{"id":25112,"date":"2026-11-13T11:23:20","date_gmt":"2026-11-13T04:23:20","guid":{"rendered":"https:\/\/vnso.vn\/?p=25112"},"modified":"2026-11-13T11:27:32","modified_gmt":"2026-11-13T04:27:32","slug":"thue-gpu-chay-ai-nen-chon-nvidia-a30-rtx-3090-hay-rtx-a6000","status":"publish","type":"post","link":"https:\/\/vnso.vn\/en\/thue-gpu-chay-ai-nen-chon-nvidia-a30-rtx-3090-hay-rtx-a6000\/","title":{"rendered":"Thu\u00ea GPU Ch\u1ea1y AI: N\u00ean Ch\u1ecdn NVIDIA A30, RTX 3090 Hay RTX A6000?"},"content":{"rendered":"<p style=\"text-align: justify;\"><a href=\"https:\/\/gpu.vnso.vn\/\"><strong>Thu\u00ea GPU<\/strong><\/a> \u0111ang tr\u1edf th\u00e0nh gi\u1ea3i ph\u00e1p \u0111\u01b0\u1ee3c nhi\u1ec1u doanh nghi\u1ec7p, l\u1eadp tr\u00ecnh vi\u00ean v\u00e0 nh\u00f3m nghi\u00ean c\u1ee9u AI l\u1ef1a ch\u1ecdn \u0111\u1ec3 ti\u1ebfp c\u1eadn s\u1ee9c m\u1ea1nh t\u00ednh to\u00e1n cao m\u00e0 kh\u00f4ng c\u1ea7n \u0111\u1ea7u t\u01b0 h\u1ec7 th\u1ed1ng ph\u1ea7n c\u1ee9ng \u0111\u1eaft \u0111\u1ecf. Tuy nhi\u00ean, gi\u1eefa NVIDIA A30 24GB, RTX 3090 24GB v\u00e0 RTX A6000 48GB, \u0111\u00e2u m\u1edbi l\u00e0 l\u1ef1a ch\u1ecdn ph\u00f9 h\u1ee3p cho t\u1eebng nhu c\u1ea7u?<\/p>\n<p style=\"text-align: justify;\">C\u1ea3 ba \u0111\u1ec1u s\u1eed d\u1ee5ng ki\u1ebfn tr\u00fac NVIDIA Ampere, h\u1ed7 tr\u1ee3 CUDA v\u00e0 c\u00e1c framework AI ph\u1ed5 bi\u1ebfn. D\u00f9 v\u1eady, s\u1ef1 kh\u00e1c bi\u1ec7t v\u1ec1 hi\u1ec7u n\u0103ng t\u00ednh to\u00e1n, b\u1ed9 nh\u1edb GPU, kh\u1ea3 n\u0103ng v\u1eadn h\u00e0nh v\u00e0 t\u00ednh n\u0103ng chuy\u00ean d\u1ee5ng khi\u1ebfn m\u1ed7i d\u00f2ng card ph\u00f9 h\u1ee3p v\u1edbi nh\u1eefng nh\u00f3m kh\u00e1ch h\u00e0ng kh\u00e1c nhau.<\/p>\n<p style=\"text-align: justify;\">Trong b\u00e0i vi\u1ebft n\u00e0y, VNSO s\u1ebd ph\u00e2n t\u00edch chi ti\u1ebft ba d\u00f2ng GPU, gi\u00fap b\u1ea1n l\u1ef1a ch\u1ecdn c\u1ea5u h\u00ecnh t\u1ed1i \u01b0u khi <strong>thu\u00ea GPU ch\u1ea1y AI, train model ho\u1eb7c tri\u1ec3n khai \u1ee9ng d\u1ee5ng Machine Learning<\/strong>.<\/p>\n<h2 style=\"text-align: justify;\" data-pm-slice=\"1 1 []\">1. V\u00ec sao nhu c\u1ea7u thu\u00ea GPU cho AI ng\u00e0y c\u00e0ng t\u0103ng?<\/h2>\n<p style=\"text-align: justify;\">S\u1ef1 ph\u00e1t tri\u1ec3n c\u1ee7a Artificial Intelligence (AI), Machine Learning v\u00e0 Deep Learning \u0111ang l\u00e0m thay \u0111\u1ed5i nhu c\u1ea7u s\u1eed d\u1ee5ng h\u1ea1 t\u1ea7ng t\u00ednh to\u00e1n c\u1ee7a doanh nghi\u1ec7p. Nh\u1eefng \u1ee9ng d\u1ee5ng nh\u01b0 chatbot AI, nh\u1eadn di\u1ec7n h\u00ecnh \u1ea3nh, x\u1eed l\u00fd ng\u00f4n ng\u1eef t\u1ef1 nhi\u00ean, t\u1ea1o h\u00ecnh \u1ea3nh b\u1eb1ng AI hay x\u00e2y d\u1ef1ng m\u00f4 h\u00ecnh d\u1ef1 \u0111o\u00e1n \u0111\u1ec1u c\u00f3 th\u1ec3 y\u00eau c\u1ea7u l\u01b0\u1ee3ng l\u1edbn t\u00e0i nguy\u00ean x\u1eed l\u00fd song song. Trong \u0111\u00f3, GPU \u0111\u00f3ng vai tr\u00f2 quan tr\u1ecdng nh\u1edd kh\u1ea3 n\u0103ng th\u1ef1c hi\u1ec7n nhi\u1ec1u ph\u00e9p t\u00ednh \u0111\u1ed3ng th\u1eddi, \u0111\u1eb7c bi\u1ec7t l\u00e0 nh\u1eefng ph\u00e9p to\u00e1n ma tr\u1eadn th\u01b0\u1eddng xu\u1ea5t hi\u1ec7n trong m\u00f4 h\u00ecnh h\u1ecdc s\u00e2u.<\/p>\n<p style=\"text-align: justify;\">Tuy nhi\u00ean, \u0111\u1ea7u t\u01b0 GPU v\u1eadt l\u00fd kh\u00f4ng ch\u1ec9 bao g\u1ed3m chi ph\u00ed mua card \u0111\u1ed3 h\u1ecda. Doanh nghi\u1ec7p c\u00f2n ph\u1ea3i chu\u1ea9n b\u1ecb m\u00e1y ch\u1ee7, CPU, RAM, l\u01b0u tr\u1eef, h\u1ec7 th\u1ed1ng \u0111i\u1ec7n, l\u00e0m m\u00e1t v\u00e0 nh\u00e2n s\u1ef1 qu\u1ea3n tr\u1ecb. \u0110\u00e2y l\u00e0 l\u00fd do d\u1ecbch v\u1ee5 <strong>thu\u00ea GPU<\/strong> tr\u1edf th\u00e0nh l\u1ef1a ch\u1ecdn \u0111\u00e1ng c\u00e2n nh\u1eafc.<\/p>\n<div id=\"attachment_25115\" style=\"width: 810px\" class=\"wp-caption alignnone\"><img fetchpriority=\"high\" decoding=\"async\" aria-describedby=\"caption-attachment-25115\" class=\"size-medium wp-image-25115\" src=\"https:\/\/vnso.vn\/wp-content\/uploads\/2026\/11\/Thue-GPU-Server-chay-AI-va-Deep-Learning-tai-VNSO-800x450.png\" alt=\"Thu\u00ea GPU Server ch\u1ea1y AI v\u00e0 Deep Learning t\u1ea1i VNSO\" width=\"800\" height=\"450\" srcset=\"https:\/\/vnso.vn\/wp-content\/uploads\/2026\/11\/Thue-GPU-Server-chay-AI-va-Deep-Learning-tai-VNSO-800x450.png 800w, https:\/\/vnso.vn\/wp-content\/uploads\/2026\/11\/Thue-GPU-Server-chay-AI-va-Deep-Learning-tai-VNSO-1024x576.png 1024w, https:\/\/vnso.vn\/wp-content\/uploads\/2026\/11\/Thue-GPU-Server-chay-AI-va-Deep-Learning-tai-VNSO-768x432.png 768w, https:\/\/vnso.vn\/wp-content\/uploads\/2026\/11\/Thue-GPU-Server-chay-AI-va-Deep-Learning-tai-VNSO-1536x864.png 1536w, https:\/\/vnso.vn\/wp-content\/uploads\/2026\/11\/Thue-GPU-Server-chay-AI-va-Deep-Learning-tai-VNSO-2048x1152.png 2048w, https:\/\/vnso.vn\/wp-content\/uploads\/2026\/11\/Thue-GPU-Server-chay-AI-va-Deep-Learning-tai-VNSO-18x10.png 18w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/><p id=\"caption-attachment-25115\" class=\"wp-caption-text\">Thu\u00ea GPU Server ch\u1ea1y AI v\u00e0 Deep Learning t\u1ea1i VNSO<\/p><\/div>\n<h3 style=\"text-align: justify;\">Nh\u1eefng l\u1ee3i \u00edch khi thu\u00ea GPU thay v\u00ec mua thi\u1ebft b\u1ecb<\/h3>\n<ul style=\"text-align: justify;\" data-spread=\"false\">\n<li><strong>Gi\u1ea3m chi ph\u00ed \u0111\u1ea7u t\u01b0 ban \u0111\u1ea7u:<\/strong> Kh\u00f4ng c\u1ea7n b\u1ecf m\u1ed9t kho\u1ea3n ng\u00e2n s\u00e1ch l\u1edbn \u0111\u1ec3 s\u1edf h\u1eefu GPU v\u00e0 h\u1ec7 th\u1ed1ng m\u00e1y ch\u1ee7.