{"id":23216,"date":"2025-09-16T16:46:16","date_gmt":"2025-09-16T09:46:16","guid":{"rendered":"https:\/\/vnso.vn\/?p=23216"},"modified":"2025-09-16T17:27:24","modified_gmt":"2025-09-16T10:27:24","slug":"thue-nvidia-rtx-5880-ada-48gb-gddr6-voi-ecc","status":"publish","type":"post","link":"https:\/\/vnso.vn\/en\/thue-nvidia-rtx-5880-ada-48gb-gddr6-voi-ecc\/","title":{"rendered":"Thu\u00ea NVIDIA RTX 5880 Ada 48GB GDDR6 v\u1edbi ECC"},"content":{"rendered":"<p style=\"text-align: justify;\">T\u1eeb d\u1ef1ng h\u00ecnh 3D, hu\u1ea5n luy\u1ec7n AI \u0111\u1ebfn x\u1eed l\u00fd d\u1eef li\u1ec7u ph\u1ee9c t\u1ea1p, <strong data-start=\"776\" data-end=\"799\">NVIDIA RTX 5880 Ada<\/strong> \u0111\u00e1p \u1ee9ng tr\u1ecdn v\u1eb9n v\u1edbi hi\u1ec7u n\u0103ng cao v\u00e0 b\u1ed9 nh\u1edb 48GB ECC. Xem qua b\u00e0i vi\u1ebft sau \u0111\u1ec3 kh\u00e1m ph\u00e1 chi ti\u1ebft c\u1ea5u h\u00ecnh v\u00e0 d\u1ecbch v\u1ee5 thu\u00ea GPU chuy\u00ean nghi\u1ec7p t\u1eeb VNSO.<\/p>\n<p style=\"text-align: justify;\"><strong>Thu\u00ea Server GPU NVIDIA RTX 5880 Ada 48GB GDDR6 v\u1edbi ECC ch\u1ec9 t\u1eeb 28.900.000 \u0111\/th\u00e1ng t\u1ea1i VNSO<\/strong><\/p>\n<p style=\"text-align: justify;\">Gi\u00e1 thu\u00ea: <span style=\"color: #333399;\"><em><strong>28<\/strong><\/em><em><strong data-start=\"499\" data-end=\"555\">.900.000 \u0111\/th\u00e1ng<\/strong><\/em><\/span><br \/>\nCPU: 2 x Intel Xeon Gold Series<br \/>\nRAM: 64 GB<br \/>\nDisk: 240GB SSD NVMe<br \/>\nGPU: 01 x Nvidia RTX 5880<br \/>\nNetwork: 200Mbps<\/p>\n<p style=\"text-align: justify;\"><em>T\u1ea5t c\u1ea3 c\u00e1c th\u00f4ng s\u1ed1 k\u1ef9 thu\u1eadt, c\u1ea5u h\u00ecnh tr\u00ean \u0111\u1ec1u c\u00f3 th\u1ec3 thay \u0111\u1ed5i theo \u0111\u00fang nhu c\u1ea7u c\u1ee7a b\u1ea1n.<\/em><\/p>\n<p style=\"text-align: justify;\" data-start=\"182\" data-end=\"604\">&gt;&gt;&gt; \u0110\u0103ng k\u00fd ngay <a href=\"https:\/\/gpu.vnso.vn\/\"><strong>Server AI\/GPU, Cloud GPU VNSO<\/strong><\/a> \u2013 <em>t\u01b0 v\u1ea5n,<\/em><em> b\u00e1o gi\u00e1 &amp; d\u00f9ng th\u1eed mi\u1ec5n ph\u00ed<\/em>!<\/p>\n<p style=\"text-align: justify;\" data-start=\"5253\" data-end=\"5426\">\n<div class=\"wpcf7 no-js\" id=\"wpcf7-f15879-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\/23216#wpcf7-f15879-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\/23216#wpcf7-f15879-o1\">\n<div style=\"display: none;\">\n<input type=\"hidden\" name=\"_wpcf7\" value=\"15879\" \/>\n<input type=\"hidden\" name=\"_wpcf7_version\" 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value=\"en\"\/><\/form>\n<\/div>\n<\/p>\n<h2 style=\"text-align: justify;\">1. NVIDIA RTX 5880 Ada 48GB GDDR6 l\u00e0 g\u00ec?<\/h2>\n<p style=\"text-align: justify;\" data-start=\"216\" data-end=\"613\">NVIDIA RTX 5880 Ada Generation l\u00e0 d\u00f2ng GPU workstation chuy\u00ean nghi\u1ec7p \u0111\u01b0\u1ee3c x\u00e2y d\u1ef1ng tr\u00ean ki\u1ebfn tr\u00fac Ada Lovelace. S\u1edf h\u1eefu 14.080 CUDA cores, 440 Tensor cores, 110 RT cores c\u00f9ng 48GB b\u1ed9 nh\u1edb GDDR6 ECC, RTX 5880 mang \u0111\u1ebfn s\u1ef1 c\u00e2n b\u1eb1ng gi\u1eefa hi\u1ec7u n\u0103ng m\u1ea1nh m\u1ebd v\u00e0 dung l\u01b0\u1ee3ng b\u1ed9 nh\u1edb l\u1edbn, ph\u00f9 h\u1ee3p cho c\u00e1c t\u00e1c v\u1ee5 AI, d\u1ef1ng h\u00ecnh 3D, m\u00f4 ph\u1ecfng khoa h\u1ecdc, x\u1eed l\u00fd d\u1eef li\u1ec7u v\u00e0 thi\u1ebft k\u1ebf k\u1ef9 thu\u1eadt.