\n\n
        GPU Count: 2\n\n0 NVIDIA GeForce RTX 5070 Ti\n1 NVIDIA RTX PRO 4000 Blackwell<\/pre>\n\n\n\n
        \n\n\n\n
        7. GPU\ub97c \uc9c0\uc815\ud574\uc11c \ud504\ub85c\uadf8\ub7a8 \uc2e4\ud589\ud558\uae30<\/h2>\n\n\n\n
        \ud2b9\uc815 GPU\uc5d0\uc11c \ud504\ub85c\uadf8\ub7a8\uc744 \uc2e4\ud589\ud558\ub824\uba74 CUDA_VISIBLE_DEVICES<\/code>\ub97c \uc0ac\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n\n\n\n
        RTX 5070 Ti\uc5d0\uc11c AI \ud559\uc2b5<\/h3>\n\n\n\n
        CUDA_VISIBLE_DEVICES=0 python train.py<\/pre>\n\n\n\n
        \ub610\ub294 YOLO\ub97c \uc0ac\uc6a9\ud558\ub294 \uacbd\uc6b0<\/p>\n\n\n\n
        yolo detect train \\\nmodel=yolo11m.pt \\\ndata=data.yaml \\\nepochs=100 \\\ndevice=0<\/pre>\n\n\n\n
        RTX PRO 4000\uc5d0\uc11c LLM \uc2e4\ud589<\/h3>\n\n\n\n
        CUDA_VISIBLE_DEVICES=1 \\\nvllm serve MODEL_NAME<\/pre>\n\n\n\n
        \uc774\uc640 \uac19\uc774 \ub450 GPU\uc758 \uc5ed\ud560\uc744 \uba85\ud655\ud558\uac8c \ub098\ub204\uba74 GPU \ud65c\uc6a9 \ud6a8\uc728\uc774 \ub192\uc544\uc9d1\ub2c8\ub2e4.<\/p>\n\n\n\n
        \n\n\n\n
        8. 16GB + 24GB = 40GB GPU\uac00 \ub418\ub294 \uac83\uc740 \uc544\ub2c8\ub2e4<\/h2>\n\n\n\n
        \ub4c0\uc5bc GPU \uad6c\uc131\uc5d0\uc11c \uac00\uc7a5 \ub9ce\uc774 \uc624\ud574\ud558\ub294 \ubd80\ubd84\uc785\ub2c8\ub2e4.<\/p>\n\n\n\n
        RTX 5070 Ti 16GB\uc640 RTX PRO 4000 24GB\ub97c \uc124\uce58\ud558\uba74 \uc804\uccb4 GPU \uba54\ubaa8\ub9ac\ub294 \ubb3c\ub9ac\uc801\uc73c\ub85c 40GB\uac00 \ub429\ub2c8\ub2e4.<\/p>\n\n\n\n
        \ud558\uc9c0\ub9cc \uc77c\ubc18\uc801\uc778 CUDA \ud504\ub85c\uadf8\ub7a8\uc5d0\uc11c\ub294 \uc774\uac83\uc774 \uc790\ub3d9\uc73c\ub85c \ud558\ub098\uc758 40GB GPU\ucc98\ub7fc \ub3d9\uc791\ud558\uc9c0 \uc54a\uc2b5\ub2c8\ub2e4.<\/strong><\/p>\n\n\n\n
        GPU 0\nRTX 5070 Ti\nVRAM 16GB\n\n+\n\nGPU 1\nRTX PRO 4000\nVRAM 24GB\n\n\u2260\n\n40GB \ub2e8\uc77c GPU<\/pre>\n\n\n\n
        \ub300\uc2e0 \ubaa8\ub378 \ubcd1\ub82c\ud654(Model Parallelism)\ub098 Tensor Parallelism\uc744 \uc0ac\uc6a9\ud558\ub294 \uacbd\uc6b0 \uc5ec\ub7ec GPU\uc5d0 \ubaa8\ub378\uc744 \ub098\ub204\uc5b4 \uc62c\ub9b4 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n\n\n\n
        \uc608\ub97c \ub4e4\uc5b4 vLLM, Hugging Face Accelerate, DeepSpeed \ub4f1\uc758 \ud504\ub808\uc784\uc6cc\ud06c\ub97c \ud65c\uc6a9\ud560 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n\n\n\n
        \ub2e4\ub9cc 16GB\uc640 24GB\ucc98\ub7fc \uc11c\ub85c \ub2e4\ub978 GPU\ub97c \ud63c\ud569\ud560 \uacbd\uc6b0 \ub3d9\uc77c GPU \ub450 \uc7a5\uc744 \uc0ac\uc6a9\ud558\ub294 \uac83\ubcf4\ub2e4 \uba54\ubaa8\ub9ac \ubd84\ubc30\uc640 \uc131\ub2a5 \ucd5c\uc801\ud654\uac00 \ubcf5\uc7a1\ud574\uc9c8 \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n\n\n\n
        \n\n\n\n
        9. \uc6a9\ub3c4\ubcc4 \ucd94\ucc9c<\/h2>\n\n\n\n
        \uc6a9\ub3c4<\/th>\ucd94\ucc9c GPU<\/th><\/tr>
        YOLO \ud559\uc2b5<\/td>RTX 5070 Ti<\/td><\/tr>