<\/li>\n<li><strong>Linh ho\u1ea1t l\u1ef1a ch\u1ecdn c\u1ea5u h\u00ecnh:<\/strong> C\u00f3 th\u1ec3 l\u1ef1a ch\u1ecdn GPU ph\u00f9 h\u1ee3p v\u1edbi k\u00edch th\u01b0\u1edbc m\u00f4 h\u00ecnh AI v\u00e0 y\u00eau c\u1ea7u x\u1eed l\u00fd.<\/li>\n<li><strong>Ch\u1ee7 \u0111\u1ed9ng d\u1ef1 to\u00e1n chi ph\u00ed:<\/strong> H\u00ecnh th\u1ee9c thu\u00ea GPU theo th\u00e1ng gi\u00fap doanh nghi\u1ec7p x\u00e2y d\u1ef1ng ng\u00e2n s\u00e1ch cho t\u1eebng giai \u0111o\u1ea1n d\u1ef1 \u00e1n.<\/li>\n<li><strong>Ti\u1ebft ki\u1ec7m ngu\u1ed3n l\u1ef1c v\u1eadn h\u00e0nh:<\/strong> Gi\u1ea3m nhu c\u1ea7u t\u1ef1 x\u00e2y d\u1ef1ng v\u00e0 duy tr\u00ec h\u1ea1 t\u1ea7ng ph\u1ea7n c\u1ee9ng.<\/li>\n<li><strong>Ti\u1ebfp c\u1eadn nhi\u1ec1u d\u00f2ng GPU:<\/strong> D\u1ec5 d\u00e0ng c\u00e2n nh\u1eafc gi\u1eefa c\u00e1c s\u1ea3n ph\u1ea9m Consumer, Workstation v\u00e0 Data Center.<\/li>\n<\/ul>\n<p style=\"text-align: justify;\">\u0110\u1eb7c bi\u1ec7t, \u0111\u1ed1i v\u1edbi c\u00e1c d\u1ef1 \u00e1n AI tri\u1ec3n khai trong nhi\u1ec1u th\u00e1ng, vi\u1ec7c s\u1eed d\u1ee5ng GPU thu\u00ea gi\u00fap doanh nghi\u1ec7p t\u1eadp trung ngu\u1ed3n l\u1ef1c v\u00e0o ph\u00e1t tri\u1ec3n ph\u1ea7n m\u1ec1m v\u00e0 t\u1ed1i \u01b0u m\u00f4 h\u00ecnh h\u01a1n l\u00e0 <a href=\"https:\/\/hqg.vn\/\">mua GPU<\/a>.<\/p>\n<p><strong>&gt;&gt; Xem th\u00eam: <a href=\"https:\/\/vnso.vn\/en\/vnso-cho-thue-gpu-nvidia-da-dang-tu-3-thang\/\">VNSO Cho Thu\u00ea GPU NVIDIA \u0110a D\u1ea1ng \u2013 T\u1eeb 3 Th\u00e1ng<\/a><\/strong><\/p>\n<h2 style=\"text-align: justify;\" data-pm-slice=\"1 1 []\">2. T\u1ed5ng quan ba d\u00f2ng NVIDIA A30, RTX 3090 v\u00e0 RTX A6000<\/h2>\n<p style=\"text-align: justify;\">M\u1eb7c d\u00f9 c\u00f9ng thu\u1ed9c th\u1ebf h\u1ec7 Ampere, NVIDIA A30, RTX 3090 v\u00e0 RTX A6000 \u0111\u01b0\u1ee3c ph\u00e1t tri\u1ec3n cho c\u00e1c ph\u00e2n kh\u00fac th\u1ecb tr\u01b0\u1eddng kh\u00e1c nhau.<\/p>\n<h3 style=\"text-align: justify;\">NVIDIA A30 24GB \u2013 GPU chuy\u00ean d\u1ee5ng cho Data Center<\/h3>\n<p style=\"text-align: justify;\">NVIDIA A30 l\u00e0 d\u00f2ng GPU \u0111\u01b0\u1ee3c thi\u1ebft k\u1ebf cho m\u00f4i tr\u01b0\u1eddng trung t\u00e2m d\u1eef li\u1ec7u, t\u1eadp trung v\u00e0o c\u00e1c t\u00e1c v\u1ee5 AI Inference, Machine Learning, High Performance Computing (HPC) v\u00e0 nh\u1eefng \u1ee9ng d\u1ee5ng t\u00ednh to\u00e1n doanh nghi\u1ec7p. A30 s\u1edf h\u1eefu 24GB HBM2 v\u1edbi b\u0103ng th\u00f4ng b\u1ed9 nh\u1edb 933GB\/s, h\u1ed7 tr\u1ee3 Tensor Cores th\u1ebf h\u1ec7 th\u1ee9 ba v\u00e0 c\u00f4ng ngh\u1ec7 Multi-Instance GPU (MIG).<\/p>\n<p style=\"text-align: justify;\">M\u1ed9t \u01b0u \u0111i\u1ec3m \u0111\u00e1ng ch\u00fa \u00fd c\u1ee7a A30 l\u00e0 m\u1ee9c ti\u00eau th\u1ee5 \u0111i\u1ec7n t\u1ed1i \u0111a 165W, th\u1ea5p h\u01a1n \u0111\u00e1ng k\u1ec3 so v\u1edbi hai d\u00f2ng GPU c\u00f2n l\u1ea1i. \u0110\u1eb7c bi\u1ec7t, MIG cho ph\u00e9p ph\u00e2n chia m\u1ed9t GPU A30 th\u00e0nh nhi\u1ec1u GPU instance \u0111\u1ed9c l\u1eadp, ph\u00f9 h\u1ee3p v\u1edbi h\u1ea1 t\u1ea7ng c\u1ea7n ph\u00e2n b\u1ed5 t\u00e0i nguy\u00ean cho nhi\u1ec1u workload ho\u1eb7c ng\u01b0\u1eddi d\u00f9ng. V\u00ec v\u1eady, <strong>thu\u00ea GPU NVIDIA A30<\/strong> l\u00e0 l\u1ef1a ch\u1ecdn \u0111\u00e1ng c\u00e2n nh\u1eafc cho doanh nghi\u1ec7p \u01b0u ti\u00ean AI Inference, v\u1eadn h\u00e0nh \u1ed5n \u0111\u1ecbnh v\u00e0 khai th\u00e1c t\u00e0i nguy\u00ean GPU hi\u1ec7u qu\u1ea3.<\/p>\n<h3 style=\"text-align: justify;\">NVIDIA RTX 3090 24GB \u2013 Hi\u1ec7u n\u0103ng cao, chi ph\u00ed d\u1ec5 ti\u1ebfp c\u1eadn<\/h3>\n<p style=\"text-align: justify;\">RTX 3090 ban \u0111\u1ea7u \u0111\u01b0\u1ee3c NVIDIA \u0111\u1ecbnh v\u1ecb cho ph\u00e2n kh\u00fac \u0111\u1ed3 h\u1ecda v\u00e0 gaming cao c\u1ea5p. Tuy nhi\u00ean, nh\u1edd s\u1edf h\u1eefu 10.496 CUDA Cores v\u00e0 24GB GDDR6X, d\u00f2ng card n\u00e0y c\u0169ng \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng r\u1ed9ng r\u00e3i trong nhi\u1ec1u d\u1ef1 \u00e1n AI. RTX 3090 c\u00f3 hi\u1ec7u n\u0103ng t\u00ednh to\u00e1n FP32 l\u00fd thuy\u1ebft kho\u1ea3ng 35,6 TFLOPS, ph\u00f9 h\u1ee3p v\u1edbi nhi\u1ec1u t\u00e1c v\u1ee5 x\u1eed l\u00fd d\u1eef li\u1ec7u song song. B\u1ed9 nh\u1edb 24GB VRAM cho ph\u00e9p tri\u1ec3n khai m\u1ed9t s\u1ed1 m\u00f4 h\u00ecnh Deep Learning, Computer Vision, Stable Diffusion v\u00e0 LLM \u0111\u00e3 \u0111\u01b0\u1ee3c l\u01b0\u1ee3ng t\u1eed h\u00f3a.