<\/p>\n<p style=\"text-align: justify;\" data-start=\"615\" data-end=\"990\">V\u1edbi b\u0103ng th\u00f4ng b\u1ed9 nh\u1edb 960 GB\/s, giao ti\u1ebfp PCIe Gen 4 x16 v\u00e0 c\u00f4ng su\u1ea5t ti\u00eau th\u1ee5 kho\u1ea3ng 285W, RTX 5880 kh\u00f4ng ch\u1ec9 h\u1ed7 tr\u1ee3 c\u00e1c d\u1ef1 \u00e1n ph\u1ee9c t\u1ea1p m\u00e0 c\u00f2n \u0111\u1ea3m b\u1ea3o \u0111\u1ed9 \u1ed5n \u0111\u1ecbnh cao trong m\u00f4i tr\u01b0\u1eddng workstation v\u00e0 server. \u0110\u00e2y l\u00e0 l\u1ef1a ch\u1ecdn n\u1eb1m gi\u1eefa RTX 5000 Ada v\u00e0 RTX 6000 Ada, h\u01b0\u1edbng \u0111\u1ebfn ng\u01b0\u1eddi d\u00f9ng c\u1ea7n VRAM l\u1edbn, hi\u1ec7u su\u1ea5t \u0111\u1ed3 h\u1ecda v\u00e0 AI m\u1ea1nh m\u1ebd m\u00e0 v\u1eabn t\u1ed1i \u01b0u chi ph\u00ed \u0111\u1ea7u t\u01b0.<\/p>\n<p style=\"text-align: justify;\" data-start=\"615\" data-end=\"990\"><a href=\"https:\/\/gpu.vnso.vn\/\"><img fetchpriority=\"high\" decoding=\"async\" class=\"aligncenter size-full wp-image-23220\" src=\"https:\/\/vnso.vn\/wp-content\/uploads\/2025\/09\/NVIDIA-RTX-5880-Ada-48GB-GDDR6-ECC.jpg\" alt=\"NVIDIA-RTX-5880-Ada-48GB-GDDR6-ECC\" width=\"1200\" height=\"624\" srcset=\"https:\/\/vnso.vn\/wp-content\/uploads\/2025\/09\/NVIDIA-RTX-5880-Ada-48GB-GDDR6-ECC.jpg 1200w, https:\/\/vnso.vn\/wp-content\/uploads\/2025\/09\/NVIDIA-RTX-5880-Ada-48GB-GDDR6-ECC-800x416.jpg 800w, https:\/\/vnso.vn\/wp-content\/uploads\/2025\/09\/NVIDIA-RTX-5880-Ada-48GB-GDDR6-ECC-1024x532.jpg 1024w, https:\/\/vnso.vn\/wp-content\/uploads\/2025\/09\/NVIDIA-RTX-5880-Ada-48GB-GDDR6-ECC-768x399.jpg 768w, https:\/\/vnso.vn\/wp-content\/uploads\/2025\/09\/NVIDIA-RTX-5880-Ada-48GB-GDDR6-ECC-18x9.jpg 18w\" sizes=\"(max-width: 1200px) 100vw, 1200px\" \/><\/a><\/p>\n<h3 style=\"text-align: justify;\" data-start=\"615\" data-end=\"990\">T\u1ea1i sao g\u1ecdi l\u00e0 <strong data-start=\"8\" data-end=\"42\">NVIDIA RTX 5880 Ada 48GB GDDR6?<\/strong><\/h3>\n<p style=\"text-align: justify;\" data-start=\"0\" data-end=\"159\">T\u00ean g\u1ecdi NVIDIA RTX 5880 Ada 48GB GDDR6 \u0111\u01b0\u1ee3c \u0111\u1eb7t theo c\u1ea5u tr\u00fac quen thu\u1ed9c c\u1ee7a d\u00f2ng GPU workstation c\u1ee7a NVIDIA, v\u00e0 m\u1ed7i ph\u1ea7n trong t\u00ean \u0111\u1ec1u c\u00f3 \u00fd ngh\u0129a ri\u00eang:<\/p>\n<p style=\"text-align: justify;\" data-start=\"163\" data-end=\"202\"><strong data-start=\"163\" data-end=\"173\">&#8211; NVIDIA<\/strong>: Th\u01b0\u01a1ng hi\u1ec7u s\u1ea3n xu\u1ea5t GPU.<\/p>\n<p style=\"text-align: justify;\" data-start=\"205\" data-end=\"386\"><strong data-start=\"205\" data-end=\"212\">&#8211; RTX<\/strong>: Vi\u1ebft t\u1eaft c\u1ee7a <em data-start=\"227\" data-end=\"254\">Ray Tracing Texel eXtreme<\/em>, d\u00f2ng GPU h\u1ed7 tr\u1ee3 c\u00f4ng ngh\u1ec7 d\u00f2 tia (ray tracing) v\u00e0 AI Tensor Core, kh\u00e1c bi\u1ec7t so v\u1edbi d\u00f2ng GTX c\u0169 ch\u1ec9 thi\u00ean v\u1ec1 \u0111\u1ed3 h\u1ecda truy\u1ec1n th\u1ed1ng.