        CNN \ud559\uc2b5<\/td>RTX 5070 Ti<\/td><\/tr>
        DETR \ud559\uc2b5<\/td>RTX 5070 Ti<\/td><\/tr>
        \uc774\ubbf8\uc9c0 \ubd84\ub958<\/td>RTX 5070 Ti<\/td><\/tr>
        7B LLM<\/td>\ub458 \ub2e4<\/td><\/tr>
        14B LLM<\/td>RTX PRO 4000<\/td><\/tr>
        20B\uae09 LLM<\/td>RTX PRO 4000<\/td><\/tr>
        QLoRA<\/td>RTX PRO 4000<\/td><\/tr>
        vLLM \uc11c\ubc84<\/td>RTX PRO 4000<\/td><\/tr>
        RAG \uc2dc\uc2a4\ud15c<\/td>RTX PRO 4000<\/td><\/tr>
        Multi-Agent LLM<\/td>RTX PRO 4000<\/td><\/tr>
        \uc7a5\uc2dc\uac04 AI \uc11c\ubc84<\/td>RTX PRO 4000<\/td><\/tr>
        \uac8c\uc784<\/td>RTX 5070 Ti<\/td><\/tr>
        CAD \/ \uc804\ubb38 \uadf8\ub798\ud53d<\/td>RTX PRO 4000<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n
        \n\n\n\n
        10. \uacb0\ub860<\/h2>\n\n\n\n
        \ub450 GPU\ub294 \ub2e8\uc21c\ud788 \uc5b4\ub290 \uc81c\ud488\uc774 \ub354 \uc88b\uc740\uac00\ub85c \ube44\uad50\ud558\uae30\ubcf4\ub2e4\ub294 \uc6a9\ub3c4\uc5d0 \ub530\ub77c \uc120\ud0dd\ud574\uc57c \ud569\ub2c8\ub2e4.<\/p>\n\n\n\n
        RTX 5070 Ti<\/h3>\n\n\n\n
        RTX 5070 Ti\ub294 \ub192\uc740 \uc5f0\uc0b0 \uc131\ub2a5\uacfc \uba54\ubaa8\ub9ac \ub300\uc5ed\ud3ed\uc744 \uac00\uc9c0\uace0 \uc788\uc5b4 YOLO, DETR, CNN\uacfc \uac19\uc740 \ub525\ub7ec\ub2dd \ubaa8\ub378 \ud559\uc2b5\uc5d0 \ub9e4\uc6b0 \uc801\ud569\ud55c GPU<\/strong>\uc785\ub2c8\ub2e4.<\/p>\n\n\n\n
        16GB VRAM \uc548\uc5d0\uc11c \ubaa8\ub378\uc744 \uc2e4\ud589\ud560 \uc218 \uc788\ub2e4\uba74 \uac00\uaca9 \ub300\ube44 AI \ud559\uc2b5 \uc131\ub2a5\uc774 \ub9e4\uc6b0 \ub6f0\uc5b4\ub0a9\ub2c8\ub2e4.<\/p>\n\n\n\n
        RTX PRO 4000 Blackwell<\/h3>\n\n\n\n
        RTX PRO 4000 Blackwell\uc740 \uc808\ub300\uc801\uc778 \uc5f0\uc0b0 \uc131\ub2a5\ubcf4\ub2e4\ub294 24GB VRAM, ECC \uba54\ubaa8\ub9ac, \ub0ae\uc740 \uc18c\ube44\uc804\ub825, \uc6cc\ud06c\uc2a4\ud14c\uc774\uc158 \uc548\uc815\uc131<\/strong>\uc774 \uac15\uc810\uc785\ub2c8\ub2e4.<\/p>\n\n\n\n
        \ub530\ub77c\uc11c LLM, vLLM, RAG, Multi-Agent \uc2dc\uc2a4\ud15c\uc774\ub098 \uc7a5\uc2dc\uac04 AI \uc11c\ubc84\ub97c \uad6c\ucd95\ud558\ub294 \uacbd\uc6b0 \ub354 \uc801\ud569\ud569\ub2c8\ub2e4.<\/p>\n\n\n\n
        \uac1c\uc778\uc801\uc778 AI \uc6cc\ud06c\uc2a4\ud14c\uc774\uc158 \uad6c\uc131<\/h3>\n\n\n\n
        \ub450 GPU\ub97c \ubaa8\ub450 \ud65c\uc6a9\ud560 \uc218 \uc788\ub2e4\uba74 \ub2e4\uc74c\uacfc \uac19\uc740 \uad6c\uc131\uc774 \ud6a8\uc728\uc801\uc785\ub2c8\ub2e4.<\/p>\n\n\n\n
        \u250c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2510\n\u2502       AI Workstation        \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 RTX 5070 Ti 16GB            \u2502\n\u2502                             \u2502\n\u2502 YOLO \/ CNN \/ DETR           \u2502\n\u2502 Computer Vision Training    \u2502\n\u251c\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2524\n\u2502 RTX PRO 4000 24GB           \u2502\n\u2502                             \u2502\n\u2502 LLM \/ vLLM \/ RAG            \u2502\n\u2502 Multi-Agent \/ AI Server     \u2502\n\u2514\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2518<\/pre>\n\n\n\n