<\/p>\n<p style=\"text-align: justify;\">M\u1ed9t l\u1ee3i th\u1ebf quan tr\u1ecdng c\u1ee7a RTX 3090 l\u00e0 h\u1ec7 sinh th\u00e1i CUDA, PyTorch v\u00e0 TensorFlow quen thu\u1ed9c v\u1edbi c\u1ed9ng \u0111\u1ed3ng ph\u00e1t tri\u1ec3n AI. \u0110\u1ed1i v\u1edbi l\u1eadp tr\u00ecnh vi\u00ean, startup ho\u1eb7c nh\u00f3m nghi\u00ean c\u1ee9u c\u00f3 ng\u00e2n s\u00e1ch h\u1ea1n ch\u1ebf, <strong>thu\u00ea GPU RTX 3090<\/strong> c\u00f3 th\u1ec3 mang l\u1ea1i t\u1ef7 l\u1ec7 hi\u1ec7u n\u0103ng tr\u00ean chi ph\u00ed h\u1ea5p d\u1eabn. Tuy nhi\u00ean, GPU n\u00e0y ti\u00eau th\u1ee5 \u0111i\u1ec7n n\u0103ng l\u1edbn h\u01a1n A30 v\u00e0 kh\u00f4ng h\u1ed7 tr\u1ee3 MIG.<\/p>\n<h3 style=\"text-align: justify;\">NVIDIA RTX A6000 48GB \u2013 L\u1ee3i th\u1ebf cho AI c\u1ea7n b\u1ed9 nh\u1edb l\u1edbn<\/h3>\n<p style=\"text-align: justify;\">RTX A6000 l\u00e0 d\u00f2ng GPU Workstation chuy\u00ean nghi\u1ec7p s\u1eed d\u1ee5ng ki\u1ebfn tr\u00fac Ampere, s\u1edf h\u1eefu 10.752 CUDA Cores v\u00e0 \u0111\u1eb7c bi\u1ec7t l\u00e0 48GB GDDR6 h\u1ed7 tr\u1ee3 ECC. Dung l\u01b0\u1ee3ng VRAM g\u1ea5p \u0111\u00f4i RTX 3090 v\u00e0 A30 gi\u00fap RTX A6000 ph\u00f9 h\u1ee3p v\u1edbi c\u00e1c workload AI y\u00eau c\u1ea7u b\u1ed9 nh\u1edb l\u1edbn. \u0110\u00e2y l\u00e0 y\u1ebfu t\u1ed1 quan tr\u1ecdng khi x\u1eed l\u00fd m\u00f4 h\u00ecnh c\u00f3 nhi\u1ec1u tham s\u1ed1, batch size l\u1edbn, d\u1eef li\u1ec7u h\u00ecnh \u1ea3nh \u0111\u1ed9 ph\u00e2n gi\u1ea3i cao ho\u1eb7c c\u00e1c t\u00e1c v\u1ee5 AI kh\u00f4ng th\u1ec3 ch\u1ee9a ho\u00e0n to\u00e0n trong 24GB VRAM.<\/p>\n<p style=\"text-align: justify;\">Ngo\u00e0i ra, RTX A6000 c\u00f2n h\u1ed7 tr\u1ee3 driver chuy\u00ean nghi\u1ec7p, c\u00e1c gi\u1ea3i ph\u00e1p NVIDIA vGPU theo gi\u1ea5y ph\u00e9p ph\u00f9 h\u1ee3p v\u00e0 nhi\u1ec1u \u1ee9ng d\u1ee5ng \u0111\u1ed3 h\u1ecda k\u1ef9 thu\u1eadt. N\u1ebfu d\u1ef1 \u00e1n c\u00f3 y\u00eau c\u1ea7u cao v\u1ec1 b\u1ed9 nh\u1edb GPU, <strong>thu\u00ea GPU RTX A6000 48GB<\/strong> c\u00f3 th\u1ec3 gi\u00fap gi\u1ea3m nhu c\u1ea7u chuy\u1ec3n d\u1eef li\u1ec7u gi\u1eefa VRAM v\u00e0 RAM h\u1ec7 th\u1ed1ng, qua \u0111\u00f3 c\u1ea3i thi\u1ec7n hi\u1ec7u qu\u1ea3 v\u1edbi nh\u1eefng workload b\u1ecb gi\u1edbi h\u1ea1n b\u1ed9 nh\u1edb.<\/p>\n<h2 style=\"text-align: justify;\" data-pm-slice=\"1 1 []\">3. B\u1ea3ng so s\u00e1nh NVIDIA A30, RTX 3090 v\u00e0 RTX A6000<\/h2>\n<table style=\"height: 404px;\" width=\"759\" data-pm-slice=\"3 3 []\">\n<tbody>\n<tr>\n<th>Ti\u00eau ch\u00ed<\/th>\n<th>NVIDIA A30<\/th>\n<th>RTX 3090<\/th>\n<th>RTX A6000<\/th>\n<\/tr>\n<tr>\n<td>Ki\u1ebfn tr\u00fac<\/td>\n<td>Ampere<\/td>\n<td>Ampere<\/td>\n<td>Ampere<\/td>\n<\/tr>\n<tr>\n<td>Ph\u00e2n kh\u00fac<\/td>\n<td>Data Center<\/td>\n<td>Consumer cao c\u1ea5p<\/td>\n<td>Workstation<\/td>\n<\/tr>\n<tr>\n<td>VRAM<\/td>\n<td>24GB<\/td>\n<td>24GB<\/td>\n<td>48GB<\/td>\n<\/tr>\n<tr>\n<td>Lo\u1ea1i b\u1ed9 nh\u1edb<\/td>\n<td>HBM2<\/td>\n<td>GDDR6X<\/td>\n<td>GDDR6 ECC<\/td>\n<\/tr>\n<tr>\n<td>CUDA Cores<\/td>\n<td>3.584<\/td>\n<td>10.496<\/td>\n<td>10.752<\/td>\n<\/tr>\n<tr>\n<td>B\u0103ng th\u00f4ng<\/td>\n<td>933GB\/s<\/td>\n<td>936GB\/s<\/td>\n<td>768GB\/s<\/td>\n<\/tr>\n<tr>\n<td>FP32 l\u00fd thuy\u1ebft<\/td>\n<td>10,3 TFLOPS<\/td>\n<td>35,6 TFLOPS<\/td>\n<td>38,7 TFLOPS<\/td>\n<\/tr>\n<tr>\n<td>C\u00f4ng su\u1ea5t t\u1ed1i \u0111a<\/td>\n<td>165W<\/td>\n<td>350W<\/td>\n<td>300W<\/td>\n<\/tr>\n<tr>\n<td>H\u1ed7 tr\u1ee3 MIG<\/td>\n<td>C\u00f3<\/td>\n<td>Kh\u00f4ng<\/td>\n<td>Kh\u00f4ng<\/td>\n<\/tr>\n<tr>\n<td>\u01afu \u0111i\u1ec3m n\u1ed5i b\u1eadt<\/td>\n<td>AI Data Center<\/td>\n<td>Hi\u1ec7u n\u0103ng\/chi ph\u00ed<\/td>\n<td>VRAM 48GB<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p style=\"text-align: justify;\" data-pm-slice=\"1 1 []\"><em>L\u01b0u \u00fd: RTX A6000 trong b\u00e0i vi\u1ebft l\u00e0 phi\u00ean b\u1ea3n Ampere 48GB, kh\u00f4ng ph\u1ea3i RTX 6000 Ada ho\u1eb7c RTX PRO 6000 Blackwell.