<\/p>\n<p style=\"text-align: justify;\" data-start=\"389\" data-end=\"558\"><strong data-start=\"389\" data-end=\"397\">&#8211; 5880<\/strong>: M\u00e3 s\u1ea3n ph\u1ea9m trong series RTX Ada d\u00e0nh cho workstation. N\u00f3 n\u1eb1m gi\u1eefa RTX 5000 Ada v\u00e0 RTX 6000 Ada, th\u1ec3 hi\u1ec7n v\u1ecb tr\u00ed t\u1ea7m trung\u2013cao trong ph\u00e2n kh\u00fac chuy\u00ean nghi\u1ec7p.<\/p>\n<p style=\"text-align: justify;\" data-start=\"561\" data-end=\"694\"><strong data-start=\"561\" data-end=\"568\">&#8211; Ada<\/strong>: Th\u1ebf h\u1ec7 ki\u1ebfn tr\u00fac Ada Lovelace \u2013 th\u1ebf h\u1ec7 GPU m\u1edbi c\u1ee7a NVIDIA (sau Ampere), t\u1ed1i \u01b0u hi\u1ec7u n\u0103ng t\u00ednh to\u00e1n, AI v\u00e0 ray tracing.<\/p>\n<p style=\"text-align: justify;\" data-start=\"697\" data-end=\"836\"><strong data-start=\"697\" data-end=\"705\">&#8211; 48GB<\/strong>: Dung l\u01b0\u1ee3ng b\u1ed9 nh\u1edb \u0111\u1ed3 h\u1ecda (VRAM). Con s\u1ed1 n\u00e0y cho th\u1ea5y card c\u00f3 kh\u1ea3 n\u0103ng x\u1eed l\u00fd kh\u1ed1i l\u01b0\u1ee3ng d\u1eef li\u1ec7u, m\u00f4 h\u00ecnh AI hay c\u1ea3nh 3D r\u1ea5t l\u1edbn.<\/p>\n<p style=\"text-align: justify;\" data-start=\"839\" data-end=\"1049\"><strong data-start=\"839\" data-end=\"858\">&#8211; GDDR6 (v\u1edbi ECC)<\/strong>: Lo\u1ea1i b\u1ed9 nh\u1edb s\u1eed d\u1ee5ng. GDDR6 cho t\u1ed1c \u0111\u1ed9 cao, c\u00f2n ECC (Error-Correcting Code) gi\u00fap ph\u00e1t hi\u1ec7n v\u00e0 s\u1eeda l\u1ed7i b\u1ed9 nh\u1edb, \u0111\u1ea3m b\u1ea3o t\u00ednh \u1ed5n \u0111\u1ecbnh trong m\u00f4i tr\u01b0\u1eddng workstation v\u00e0 server chuy\u00ean nghi\u1ec7p.<\/p>\n<p data-start=\"839\" data-end=\"1049\"><strong>&gt;&gt;&gt; Xem th\u00eam: <a href=\"https:\/\/vnso.vn\/en\/nvidia-a100-vs-v100-so-sanh-chi-tiet-gpu-ai\/\">NVIDIA A100 vs. V100: So s\u00e1nh chi ti\u1ebft GPU AI<\/a><\/strong><\/p>\n<h2 style=\"text-align: justify;\" data-start=\"615\" data-end=\"990\">2. Th\u00f4ng s\u1ed1 k\u1ef9 thu\u1eadt NVIDIA RTX 5880 GPU<\/h2>\n<table style=\"height: 769px;\" width=\"600\">\n<thead>\n<tr>\n<th>Th\u00f4ng s\u1ed1<\/th>\n<th>Chi ti\u1ebft<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>B\u1ed9 nh\u1edb GPU<\/td>\n<td>48GB GDDR6<\/td>\n<\/tr>\n<tr>\n<td>Giao ti\u1ebfp b\u1ed9 nh\u1edb<\/td>\n<td>384-bit<\/td>\n<\/tr>\n<tr>\n<td>B\u0103ng th\u00f4ng b\u1ed9 nh\u1edb<\/td>\n<td>960 GB\/s<\/td>\n<\/tr>\n<tr>\n<td>ECC (s\u1eeda l\u1ed7i)<\/td>\n<td>C\u00f3<\/td>\n<\/tr>\n<tr>\n<td>Nh\u00e2n CUDA (ki\u1ebfn tr\u00fac Ada Lovelace)<\/td>\n<td>14.080<\/td>\n<\/tr>\n<tr>\n<td>Nh\u00e2n Tensor th\u1ebf h\u1ec7 4<\/td>\n<td>440<\/td>\n<\/tr>\n<tr>\n<td>Nh\u00e2n RT th\u1ebf h\u1ec7 3<\/td>\n<td>110<\/td>\n<\/tr>\n<tr>\n<td>Hi\u1ec7u n\u0103ng t\u00ednh to\u00e1n \u0111\u01a1n (FP32)<\/td>\n<td>69,3 TFLOPS<\/td>\n<\/tr>\n<tr>\n<td>Hi\u1ec7u