        \uacb0\uad6d \uc601\uc0c1 AI \ud559\uc2b5\uc740 RTX 5070 Ti<\/strong>, LLM\uacfc AI \uc11c\ubc84\ub294 RTX PRO 4000<\/strong>\uc73c\ub85c \uc5ed\ud560\uc744 \ub098\ub204\ub294 \uac83\uc774 \ub9e4\uc6b0 \ud6a8\uc728\uc801\uc778 \uad6c\uc131\uc774\ub77c\uace0 \ubcfc \uc218 \uc788\uc2b5\ub2c8\ub2e4.<\/p>\n\n\n\n
        <\/p>\n\n\n\n
        \ud604\uc7ac  5070 Ti + PRO 4000 \ub4c0\uc5bc GPU<\/strong> \uad6c\uc131\uc774 \uc815\ub9d0 \ub9e4\ub825\uc801 \uc778\uac83 \uac19\uc2b5\ub2c8\ub2e4.<\/p>\n\n\n\n
        \ucc38\uace0\ub85c \uba54\uc778\ubcf4\ub4dc\ub294 [ASUS] ROG STRIX B760-G GAMING WIFI \ucf54\uc787 (\uc778\ud154B760\/M-ATX) \uc0ac\uc6a9 \uc911 \uc785\ub2c8\ub2e4.<\/p>\n\n\n\n
        \"\"
        https:\/\/rog.asus.com\/kr\/motherboards\/rog-strix\/rog-strix-b760-g-gaming-wifi\/<\/figcaption><\/figure>\n\n\n\n
        \"\"<\/p>\n\n\n\n
        \ub4dc\ub514\uc5b4 RTX PRO 4000 + RTX 5070 ti 2way \uc124\uce58\ud558\ub294\ub370 \uc131\uacf5\ud588\uc2b5\ub2c8\ub2e4.<\/p>\n\n\n","protected":false},"excerpt":{"rendered":"
        AI \ubaa8\ub378 \ud559\uc2b5\uacfc LLM \ucd94\ub860\uc6a9 GPU\ub97c \uad6c\uc131\ud560 \ub54c GeForce RTX 5070 Ti\uc640 NVIDIA RTX PRO 4000 Blackwell \uc911 \uc5b4\ub5a4 \uc81c\ud488\uc774 \ub354 \uc801\ud569\ud55c\uc9c0 \ube44\uad50\ud574 \ubcf4\uc558\uc2b5\ub2c8\ub2e4. \ub450 \uc81c\ud488 \ubaa8\ub450 NVIDIA\uc758 \ucd5c\uc2e0 Blackwell \uc544\ud0a4\ud14d\ucc98\ub97c \uae30\ubc18\uc73c\ub85c \ud558\uc9c0\ub9cc, \uc81c\ud488\uc758 \uc131\uaca9\uc740 \uc0c1\ub2f9\ud788 \ub2e4\ub985\ub2c8\ub2e4. RTX… <\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":[],"categories":[4],"tags":[58,52,53,61,54,56,59,50,55,60,57,51],"_links":{"self":[{"href":"https:\/\/www.kkoc.org\/index.php?rest_route=\/wp\/v2\/posts\/892"}],"collection":[{"href":"https:\/\/www.kkoc.org\/index.php?rest_route=\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.kkoc.org\/index.php?rest_route=\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.kkoc.org\/index.php?rest_route=\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.kkoc.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcomments&post=892"}],"version-history":[{"count":8,"href":"https:\/\/www.kkoc.org\/index.php?rest_route=\/wp\/v2\/posts\/892\/revisions"}],"predecessor-version":[{"id":904,"href":"https:\/\/www.kkoc.org\/index.php?rest_route=\/wp\/v2\/posts\/892\/revisions\/904"}],"wp:attachment":[{"href":"https:\/\/www.kkoc.org\/index.php?rest_route=%2Fwp%2Fv2%2Fmedia&parent=892"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.kkoc.org\/index.php?rest_route=%2Fwp%2Fv2%2Fcategories&post=892"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.kkoc.org\/index.php?rest_route=%2Fwp%2Fv2%2Ftags&post=892"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}