<\/em><\/p>\n<p style=\"text-align: justify;\">T\u1eeb b\u1ea3ng tr\u00ean, c\u00f3 th\u1ec3 th\u1ea5y RTX 3090 v\u00e0 RTX A6000 s\u1edf h\u1eefu s\u1ed1 l\u01b0\u1ee3ng CUDA Cores v\u00e0 hi\u1ec7u n\u0103ng FP32 l\u00fd thuy\u1ebft cao h\u01a1n A30. Tuy nhi\u00ean, kh\u00f4ng n\u00ean s\u1eed d\u1ee5ng FP32 l\u00e0m ti\u00eau ch\u00ed duy nh\u1ea5t \u0111\u1ec3 \u0111\u00e1nh gi\u00e1 hi\u1ec7u n\u0103ng AI. Nh\u1eefng workload s\u1eed d\u1ee5ng Tensor Cores, BF16, FP16 ho\u1eb7c INT8 c\u00f3 \u0111\u1eb7c \u0111i\u1ec3m t\u00ednh to\u00e1n kh\u00e1c nhau. Hi\u1ec7u qu\u1ea3 th\u1ef1c t\u1ebf c\u00f2n ph\u1ee5 thu\u1ed9c v\u00e0o ki\u1ebfn tr\u00fac m\u00f4 h\u00ecnh, batch size, \u0111\u1ed9 ch\u00ednh x\u00e1c t\u00ednh to\u00e1n v\u00e0 ph\u1ea7n m\u1ec1m \u0111\u01b0\u1ee3c s\u1eed d\u1ee5ng. Do \u0111\u00f3, l\u1ef1a ch\u1ecdn GPU c\u1ea7n d\u1ef1a tr\u00ean k\u1ebft qu\u1ea3 benchmark \u0111\u00fang v\u1edbi \u1ee9ng d\u1ee5ng th\u1ef1c t\u1ebf thay v\u00ec ch\u1ec9 so s\u00e1nh th\u00f4ng s\u1ed1 l\u00fd thuy\u1ebft.<\/p>\n<p><strong>&gt;&gt; Xem th\u00eam: <a href=\"https:\/\/vnso.vn\/en\/rtx-pro-6000-blackwell-96gb-gia-thue-cloud-gpu-tai-vnso\/\">RTX PRO 6000 Blackwell 96GB: Gi\u00e1 Thu\u00ea Cloud GPU T\u1ea1i VNSO<\/a><\/strong><\/p>\n<h2 style=\"text-align: justify;\" data-pm-slice=\"1 1 []\">4. Thu\u00ea GPU ch\u1ea1y AI n\u00ean ch\u1ecdn d\u00f2ng n\u00e0o?<\/h2>\n<p style=\"text-align: justify;\">Kh\u00f4ng c\u00f3 d\u00f2ng GPU n\u00e0o ph\u00f9 h\u1ee3p nh\u1ea5t v\u1edbi m\u1ecdi b\u00e0i to\u00e1n AI. M\u1ed9t c\u1ea5u h\u00ecnh m\u1ea1nh trong hu\u1ea5n luy\u1ec7n m\u00f4 h\u00ecnh ch\u01b0a ch\u1eafc \u0111\u00e3 t\u1ed1i \u01b0u cho inference, v\u00e0 m\u1ed9t GPU c\u00f3 VRAM l\u1edbn ch\u01b0a ch\u1eafc mang l\u1ea1i t\u1ed1c \u0111\u1ed9 x\u1eed l\u00fd cao nh\u1ea5t.<\/p>\n<h3 style=\"text-align: justify;\">Thu\u00ea GPU NVIDIA A30 cho AI Inference<\/h3>\n<p style=\"text-align: justify;\">AI Inference l\u00e0 qu\u00e1 tr\u00ecnh s\u1eed d\u1ee5ng m\u00f4 h\u00ecnh \u0111\u00e3 \u0111\u01b0\u1ee3c hu\u1ea5n luy\u1ec7n \u0111\u1ec3 \u0111\u01b0a ra d\u1ef1 \u0111o\u00e1n ho\u1eb7c t\u1ea1o k\u1ebft qu\u1ea3 t\u1eeb d\u1eef li\u1ec7u \u0111\u1ea7u v\u00e0o. V\u00ed d\u1ee5, h\u1ec7 th\u1ed1ng nh\u1eadn di\u1ec7n h\u00ecnh \u1ea3nh, ph\u00e2n lo\u1ea1i v\u0103n b\u1ea3n, ph\u00e1t hi\u1ec7n \u0111\u1ed1i t\u01b0\u1ee3ng ho\u1eb7c chatbot doanh nghi\u1ec7p \u0111\u1ec1u c\u00f3 th\u1ec3 s\u1eed d\u1ee5ng GPU \u0111\u1ec3 t\u0103ng t\u1ed1c inference. NVIDIA A30 \u0111\u01b0\u1ee3c thi\u1ebft k\u1ebf cho nh\u00f3m t\u00e1c v\u1ee5 n\u00e0y v\u1edbi b\u1ed9 nh\u1edb HBM2, Tensor Cores v\u00e0 kh\u1ea3 n\u0103ng v\u1eadn h\u00e0nh trong h\u1ec7 th\u1ed1ng Data Center.<\/p>\n<p style=\"text-align: justify;\">Ngo\u00e0i ra, MIG gi\u00fap doanh nghi\u1ec7p ph\u00e2n chia GPU th\u00e0nh nh\u1eefng instance ph\u00f9 h\u1ee3p v\u1edbi t\u1eebng \u1ee9ng d\u1ee5ng, khi h\u1ec7 th\u1ed1ng v\u00e0 d\u1ecbch v\u1ee5 h\u1ed7 tr\u1ee3 c\u1ea5u h\u00ecnh n\u00e0y. A30 \u0111\u1eb7c bi\u1ec7t \u0111\u00e1ng c\u00e2n nh\u1eafc khi doanh nghi\u1ec7p c\u1ea7n tri\u1ec3n khai nhi\u1ec1u t\u00e1c v\u1ee5 AI \u0111\u1ed9c l\u1eadp v\u00e0 mu\u1ed1n t\u1ed1i \u01b0u m\u1ee9c s\u1eed d\u1ee5ng ph\u1ea7n c\u1ee9ng. Tuy v\u1eady, A30 kh\u00f4ng m\u1eb7c nhi\u00ean nhanh h\u01a1n RTX 3090 trong m\u1ecdi b\u00e0i to\u00e1n inference. Doanh nghi\u1ec7p c\u1ea7n ki\u1ec3m tra throughput, latency v\u00e0 m\u1ee9c s\u1eed d\u1ee5ng b\u1ed9 nh\u1edb c\u1ee7a m\u00f4 h\u00ecnh c\u1ee5 th\u1ec3.<\/p>\n<h3 style=\"text-align: justify;\">Thu\u00ea GPU RTX 3090 \u0111\u1ec3 ph\u00e1t tri\u1ec3n v\u00e0 hu\u1ea5n luy\u1ec7n AI<\/h3>\n<p style=\"text-align: justify;\">RTX 3090 l\u00e0 l\u1ef1a ch\u1ecdn ph\u00f9 h\u1ee3p cho nhi\u1ec1u nh\u00f3m ph\u00e1t tri\u1ec3n AI \u0111ang t\u00ecm ki\u1ebfm hi\u1ec7u n\u0103ng t\u00ednh to\u00e1n t\u1ed1t trong gi\u1edbi h\u1ea1n ng\u00e2n s\u00e1ch. V\u1edbi 24GB VRAM, RTX 3090 c\u00f3 th\u1ec3 ph\u1ee5c v\u1ee5 nhi\u1ec1u t\u00e1c v\u1ee5 nh\u01b0:<\/p>\n<ul style=\"text-align: justify;\" data-spread=\"false\">\n<li>Hu\u1ea5n luy\u1ec7n m\u00f4 h\u00ecnh Computer Vision.<\/li>\n<li>Fine-tuning c\u00e1c m\u00f4 h\u00ecnh Deep Learning v\u1eeba v\u00e0 nh\u1ecf.<\/li>\n<li>Ph\u00e1t tri\u1ec3n \u1ee9ng d\u1ee5ng nh\u1eadn di\u1ec7n \u0111\u1ed1i t\u01b0\u1ee3ng.<\/li>\n<li>Ch\u1ea1y Stable Diffusion v\u00e0 c\u00e1c m\u00f4 h\u00ecnh t\u1ea1o \u1ea3nh.<\/li>\n<li>Th\u1eed nghi\u1ec7m LLM v\u1edbi c\u1ea5u h\u00ecnh v\u00e0 ph\u01b0\u01a1ng ph\u00e1p l\u01b0\u1ee3ng t\u1eed h\u00f3a ph\u00f9 h\u1ee3p.<\/li>\n<\/ul>\n<p style=\"text-align: justify;\">Nh\u1edd CUDA Cores m\u1ea1nh v\u00e0 h\u1ec7 sinh th\u00e1i ph\u1ea7n m\u1ec1m ph\u1ed5 bi\u1ebfn, RTX 3090 v\u1eabn l\u00e0 l\u1ef1a ch\u1ecdn th\u1ef1c d\u1ee5ng cho nhi\u1ec1u workload AI. Tuy nhi\u00ean, khi m\u00f4 h\u00ecnh v\u01b0\u1ee3t qu\u00e1 kh\u1ea3 n\u0103ng b\u1ed9 nh\u1edb 24GB, nh\u00e0 ph\u00e1t tri\u1ec3n c\u00f3 th\u1ec3 ph\u1ea3i gi\u1ea3m batch size, s\u1eed d\u1ee5ng gradient checkpointing, l\u01b0\u1ee3ng t\u1eed h\u00f3a ho\u1eb7c offload d\u1eef li\u1ec7u sang RAM. Nh\u1eefng ph\u01b0\u01a1ng ph\u00e1p n\u00e0y gi\u00fap ti\u1ebft ki\u1ec7m VRAM nh\u01b0ng \u0111\u00f4i khi l\u00e0m gi\u1ea3m t\u1ed1c \u0111\u1ed9 x\u1eed l\u00fd. V\u00ec v\u1eady, tr\u01b0\u1edbc khi thu\u00ea GPU RTX 3090, c\u1ea7n x\u00e1c \u0111\u1ecbnh r\u00f5 m\u1ee9c VRAM th\u1ef1c t\u1ebf m\u00e0 m\u00f4 h\u00ecnh s\u1eed d\u1ee5ng.