n\u0103ng nh\u00e2n RT<\/td>\n<td>160,2 TFLOPS<\/td>\n<\/tr>\n<tr>\n<td>Hi\u1ec7u n\u0103ng nh\u00e2n Tensor<\/td>\n<td>1108,4 TFLOPS<\/td>\n<\/tr>\n<tr>\n<td>Giao ti\u1ebfp h\u1ec7 th\u1ed1ng<\/td>\n<td>PCIe 4.0 x16<\/td>\n<\/tr>\n<tr>\n<td>\u0110i\u1ec7n n\u0103ng ti\u00eau th\u1ee5<\/td>\n<td>285 W (T\u1ed5ng c\u00f4ng su\u1ea5t board)<\/td>\n<\/tr>\n<tr>\n<td>Gi\u1ea3i ph\u00e1p t\u1ea3n nhi\u1ec7t<\/td>\n<td>Ch\u1ee7 \u0111\u1ed9ng (Active)<\/td>\n<\/tr>\n<tr>\n<td>K\u00edch th\u01b0\u1edbc<\/td>\n<td>4.4\u201d H x 10.5\u201d L, dual-slot<\/td>\n<\/tr>\n<tr>\n<td>C\u1ed5ng xu\u1ea5t h\u00ecnh<\/td>\n<td>4x DisplayPort 1.4a<\/td>\n<\/tr>\n<tr>\n<td>S\u1ed1 m\u00e0n h\u00ecnh t\u1ed1i \u0111a<\/td>\n<td>4x 4096 \u00d7 2160 @ 120Hz 4x 5120 \u00d7 2880 @ 60Hz 2x 7680 \u00d7 4320 @ 60Hz<\/td>\n<\/tr>\n<tr>\n<td>B\u1ed9 m\u00e3 h\u00f3a\/gi\u1ea3i m\u00e3<\/td>\n<td>3x encode, 3x decode (+AV1 encode\/decode)<\/td>\n<\/tr>\n<tr>\n<td>H\u1ed7 tr\u1ee3 VR<\/td>\n<td>C\u00f3<\/td>\n<\/tr>\n<tr>\n<td>Ph\u1ea7n m\u1ec1m vGPU h\u1ed7 tr\u1ee3<\/td>\n<td>NVIDIA vPC\/vApps NVIDIA RTX Virtual Workstation<\/td>\n<\/tr>\n<tr>\n<td>H\u1ed3 s\u01a1 vGPU h\u1ed7 tr\u1ee3<\/td>\n<td>Theo Virtual GPU Licensing Guide<\/td>\n<\/tr>\n<tr>\n<td>API \u0111\u1ed3 h\u1ecda<\/td>\n<td>DirectX 12, Shader Model 6.6, OpenGL 4.67, Vulkan 1.3.7<\/td>\n<\/tr>\n<tr>\n<td>API t\u00ednh to\u00e1n<\/td>\n<td>CUDA 11.6, OpenCL 3.0, DirectCompute<\/td>\n<\/tr>\n<tr>\n<td>NVIDIA NVLink<\/td>\n<td>Kh\u00f4ng<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2 style=\"text-align: justify;\"><\/h2>\n<h2 style=\"text-align: justify;\">3. Review chi ti\u1ebft <strong data-start=\"146\" data-end=\"186\">NVIDIA RTX 5880 Ada 48GB GDDR6 ECC<\/strong><\/h2>\n<p style=\"text-align: justify;\" data-start=\"68\" data-end=\"266\">D\u01b0\u1edbi \u0111\u00e2y l\u00e0 ph\u00e2n t\u00edch k\u1ef9 thu\u1eadt, hi\u1ec7u n\u0103ng th\u1ef1c t\u1ebf v\u00e0 l\u1eddi khuy\u00ean tri\u1ec3n khai v\u1ec1 <strong data-start=\"146\" data-end=\"186\">NVIDIA RTX 5880 (Ada) 48GB GDDR6 ECC<\/strong> \u2014 t\u1eadp trung v\u00e0o d\u1eef li\u1ec7u, benchmark v\u00e0 b\u00e1o c\u00e1o.<\/p>\n<h3 style=\"text-align: justify;\" data-start=\"273\" data-end=\"312\">T\u00f3m l\u1ea1i th\u00f4ng s\u1ed1 k\u1ef9 thu\u1eadt quan tr\u1ecdng c\u1ea7n bi\u1ebft<\/h3>\n<p style=\"text-align: justify;\" data-start=\"315\" data-end=\"361\">&#8211; Ki\u1ebfn tr\u00fac: Ada Lovelace (AD102 variant).<\/p>\n<p style=\"text-align: justify;\" data-start=\"364\" data-end=\"489\">&#8211; CUDA Cores: 14,080; RT Cores (3rd-gen): 110; Tensor Cores (4th-gen): 440.<\/p>\n<p style=\"text-align: justify;\" data-start=\"492\" data-end=\"603\">&#8211; B\u1ed9 nh\u1edb: 48 GB GDDR6 ECC, bus 384-bit, b\u0103ng th\u00f4ng ~960 GB\/s.<\/p>\n<p style=\"text-align: justify;\" data-start=\"606\" data-end=\"765\">&#8211; Giao ti\u1ebfp: PCIe Gen4 x16; I\/O: 4 \u00d7 DisplayPort 1.4a. Form factor dual-slot (k\u00edch th\u01b0\u1edbc tham kh\u1ea3o 4.4\u201d \u00d7 10.5\u201d).