<\/p>\n<h3 style=\"text-align: justify;\">Thu\u00ea GPU RTX A6000 khi m\u00f4 h\u00ecnh AI c\u1ea7n VRAM l\u1edbn<\/h3>\n<p style=\"text-align: justify;\">Dung l\u01b0\u1ee3ng b\u1ed9 nh\u1edb GPU l\u00e0 m\u1ed9t trong nh\u1eefng y\u1ebfu t\u1ed1 quan tr\u1ecdng khi x\u1eed l\u00fd c\u00e1c m\u00f4 h\u00ecnh AI l\u1edbn. Khi th\u1ef1c hi\u1ec7n training ho\u1eb7c inference, VRAM kh\u00f4ng ch\u1ec9 ch\u1ee9a tr\u1ecdng s\u1ed1 m\u00f4 h\u00ecnh m\u00e0 c\u00f2n l\u01b0u tr\u1eef d\u1eef li\u1ec7u trung gian, activation, KV cache v\u00e0 c\u00e1c t\u00e0i nguy\u00ean t\u00ednh to\u00e1n kh\u00e1c. RTX A6000 v\u1edbi 48GB VRAM mang l\u1ea1i l\u1ee3i th\u1ebf r\u00f5 r\u1ec7t khi workload kh\u00f4ng th\u1ec3 v\u1eadn h\u00e0nh hi\u1ec7u qu\u1ea3 tr\u00ean GPU 24GB.<\/p>\n<p style=\"text-align: justify;\">V\u00ed d\u1ee5, c\u00e1c d\u1ef1 \u00e1n x\u1eed l\u00fd \u1ea3nh \u0111\u1ed9 ph\u00e2n gi\u1ea3i cao, m\u00f4 h\u00ecnh ng\u00f4n ng\u1eef c\u00f3 y\u00eau c\u1ea7u b\u1ed9 nh\u1edb l\u1edbn ho\u1eb7c hu\u1ea5n luy\u1ec7n v\u1edbi batch size cao c\u00f3 th\u1ec3 h\u01b0\u1edfng l\u1ee3i t\u1eeb dung l\u01b0\u1ee3ng VRAM n\u00e0y. D\u00f9 v\u1eady, 48GB VRAM kh\u00f4ng c\u00f3 ngh\u0129a RTX A6000 lu\u00f4n x\u1eed l\u00fd nhanh g\u1ea5p \u0111\u00f4i RTX 3090. L\u1ee3i \u00edch l\u1edbn nh\u1ea5t n\u1eb1m \u1edf kh\u1ea3 n\u0103ng ch\u1ee9a nh\u1eefng workload l\u1edbn h\u01a1n trong b\u1ed9 nh\u1edb v\u00e0 gi\u1ea3m nhu c\u1ea7u s\u1eed d\u1ee5ng c\u00e1c k\u1ef9 thu\u1eadt ti\u1ebft ki\u1ec7m VRAM.<\/p>\n<h2 style=\"text-align: justify;\">5. Thu\u00ea GPU Train Model: Nh\u1eefng y\u1ebfu t\u1ed1 c\u1ea7n ki\u1ec3m tra<\/h2>\n<div id=\"attachment_25114\" style=\"width: 810px\" class=\"wp-caption alignnone\"><img decoding=\"async\" aria-describedby=\"caption-attachment-25114\" class=\"size-medium wp-image-25114\" src=\"https:\/\/vnso.vn\/wp-content\/uploads\/2026\/11\/train-ai-800x450.png\" alt=\"Thu\u00ea GPU train model v\u00e0 hu\u1ea5n luy\u1ec7n tr\u00ed tu\u1ec7 nh\u00e2n t\u1ea1o\" width=\"800\" height=\"450\" srcset=\"https:\/\/vnso.vn\/wp-content\/uploads\/2026\/11\/train-ai-800x450.png 800w, https:\/\/vnso.vn\/wp-content\/uploads\/2026\/11\/train-ai-1024x576.png 1024w, https:\/\/vnso.vn\/wp-content\/uploads\/2026\/11\/train-ai-768x432.png 768w, https:\/\/vnso.vn\/wp-content\/uploads\/2026\/11\/train-ai-1536x864.png 1536w, https:\/\/vnso.vn\/wp-content\/uploads\/2026\/11\/train-ai-2048x1152.png 2048w, https:\/\/vnso.vn\/wp-content\/uploads\/2026\/11\/train-ai-18x10.png 18w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/><p id=\"caption-attachment-25114\" class=\"wp-caption-text\">Thu\u00ea GPU train model v\u00e0 hu\u1ea5n luy\u1ec7n tr\u00ed tu\u1ec7 nh\u00e2n t\u1ea1o<\/p><\/div>\n<p style=\"text-align: justify;\">\u0110\u1ed1i v\u1edbi nhu c\u1ea7u <strong>thu\u00ea GPU train model<\/strong>, l\u1ef1a ch\u1ecdn ph\u1ea7n c\u1ee9ng c\u1ea7n b\u1eaft \u0111\u1ea7u t\u1eeb \u0111\u1eb7c \u0111i\u1ec3m m\u00f4 h\u00ecnh thay v\u00ec ch\u1ec9 nh\u00ecn v\u00e0o t\u00ean GPU.<\/p>\n<h3 style=\"text-align: justify;\">Dung l\u01b0\u1ee3ng VRAM<\/h3>\n<p style=\"text-align: justify;\">VRAM quy\u1ebft \u0111\u1ecbnh kh\u1ea3 n\u0103ng l\u01b0u tr\u1eef m\u00f4 h\u00ecnh v\u00e0 d\u1eef li\u1ec7u ph\u1ee5c v\u1ee5 qu\u00e1 tr\u00ecnh t\u00ednh to\u00e1n tr\u00ean GPU. M\u00f4 h\u00ecnh c\u00e0ng l\u1edbn, sequence length c\u00e0ng d\u00e0i ho\u1eb7c batch size c\u00e0ng cao th\u00ec y\u00eau c\u1ea7u b\u1ed9 nh\u1edb th\u01b0\u1eddng c\u00e0ng t\u0103ng. N\u1ebfu m\u00f4 h\u00ecnh ch\u1ec9 c\u1ea7n kho\u1ea3ng 12\u201320GB VRAM, c\u00e1c GPU 24GB c\u00f3 th\u1ec3 \u0111\u00e1p \u1ee9ng trong nh\u1eefng \u0111i\u1ec1u ki\u1ec7n nh\u1ea5t \u0111\u1ecbnh. Ng\u01b0\u1ee3c l\u1ea1i, nh\u1eefng workload c\u1ea7n tr\u00ean 24GB VRAM c\u00f3 th\u1ec3 ph\u00f9 h\u1ee3p h\u01a1n v\u1edbi RTX A6000 ho\u1eb7c c\u00e1c d\u00f2ng GPU dung l\u01b0\u1ee3ng l\u1edbn kh\u00e1c.<\/p>\n<h3 style=\"text-align: justify;\">Hi\u1ec7u n\u0103ng Tensor Cores<\/h3>\n<p style=\"text-align: justify;\">C\u00e1c m\u00f4 h\u00ecnh Deep Learning th\u01b0\u1eddng t\u1eadn d\u1ee5ng Tensor Cores \u0111\u1ec3 t\u0103ng t\u1ed1c ph\u00e9p to\u00e1n ma tr\u1eadn. Tuy nhi\u00ean, hi\u1ec7u n\u0103ng c\u00f2n ph\u1ee5 thu\u1ed9c v\u00e0o precision nh\u01b0 FP32, TF32, FP16 ho\u1eb7c BF16. Do \u0111\u00f3, s\u1ed1 CUDA Cores ho\u1eb7c TFLOPS FP32 kh\u00f4ng ph\u1ea3i l\u00fac n\u00e0o c\u0169ng ph\u1ea3n \u00e1nh t\u1ed1c \u0111\u1ed9 train model th\u1ef1c t\u1ebf.<\/p>\n<h3 style=\"text-align: justify;\">CPU, RAM v\u00e0 t\u1ed1c \u0111\u1ed9 l\u01b0u tr\u1eef<\/h3>\n<p style=\"text-align: justify;\">GPU m\u1ea1nh nh\u01b0ng CPU kh\u00f4ng \u0111\u1ee7 n\u0103ng l\u1ef1c x\u1eed l\u00fd d\u1eef li\u1ec7u c\u0169ng c\u00f3 th\u1ec3 d\u1eabn \u0111\u1ebfn t\u00ecnh tr\u1ea1ng GPU ph\u1ea3i ch\u1edd. T\u01b0\u01a1ng t\u1ef1, RAM h\u1ec7 th\u1ed1ng h\u1ea1n ch\u1ebf ho\u1eb7c \u1ed5 c\u1ee9ng ch\u1eadm s\u1ebd \u1ea3nh h\u01b0\u1edfng \u0111\u1ebfn qu\u00e1 tr\u00ecnh t\u1ea3i dataset, ti\u1ec1n x\u1eed l\u00fd d\u1eef li\u1ec7u v\u00e0 l\u01b0u checkpoint. Khi thu\u00ea GPU ch\u1ea1y AI, c\u1ea7n c\u00e2n nh\u1eafc to\u00e0n b\u1ed9 c\u1ea5u h\u00ecnh m\u00e1y ch\u1ee7, bao g\u1ed3m CPU, RAM, GPU, NVMe v\u00e0 h\u1ec7 th\u1ed1ng m\u1ea1ng.<\/p>\n<h3 style=\"text-align: justify;\">Kh\u1ea3 n\u0103ng m\u1edf r\u1ed9ng<\/h3>\n<p style=\"text-align: justify;\">D\u1ef1 \u00e1n AI c\u00f3 th\u1ec3 b\u1eaft \u0111\u1ea7u b\u1eb1ng m\u1ed9t m\u00f4 h\u00ecnh nh\u1ecf nh\u01b0ng ph\u00e1t tri\u1ec3n nhanh theo th\u1eddi gian. V\u00ec v\u1eady, doanh nghi\u1ec7p c\u1ea7n t\u00ednh \u0111\u1ebfn kh\u1ea3 n\u0103ng n\u00e2ng c\u1ea5p dung l\u01b0\u1ee3ng VRAM, thay \u0111\u1ed5i d\u00f2ng GPU ho\u1eb7c tri\u1ec3n khai nhi\u1ec1u GPU trong t\u01b0\u01a1ng lai. \u0110\u1ed1i v\u1edbi c\u00e1c d\u1ef1 \u00e1n d\u00e0i h\u1ea1n, n\u00ean l\u1ef1a ch\u1ecdn c\u1ea5u h\u00ecnh c\u00f3 kh\u1ea3 n\u0103ng \u0111\u00e1p \u1ee9ng c\u1ea3 nhu c\u1ea7u hi\u1ec7n t\u1ea1i l\u1eabn k\u1ebf ho\u1ea1ch m\u1edf r\u1ed9ng.<\/p>\n<h2 style=\"text-align: justify;\">6. So s\u00e1nh chi ph\u00ed khi thu\u00ea GPU A30, RTX 3090 v\u00e0 RTX A6000<\/h2>\n<p style=\"text-align: justify;\">Chi ph\u00ed l\u00e0 y\u1ebfu t\u1ed1 quan tr\u1ecdng nh\u01b0ng kh\u00f4ng n\u00ean tr\u1edf th\u00e0nh ti\u00eau ch\u00ed duy nh\u1ea5t khi l\u1ef1a ch\u1ecdn GPU. Th\u00f4ng th\u01b0\u1eddng, RTX 3090 \u0111\u01b0\u1ee3c \u0111\u00e1nh gi\u00e1 cao nh\u1edd hi\u1ec7u n\u0103ng t\u00ednh to\u00e1n t\u1ed1t trong ph\u00e2n kh\u00fac gi\u00e1 d\u1ec5 ti\u1ebfp c\u1eadn. NVIDIA A30 ph\u00f9 h\u1ee3p v\u1edbi nh\u1eefng doanh nghi\u1ec7p \u01b0u ti\u00ean t\u00ednh n\u0103ng Data Center, hi\u1ec7u qu\u1ea3 s\u1eed d\u1ee5ng \u0111i\u1ec7n n\u0103ng v\u00e0 kh\u1ea3 n\u0103ng ph\u00e2n b\u1ed5 t\u00e0i nguy\u00ean.<\/p>\n<p style=\"text-align: justify;\">Trong khi \u0111\u00f3, RTX A6000 c\u00f3 l\u1ee3i th\u1ebf v\u1ec1 VRAM, nh\u01b0ng chi ph\u00ed thu\u00ea th\u01b0\u1eddng cao h\u01a1n c\u00e1c d\u00f2ng GPU 24GB. Khi so s\u00e1nh b\u00e1o gi\u00e1, doanh nghi\u1ec7p n\u00ean xem x\u00e9t t\u1ed5ng chi ph\u00ed v\u1eadn h\u00e0nh thay v\u00ec ch\u1ec9 d\u1ef1a v\u00e0o gi\u00e1 thu\u00ea GPU. V\u00ed d\u1ee5, m\u1ed9t GPU c\u00f3 gi\u00e1 thu\u00ea th\u1ea5p h\u01a1n nh\u01b0ng kh\u00f4ng \u0111\u1ee7 VRAM c\u00f3 th\u1ec3 khi\u1ebfn th\u1eddi gian hu\u1ea5n luy\u1ec7n t\u0103ng do ph\u1ea3i offload d\u1eef li\u1ec7u. Ng\u01b0\u1ee3c l\u1ea1i, thu\u00ea GPU \u0111\u1eaft ti\u1ec1n v\u1edbi dung l\u01b0\u1ee3ng b\u1ed9 nh\u1edb v\u01b0\u1ee3t xa nhu c\u1ea7u th\u1ef1c t\u1ebf c\u0169ng g\u00e2y l\u00e3ng ph\u00ed ng\u00e2n s\u00e1ch. V\u00ec v\u1eady, l\u1ef1a ch\u1ecdn h\u1ee3p l\u00fd l\u00e0 c\u1ea5u h\u00ecnh c\u00f3 th\u1ec3 ho\u00e0n th\u00e0nh workload trong th\u1eddi gian mong mu\u1ed1n v\u1edbi t\u1ed5ng chi ph\u00ed ph\u00f9 h\u1ee3p.<\/p>\n<h2 style=\"text-align: justify;\">7. Thu\u00ea GPU theo th\u00e1ng t\u1ea1i VNSO c\u00f3 nh\u1eefng l\u1ee3i \u00edch g\u00ec?<\/h2>\n<div id=\"attachment_25117\" style=\"width: 810px\" class=\"wp-caption alignnone\"><img decoding=\"async\" aria-describedby=\"caption-attachment-25117\" class=\"size-medium wp-image-25117\" src=\"https:\/\/vnso.vn\/wp-content\/uploads\/2026\/11\/gpu-theo-thang-moi-co-logo-1-800x450.png\" alt=\"Thu\u00ea gpu theo th\u00e1ng b\u1ea3ng gi\u00e1 t\u1ea1i VNSO\" width=\"800\" height=\"450\" srcset=\"https:\/\/vnso.vn\/wp-content\/uploads\/2026\/11\/gpu-theo-thang-moi-co-logo-1-800x450.png 800w, https:\/\/vnso.vn\/wp-content\/uploads\/2026\/11\/gpu-theo-thang-moi-co-logo-1-1024x576.png 1024w, https:\/\/vnso.vn\/wp-content\/uploads\/2026\/11\/gpu-theo-thang-moi-co-logo-1-768x432.png 768w, https:\/\/vnso.vn\/wp-content\/uploads\/2026\/11\/gpu-theo-thang-moi-co-logo-1-18x10.png 18w, https:\/\/vnso.vn\/wp-content\/uploads\/2026\/11\/gpu-theo-thang-moi-co-logo-1.png 1200w\" sizes=\"(max-width: 800px) 100vw, 800px\" \/><p id=\"caption-attachment-25117\" class=\"wp-caption-text\">Thu\u00ea gpu theo th\u00e1ng b\u1ea3ng gi\u00e1 t\u1ea1i VNSO<\/p><\/div>\n<p style=\"text-align: justify;\">VNSO cung c\u1ea5p c\u00e1c gi\u1ea3i ph\u00e1p h\u1ea1 t\u1ea7ng GPU ph\u1ee5c v\u1ee5 nhu c\u1ea7u nghi\u00ean c\u1ee9u, ph\u00e1t tri\u1ec3n v\u00e0 tri\u1ec3n khai AI cho c\u00e1 nh\u00e2n, doanh nghi\u1ec7p v\u00e0 t\u1ed5 ch\u1ee9c c\u00f4ng ngh\u1ec7. Danh m\u1ee5c GPU \u0111a d\u1ea1ng gi\u00fap kh\u00e1ch h\u00e0ng l\u1ef1a ch\u1ecdn ph\u1ea7n c\u1ee9ng theo t\u1eebng nh\u00f3m workload, t\u1eeb ph\u00e1t tri\u1ec3n \u1ee9ng d\u1ee5ng AI \u0111\u1ebfn nh\u1eefng d\u1ef1 \u00e1n y\u00eau c\u1ea7u n\u0103ng l\u1ef1c x\u1eed l\u00fd chuy\u00ean s\u00e2u.