<\/p>\n<p style=\"text-align: justify;\" data-start=\"768\" data-end=\"834\">&#8211; C\u00f4ng su\u1ea5t TBP: ~285 W.<\/p>\n<p style=\"text-align: justify;\" data-start=\"837\" data-end=\"1022\">T\u00ednh n\u0103ng th\u00eam: ECC memory, h\u1ed7 tr\u1ee3 vGPU (theo ch\u00ednh s\u00e1ch\/vGPU release c\u1ee7a NVIDIA); NVLink: Kh\u00f4ng h\u1ed7 tr\u1ee3 (kh\u00f4ng c\u00f3 bridge NVLink cho model n\u00e0y).<\/p>\n<p style=\"text-align: justify;\" data-start=\"837\" data-end=\"1022\"><a href=\"https:\/\/gpu.vnso.vn\/\"><img decoding=\"async\" class=\"aligncenter wp-image-23219 size-full\" src=\"https:\/\/vnso.vn\/wp-content\/uploads\/2025\/09\/workloads-suc-manh-cua-nvidia-rtx.jpg\" alt=\"workloads-suc-manh-cua-nvidia-rtx\" width=\"1200\" height=\"624\" srcset=\"https:\/\/vnso.vn\/wp-content\/uploads\/2025\/09\/workloads-suc-manh-cua-nvidia-rtx.jpg 1200w, https:\/\/vnso.vn\/wp-content\/uploads\/2025\/09\/workloads-suc-manh-cua-nvidia-rtx-800x416.jpg 800w, https:\/\/vnso.vn\/wp-content\/uploads\/2025\/09\/workloads-suc-manh-cua-nvidia-rtx-1024x532.jpg 1024w, https:\/\/vnso.vn\/wp-content\/uploads\/2025\/09\/workloads-suc-manh-cua-nvidia-rtx-768x399.jpg 768w, https:\/\/vnso.vn\/wp-content\/uploads\/2025\/09\/workloads-suc-manh-cua-nvidia-rtx-18x9.jpg 18w\" sizes=\"(max-width: 1200px) 100vw, 1200px\" \/><\/a><\/p>\n<h3 style=\"text-align: justify;\" data-start=\"1143\" data-end=\"1186\">Ki\u1ebfn tr\u00fac &amp; \u0111i\u1ec3m c\u00f4ng ngh\u1ec7 \u0111\u00e1ng ch\u00fa \u00fd<\/h3>\n<p style=\"text-align: justify;\" data-start=\"1189\" data-end=\"1493\"><em>&#8211; Ada Lovelace, Tensor 4th-gen &amp; FP8<\/em>: RTX 5880 th\u1eeba h\u01b0\u1edfng Tensor Cores th\u1ebf h\u1ec7 4 c\u1ee7a Ada, h\u1ed7 tr\u1ee3 t\u0103ng t\u1ed1c d\u1ea1ng s\u1ed1 li\u1ec7u FP8 (Transformer\/FP8 optimizations) cho inference\/transformer workloads, gi\u00fap t\u0103ng throughput tr\u00ean c\u00e1c t\u00e1c v\u1ee5 inference\/LLM so v\u1edbi th\u1ebf h\u1ec7 tr\u01b0\u1edbc.<\/p>\n<p style=\"text-align: justify;\" data-start=\"1496\" data-end=\"1650\"><em>&#8211; RT Cores 3-gen<\/em>: c\u1ea3i thi\u1ec7n d\u00f2 tia th\u1eddi gian th\u1ef1c (ray tracing) v\u00e0 ph\u1ed1i h\u1ee3p t\u1ed1t v\u1edbi shader\/concurrent workloads.<\/p>\n<p style=\"text-align: justify;\" data-start=\"1653\" data-end=\"1878\"><em>&#8211; B\u1ed9 nh\u1edb l\u1edbn 48 GB + ECC:<\/em> \u0111\u00e2y l\u00e0 y\u1ebfu t\u1ed1 ph\u00e2n bi\u1ec7t ch\u00ednh \u2014 dung l\u01b0\u1ee3ng l\u1edbn, ECC gi\u00fap \u1ed5n \u0111\u1ecbnh cho workflow chuy\u00ean nghi\u1ec7p (render ph\u00e2n c\u1ea3nh l\u1edbn, d\u1eef li\u1ec7u khoa h\u1ecdc, m\u00f4 h\u00ecnh ML c\u1ea7n batch l\u1edbn).<\/p>\n<h3 style=\"text-align: justify;\" data-start=\"1885\" data-end=\"1944\">Hi\u1ec7u n\u0103ng th\u1ef1c t\u1ebf<\/h3>\n<p style=\"text-align: justify;\"><em>So s\u00e1nh d\u00f2ng n\u1ed9i b\u1ed9:<\/em> RTX 5880 n\u1eb1m gi\u1eefa RTX 5000 Ada v\u00e0 RTX 6000 Ada v\u1ec1 t\u1ed5ng th\u1ec3 \u2014 GPU gi\u1eef nguy\u00ean subsystem b\u1ed9 nh\u1edb (48GB\/384-bit\/960GB\/s) nh\u01b0ng s\u1ed1 nh\u00e2n (CUDA\/Tensor\/RT) b\u1ecb c\u1eaft xu\u1ed1ng so v\u1edbi 6000 Ada, n\u00ean hi\u1ec7u n\u0103ng t\u00ednh to\u00e1n th\u00f4 k\u00e9m h\u01a1n 6000 Ada nh\u01b0ng th\u01b0\u1eddng v\u01b0\u1ee3t RTX 5000 Ada.<\/p>\n<p style=\"text-align: justify;\" data-start=\"2268\" data-end=\"2691\"><em>Benchmarks vendor \/ nh\u00e0 ph\u00e2n ph\u1ed1i:<\/em> c\u00e1c b\u00e0i test do nh\u00e0 ph\u00e2n ph\u1ed1i\/\u0111\u1ed1i t\u00e1c c\u00f4ng b\u1ed1 cho th\u1ea5y RTX 5880 nhanh h\u01a1n RTX 5000 Ada \u1edf nhi\u1ec1u b\u00e0i to\u00e1n render (V-Ray, Octane, Blender Cycles) \u2014 v\u00ed d\u1ee5 c\u00e1c b\u00e1o c\u00e1o vendor tr\u00edch d\u1eabn m\u1ee9c c\u1ea3i thi\u1ec7n t\u1eeb ~20% \u0111\u1ebfn ~48% t\u00f9y engine\/mode (CUDA vs RTX\/OptiX). L\u01b0u \u00fd: \u0111\u00e2y l\u00e0 k\u1ebft qu\u1ea3 do nh\u00e0 ph\u00e2n ph\u1ed1i\/nh\u00e0 s\u1ea3n xu\u1ea5t cung c\u1ea5p, \u0111i\u1ec1u ki\u1ec7n test c\u00f3 th\u1ec3 kh\u00e1c nhau.<\/p>\n<p style=\"text-align: justify;\" data-start=\"2694\" data-end=\"3061\"><em>Benchmark c\u1ed9ng \u0111\u1ed3ng \u2014 Blender Open Data<\/em>: c\u00f3 k\u1ebft qu\u1ea3 Blender benchmark cho RTX 5880. Nh\u1eefng b\u1ea3n test c\u1ed9ng \u0111\u1ed3ng cho th\u1ea5y \u0111i\u1ec3m benchmark thu\u1ed9c nh\u00f3m cao trong danh s\u00e1ch thi\u1ebft k\u1ebf\/visualization, c\u1ea1nh tranh v\u1edbi c\u00e1c GPU GeForce cao c\u1ea5p trong n\u1ed9i dung render OptiX.<\/p>\n<p style=\"text-align: justify;\" data-start=\"3063\" data-end=\"3386\">RTX 5880 r\u1ea5t m\u1ea1nh cho GPU rendering (Octane, V-Ray, Blender\/OptiX) v\u00e0 workloads ray-tracing nh\u1edd s\u1ed1 l\u01b0\u1ee3ng RT cores v\u00e0 b\u1ed9 nh\u1edb l\u1edbn; v\u1edbi AI, n\u00f3 cung c\u1ea5p throughput inference t\u1ed1t nh\u1edd Tensor Gen-4 + FP8, v\u00e0 c\u00f3 l\u1ee3i th\u1ebf khi b\u1ea1n c\u1ea7n loads\/ batch l\u1edbn v\u00ec 48GB VRAM.<\/p>\n<h3 style=\"text-align: justify;\" data-start=\"3393\" data-end=\"3439\">\u1ee8ng d\u1ee5ng ph\u00f9 h\u1ee3p \/ khi n\u00ean ch\u1ecdn RTX 5880<\/h3>\n<p style=\"text-align: justify;\" data-start=\"3442\" data-end=\"3698\"><strong data-start=\"3442\" data-end=\"3460\">\u0110\u00fang m\u1ee5c ti\u00eau:<\/strong> workstation chuy\u00ean nghi\u1ec7p (VFX, 3D rendering, CAD\/CAE, visualisation), d\u1ef1ng film\/scene l\u1edbn, x\u1eed l\u00fd dataset l\u1edbn cho inference\/ho\u1eb7c fine-tuning nh\u1ecf-v\u1eeba, m\u00f4i tr\u01b0\u1eddng vGPU cho nhi\u1ec1u user (h\u1ed7 tr\u1ee3 vGPU).<\/p>\n<p style=\"text-align: justify;\" data-start=\"3701\" data-end=\"4098\"><strong>Kh\u00f4ng ph\u1ea3i t\u1ed1i \u01b0u cho<\/strong>: b\u00e0i to\u00e1n training quy m\u00f4 r\u1ea5t l\u1edbn, multi-GPU ph\u00e2n t\u00e1n \u1edf c\u1ea5p data-center (\u1edf \u0111\u00f3 HBM + NVLink + NVSwitch tr\u00ean H100\/Hopper ho\u1eb7c c\u00e1c card datacenter s\u1ebd c\u00f3 l\u1ee3i v\u1ec1 b\u0103ng th\u00f4ng b\u1ed9 nh\u1edb v\u00e0 kh\u1ea3 n\u0103ng k\u1ebft n\u1ed1i \u0111a-GPU). RTX 5880 kh\u00f4ng c\u00f3 NVLink, n\u00ean kh\u1ea3 n\u0103ng pooling memory\/performance multi-GPU b\u1ecb h\u1ea1n ch\u1ebf so v\u1edbi GPU datacenter c\u00f3 NVLink.