<\/p>\n<h3 style=\"text-align: justify;\">\u0110a d\u1ea1ng c\u1ea5u h\u00ecnh GPU NVIDIA<\/h3>\n<p style=\"text-align: justify;\">Kh\u00e1ch h\u00e0ng c\u00f3 th\u1ec3 trao \u0111\u1ed5i nhu c\u1ea7u s\u1eed d\u1ee5ng nh\u1eefng d\u00f2ng GPU nh\u01b0 NVIDIA A30, RTX 3090, RTX A6000 c\u00f9ng c\u00e1c d\u00f2ng GPU kh\u00e1c trong danh m\u1ee5c VNSO. Kh\u1ea3 n\u0103ng cung c\u1ea5p t\u1eebng c\u1ea5u h\u00ecnh ph\u1ee5 thu\u1ed9c t\u00ecnh tr\u1ea1ng t\u00e0i nguy\u00ean t\u1ea1i th\u1eddi \u0111i\u1ec3m \u0111\u0103ng k\u00fd.<\/p>\n<h3 style=\"text-align: justify;\">L\u1ef1a ch\u1ecdn CPU, RAM v\u00e0 l\u01b0u tr\u1eef ph\u00f9 h\u1ee3p<\/h3>\n<p style=\"text-align: justify;\">B\u00ean c\u1ea1nh GPU, c\u1ea5u h\u00ecnh CPU, RAM v\u00e0 NVMe c\u00f3 \u1ea3nh h\u01b0\u1edfng tr\u1ef1c ti\u1ebfp \u0111\u1ebfn hi\u1ec7u qu\u1ea3 s\u1eed d\u1ee5ng h\u1ec7 th\u1ed1ng. VNSO h\u1ed7 tr\u1ee3 t\u01b0 v\u1ea5n l\u1ef1a ch\u1ecdn c\u1ea5u h\u00ecnh theo \u0111\u1eb7c \u0111i\u1ec3m workload, ng\u00e2n s\u00e1ch v\u00e0 y\u00eau c\u1ea7u tri\u1ec3n khai.<\/p>\n<h3 style=\"text-align: justify;\">Ch\u1ee7 \u0111\u1ed9ng ng\u00e2n s\u00e1ch d\u1ef1 \u00e1n<\/h3>\n<p style=\"text-align: justify;\"><a href=\"https:\/\/gpu.vnso.vn\/\">Thu\u00ea GPU theo th\u00e1ng<\/a> ph\u00f9 h\u1ee3p v\u1edbi doanh nghi\u1ec7p \u0111ang tri\u1ec3n khai d\u1ef1 \u00e1n AI theo t\u1eebng giai \u0111o\u1ea1n, gi\u00fap d\u1ef1 to\u00e1n chi ph\u00ed h\u1ea1 t\u1ea7ng v\u00e0 h\u1ea1n ch\u1ebf kho\u1ea3n \u0111\u1ea7u t\u01b0 ph\u1ea7n c\u1ee9ng ban \u0111\u1ea7u. Th\u1eddi h\u1ea1n thu\u00ea t\u1ed1i thi\u1ec3u, c\u1ea5u h\u00ecnh, gi\u00e1 d\u1ecbch v\u1ee5 v\u00e0 \u0111i\u1ec1u ki\u1ec7n tri\u1ec3n khai c\u1ea7n \u0111\u01b0\u1ee3c x\u00e1c nh\u1eadn theo g\u00f3i GPU c\u1ee5 th\u1ec3.<\/p>\n<h3 style=\"text-align: justify;\">H\u1ed7 tr\u1ee3 l\u1ef1a ch\u1ecdn GPU theo nhu c\u1ea7u<\/h3>\n<p style=\"text-align: justify;\">Thay v\u00ec ch\u1ec9 l\u1ef1a ch\u1ecdn GPU c\u00f3 gi\u00e1 cao nh\u1ea5t, kh\u00e1ch h\u00e0ng c\u00f3 th\u1ec3 cung c\u1ea5p th\u00f4ng tin v\u1ec1 m\u00f4 h\u00ecnh AI, dung l\u01b0\u1ee3ng VRAM c\u1ea7n s\u1eed d\u1ee5ng, dataset v\u00e0 y\u00eau c\u1ea7u hi\u1ec7u n\u0103ng \u0111\u1ec3 \u0111\u01b0\u1ee3c t\u01b0 v\u1ea5n c\u1ea5u h\u00ecnh ph\u00f9 h\u1ee3p.<\/p>\n<p style=\"text-align: justify;\">\u0110\u1ec3 t\u00ecm hi\u1ec3u th\u00eam, b\u1ea1n c\u00f3 th\u1ec3 tham kh\u1ea3o d\u1ecbch v\u1ee5 <a href=\"https:\/\/vnso.vn\/en\/may-chu-gpu\/\">thu\u00ea m\u00e1y ch\u1ee7 GPU t\u1ea1i VNSO<\/a>.<\/p>\n<p>&nbsp;<\/p>\n\n<div class=\"wpcf7 no-js\" id=\"wpcf7-f22528-o1\" lang=\"en-US\" dir=\"ltr\">\n<div class=\"screen-reader-response\"><p role=\"status\" aria-live=\"polite\" aria-atomic=\"true\"><\/p> <ul><\/ul><\/div>\n<form action=\"\/en\/wp-json\/wp\/v2\/posts\/25112#wpcf7-f22528-o1\" method=\"post\" class=\"wpcf7-form init\" aria-label=\"Contact form\" novalidate=\"novalidate\" data-status=\"init\" data-trp-original-action=\"\/en\/wp-json\/wp\/v2\/posts\/25112#wpcf7-f22528-o1\">\n<div style=\"display: none;\">\n<input type=\"hidden\" name=\"_wpcf7\" value=\"22528\" \/>\n<input type=\"hidden\" name=\"_wpcf7_version\" value=\"5.9.5\" \/>\n<input type=\"hidden\" name=\"_wpcf7_locale\" value=\"en_US\" \/>\n<input type=\"hidden\" name=\"_wpcf7_unit_tag\" value=\"wpcf7-f22528-o1\" \/>\n<input type=\"hidden\" name=\"_wpcf7_container_post\" value=\"0\" \/>\n<input type=\"hidden\" name=\"_wpcf7_posted_data_hash\" value=\"\" \/>\n<input type=\"hidden\" name=\"_wpcf7_recaptcha_response\" value=\"\" \/>\n<\/div>\n<style>\n .popup-template-wrap .wpcf7-list-item {\n display: inline-block;\n margin: 0 1em 0 0;\n width: 127px;\n}\n<\/style>\n<div class=\"d-flex gap-3\">\n\t<p><label> <span class=\"wpcf7-form-control-wrap\" data-name=\"your-name\"><input size=\"40\" class=\"wpcf7-form-control wpcf7-text wpcf7-validates-as-required\" autocomplete=\"name\" aria-required=\"true\" aria-invalid=\"false\" placeholder=\"Your name\/company (*)\" value=\"\" type=\"text\" name=\"your-name\" \/><\/span> <\/label>\n\t<\/p>\n\t<p><label> <span class=\"wpcf7-form-control-wrap\" data-name=\"your-phone\"><input size=\"40\" class=\"wpcf7-form-control wpcf7-tel wpcf7-validates-as-required wpcf7-text wpcf7-validates-as-tel\" id=\"phone\" aria-required=\"true\" aria-invalid=\"false\" placeholder=\"S\u1ed1 \u0111i\u1ec7n tho\u1ea1i (*)\" value=\"\" type=\"tel\" name=\"your-phone\" \/><\/span> <\/label>\n\t<\/p>\n<\/div>\n<p><label> <span