<\/p>\n<p data-start=\"3701\" data-end=\"4098\"><strong>&gt;&gt;&gt; C\u00f3 th\u1ec3 b\u1ea1n quan t\u00e2m <a href=\"https:\/\/vnso.vn\/en\/nvidia-hgx-h100-be-phong-suc-manh-ai-va-hpc\/\">NVIDIA HGX H100 \u2013 B\u1ec7 ph\u00f3ng s\u1ee9c m\u1ea1nh AI v\u00e0 HPC<\/a><\/strong><\/p>\n<h3 style=\"text-align: justify;\" data-start=\"4105\" data-end=\"4135\">\u01afu &amp; nh\u01b0\u1ee3c \u0111i\u1ec3m c\u1ee5 th\u1ec3<\/h3>\n<p style=\"text-align: justify;\" data-start=\"4136\" data-end=\"4147\"><strong data-start=\"4136\" data-end=\"4147\">\u01afu \u0111i\u1ec3m<\/strong><\/p>\n<p style=\"text-align: justify;\" data-start=\"4150\" data-end=\"4280\">&#8211; VRAM l\u1edbn<em> 48 GB GDDR6 ECC<\/em>: x\u1eed l\u00fd scene\/m\u00f4 h\u00ecnh ML l\u1edbn m\u00e0 kh\u00f4ng ph\u1ea3i chia nh\u1ecf d\u1eef li\u1ec7u.<\/p>\n<p style=\"text-align: justify;\" data-start=\"4283\" data-end=\"4402\">&#8211; Ada features (Tensor4 + FP8, RT3): t\u0103ng hi\u1ec7u qu\u1ea3 cho inference &amp; ray tracing.<\/p>\n<p style=\"text-align: justify;\" data-start=\"4405\" data-end=\"4532\">&#8211; B\u0103ng th\u00f4ng b\u1ed9 nh\u1edb cao (960 GB\/s) d\u00f9 d\u00f9ng GDDR6 \u2014 l\u1ee3i cho workloads c\u1ea7n throughput VRAM.<\/p>\n<p style=\"text-align: justify;\" data-start=\"4534\" data-end=\"4559\"><strong data-start=\"4534\" data-end=\"4559\">Nh\u01b0\u1ee3c \u0111i\u1ec3m<\/strong><\/p>\n<p style=\"text-align: justify;\" data-start=\"4562\" data-end=\"4677\"><strong data-start=\"4562\" data-end=\"4581\">&#8211; <\/strong>Kh\u00f4ng c\u00f3 NVLink d\u1eabn \u0111\u1ebfn k\u00e9m linh ho\u1ea1t khi c\u1ea7n pooling memory cho multi-GPU.<\/p>\n<p style=\"text-align: justify;\" data-start=\"4680\" data-end=\"4881\">&#8211; Hi\u1ec7u n\u0103ng thu\u1ea7n s\u1ed1 li\u1ec7u\/FP32 c\u00f3 th\u1ec3 th\u1ea5p h\u01a1n RTX 6000 Ada (v\u00ec s\u1ed1 nh\u00e2n \u00edt h\u01a1n) \u2014 t\u1ee9c n\u1ebfu b\u1ea1n c\u1ea7n \u201cmax compute\u201d th\u00ec d\u00f2ng 6000 (ho\u1eb7c GPU datacenter) v\u1eabn m\u1ea1nh h\u01a1n.<\/p>\n<p style=\"text-align: justify;\" data-start=\"4884\" data-end=\"4979\">&#8211; C\u00f4ng su\u1ea5t ~285W \u2014 c\u1ea7n h\u1ec7 th\u1ed1ng ngu\u1ed3n\/l\u00e0m m\u00e1t t\u01b0\u01a1ng \u1ee9ng.<\/p>\n<h3 style=\"text-align: justify;\" data-start=\"4986\" data-end=\"5018\">Gi\u00e1 &amp; s\u1eb5n h\u00e0ng<\/h3>\n<p style=\"text-align: justify;\" data-start=\"5021\" data-end=\"5380\">NVIDIA\/nh\u00e0 s\u1ea3n xu\u1ea5t th\u01b0\u1eddng kh\u00f4ng c\u00f4ng b\u1ed1 MSRP cho m\u1ed9t s\u1ed1 d\u00f2ng workstation; nhi\u1ec1u reseller\/boutique li\u1ec7t k\u00ea RTX 5880 v\u1edbi gi\u00e1 th\u01b0\u01a1ng m\u1ea1i kh\u00e1c nhau (v\u00ed d\u1ee5 m\u1ed9t s\u1ed1 trang reseller ni\u00eam y\u1ebft \u1edf v\u00e0i ngh\u00ecn USD \u2014 tham kh\u1ea3o danh s\u00e1ch nh\u00e0 ph\u00e2n ph\u1ed1i). Gi\u00e1 th\u1ef1c t\u1ebf t\u00f9y th\u1ecb tr\u01b0\u1eddng, VAT, b\u1ea3o h\u00e0nh, v\u00e0 c\u00e1c g\u00f3i ph\u1ea7n m\u1ec1m (vGPU license).