class=\"wpcf7-form-control-wrap\" data-name=\"your-email\"><input size=\"40\" class=\"wpcf7-form-control wpcf7-email wpcf7-validates-as-required wpcf7-text wpcf7-validates-as-email\" autocomplete=\"email\" aria-required=\"true\" aria-invalid=\"false\" placeholder=\"Email c\u00f4ng ty\/c\u00e1 nh\u00e2n (*)\" value=\"\" type=\"email\" name=\"your-email\" \/><\/span> <\/label>\n<\/p>\n<div style=\"text-align: left;\">\n\t<p><label class=\"label-select text-left\"><b> Service you're interested in:<\/b> (Choose one) <\/label><br \/>\n<span class=\"wpcf7-form-control-wrap\" data-name=\"your-service\"><span class=\"wpcf7-form-control wpcf7-checkbox wpcf7-validates-as-required wpcf7-exclusive-checkbox\"><span class=\"wpcf7-list-item first\"><input type=\"checkbox\" name=\"your-service\" value=\"Dedicated Server\" \/><span class=\"wpcf7-list-item-label\">Dedicated Server<\/span><\/span><span class=\"wpcf7-list-item\"><input type=\"checkbox\" name=\"your-service\" value=\"Server GPU\" \/><span class=\"wpcf7-list-item-label\">Server GPU<\/span><\/span><span class=\"wpcf7-list-item\"><input type=\"checkbox\" name=\"your-service\" value=\"Cloud GPU\" \/><span class=\"wpcf7-list-item-label\">Cloud GPU<\/span><\/span><span class=\"wpcf7-list-item\"><input type=\"checkbox\" name=\"your-service\" value=\"Cloud Camera AI\" \/><span class=\"wpcf7-list-item-label\">Cloud Camera AI<\/span><\/span><span class=\"wpcf7-list-item\"><input type=\"checkbox\" name=\"your-service\" value=\"Hosting\" \/><span class=\"wpcf7-list-item-label\">Hosting<\/span><\/span><span class=\"wpcf7-list-item\"><input type=\"checkbox\" name=\"your-service\" value=\"VPS\" \/><span class=\"wpcf7-list-item-label\">VPS<\/span><\/span><span class=\"wpcf7-list-item\"><input type=\"checkbox\" name=\"your-service\" value=\"Cloud Server\" \/><span class=\"wpcf7-list-item-label\">Cloud Server<\/span><\/span><span class=\"wpcf7-list-item\"><input type=\"checkbox\" name=\"your-service\" value=\"Enterprise Cloud\" \/><span class=\"wpcf7-list-item-label\">Enterprise Cloud<\/span><\/span><span class=\"wpcf7-list-item\"><input type=\"checkbox\" name=\"your-service\" value=\"Private Cloud\" \/><span class=\"wpcf7-list-item-label\">Private Cloud<\/span><\/span><span class=\"wpcf7-list-item\"><input type=\"checkbox\" name=\"your-service\" value=\"Cloud Storage\" \/><span class=\"wpcf7-list-item-label\">Cloud Storage<\/span><\/span><span class=\"wpcf7-list-item\"><input type=\"checkbox\" name=\"your-service\" value=\"CDN\" \/><span class=\"wpcf7-list-item-label\">CDN<\/span><\/span><span class=\"wpcf7-list-item\"><input type=\"checkbox\" name=\"your-service\" value=\"Anti-DDoS\" \/><span class=\"wpcf7-list-item-label\">Anti-DDoS<\/span><\/span><span class=\"wpcf7-list-item\"><input type=\"checkbox\" name=\"your-service\" value=\"C\u00e1c d\u1ecbch v\u1ee5 kh\u00e1c\" \/><span class=\"wpcf7-list-item-label\">C\u00e1c d\u1ecbch v\u1ee5 kh\u00e1c<\/span><\/span><span class=\"wpcf7-list-item last\"><input type=\"checkbox\" name=\"your-service\" value=\"T\u01b0 v\u1ea5n\" \/><span class=\"wpcf7-list-item-label\">T\u01b0 v\u1ea5n<\/span><\/span><\/span><\/span>\n\t<\/p>\n<\/div>\n<div class=\"m-auto text-center\">\n\t<p><input class=\"wpcf7-form-control wpcf7-submit has-spinner\" type=\"submit\" value=\"Sign Up Now\" \/>\n\t<\/p>\n<\/div><div class=\"wpcf7-response-output\" aria-hidden=\"true\"><\/div>\n<input type=\"hidden\" name=\"trp-form-language\" value=\"en\"\/><\/form>\n<\/div>\n\n<p><strong>Th\u00f4ng tin li\u00ean h\u1ec7<\/strong><br \/>\n\u0110\u1ec3 t\u00ecm hi\u1ec3u th\u00f4ng tin v\u1ec1 c\u00e1c gi\u1ea3i ph\u00e1p CNTT, Cloud Server, GPU v\u00e0 m\u00e0n h\u00ecnh LED BOE h\u00e0ng \u0111\u1ea7u Vi\u1ec7t Nam, Qu\u00fd kh\u00e1ch vui l\u00f2ng li\u00ean h\u1ec7 ch\u00fang t\u00f4i theo th\u00f4ng tin d\u01b0\u1edbi \u0111\u00e2y:<\/p>\n<p>C\u00d4NG TY C\u1ed4 PH\u1ea6N C\u00d4NG NGH\u1ec6 VNSO \u2013 SINCE 2015<\/p>\n<p>\u2013 Website: <a 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H\u1ed3 Ch\u00ed Minh<br \/>\n\u2013 VPGD \u0110\u00e0 N\u1eb5ng: 30 Nguy\u1ec5n H\u1eefu Th\u1ecd, Ph\u01b0\u1eddng H\u1ea3i Ch\u00e2u, \u0110\u00e0 N\u1eb5ng<br \/>\n\u2013 VPGD H\u00e0 N\u1ed9i: 132 V\u0169 Ph\u1ea1m H\u00e0m, Ph\u01b0\u1eddng Y\u00ean H\u00f2a, H\u00e0 N\u1ed9i<\/p>","protected":false},"excerpt":{"rendered":"<p>Thu\u00ea GPU \u0111ang tr\u1edf th\u00e0nh gi\u1ea3i ph\u00e1p \u0111\u01b0\u1ee3c nhi\u1ec1u doanh nghi\u1ec7p, l\u1eadp tr\u00ecnh vi\u00ean v\u00e0 nh\u00f3m nghi\u00ean c\u1ee9u AI l\u1ef1a ch\u1ecdn \u0111\u1ec3 ti\u1ebfp c\u1eadn s\u1ee9c m\u1ea1nh t\u00ednh to\u00e1n cao m\u00e0 kh\u00f4ng c\u1ea7n \u0111\u1ea7u t\u01b0 h\u1ec7 th\u1ed1ng ph\u1ea7n c\u1ee9ng \u0111\u1eaft \u0111\u1ecf. 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