<\/p>\n<h3 style=\"text-align: justify;\" data-start=\"5387\" data-end=\"5421\">L\u1eddi khuy\u00ean tr\u01b0\u1edbc khi mua ho\u1eb7c thu\u00ea <strong data-start=\"146\" data-end=\"186\">NVIDIA RTX 5880 Ada 48GB GDDR6 ECC<\/strong><\/h3>\n<p style=\"text-align: justify;\" data-start=\"5424\" data-end=\"5707\">Ch\u1ecdn RTX 5880 n\u1ebfu b\u1ea1n l\u00e0 studio\/engineer\/designer c\u1ea7n 48GB VRAM \u0111\u1ec3 render c\u1ea3nh l\u1edbn, ch\u1ea1y inference hay fine-tune m\u00f4 h\u00ecnh v\u1eeba, ho\u1eb7c mu\u1ed1n m\u1ed9t GPU workstation m\u1ea1nh cho workflows \u0111\u1ed3 h\u1ecda\/visualization v\u1edbi t\u00ednh \u1ed5n \u0111\u1ecbnh (ECC, vGPU support).<\/p>\n<p style=\"text-align: justify;\" data-start=\"5424\" data-end=\"5707\">Kh\u00f4ng ch\u1ecdn n\u1ebfu b\u1ea1n c\u1ea7n t\u1ed1i \u0111a hi\u1ec7u n\u0103ng training ph\u00e2n t\u00e1n (multi-GPU NVLink + HBM) \u2014 \u1edf \u0111\u00f3 GPU datacenter (H100\/6000 Ada v\u1edbi NVLink\/HBM ho\u1eb7c s\u1ea3n ph\u1ea9m t\u01b0\u01a1ng t\u1ef1) s\u1ebd ph\u00f9 h\u1ee3p h\u01a1n.<\/p>\n<p style=\"text-align: justify;\" data-start=\"5933\" data-end=\"6136\">N\u1ebfu m\u1ee5c ti\u00eau l\u00e0 kh\u1edfi \u0111\u1ed9ng nhanh &amp; ti\u1ebft ki\u1ec7m v\u1ed1n, c\u00e2n nh\u1eafc thu\u00ea (rent) GPU n\u00e0y tr\u00ean cloud ho\u1eb7c thu\u00ea server ch\u1ee9a RTX 5880 tr\u01b0\u1edbc khi mua \u2014 \u0111\u1eb7c bi\u1ec7t khi workload ch\u1ec9 c\u1ea7n VRAM l\u1edbn theo th\u1eddi gian ng\u1eafn.<\/p>\n<h2 style=\"text-align: justify;\" data-start=\"5933\" data-end=\"6136\">4. \u1ee8ng d\u1ee5ng th\u1ef1c t\u1ebf c\u1ee7a <strong data-start=\"146\" data-end=\"186\">NVIDIA RTX 5880 Ada<\/strong><\/h2>\n<p style=\"text-align: justify;\" data-start=\"0\" data-end=\"239\">NVIDIA RTX 5880 Ada 48GB GDDR6 ECC mang \u0111\u1ebfn s\u1ee9c m\u1ea1nh \u0111\u1ed3 h\u1ecda chuy\u00ean nghi\u1ec7p cho d\u1ef1ng h\u00ecnh 3D, render phim, thi\u1ebft k\u1ebf ki\u1ebfn tr\u00fac v\u00e0 k\u1ef9 thu\u1eadt. V\u1edbi ki\u1ebfn tr\u00fac Ada Lovelace, card \u0111\u00e1p \u1ee9ng t\u1ed1t c\u00e1c t\u00e1c v\u1ee5 ph\u1ee9c t\u1ea1p c\u1ea7n t\u1ed1c \u0111\u1ed9 v\u00e0 \u0111\u1ed9 ch\u00ednh x\u00e1c cao.<\/p>\n<p style=\"text-align: justify;\" data-start=\"241\" data-end=\"462\">Trong l\u0129nh v\u1ef1c AI v\u00e0 d\u1eef li\u1ec7u l\u1edbn, RTX 5880 h\u1ed7 tr\u1ee3 hu\u1ea5n luy\u1ec7n m\u00f4 h\u00ecnh, x\u1eed l\u00fd dataset kh\u1ed5ng l\u1ed3 nh\u1edd 48GB b\u1ed9 nh\u1edb ECC v\u00e0 Tensor Core th\u1ebf h\u1ec7 4. \u0110\u00e2y l\u00e0 l\u1ef1a ch\u1ecdn \u0111\u00e1ng tin c\u1eady cho nghi\u00ean c\u1ee9u, ph\u00e2n t\u00edch v\u00e0 \u1ee9ng d\u1ee5ng Generative AI.<\/p>\n<p style=\"text-align: justify;\" data-start=\"464\" data-end=\"712\">Ngo\u00e0i ra, GPU c\u00f2n h\u1ed7 tr\u1ee3 AV1 encode\/decode, \u0111a m\u00e0n h\u00ecnh v\u00e0 \u1ea3o h\u00f3a GPU, ph\u00f9 h\u1ee3p cho media, livestream, l\u00e0m vi\u1ec7c nh\u00f3m t\u1eeb xa v\u00e0 m\u00f4i tr\u01b0\u1eddng doanh nghi\u1ec7p. \u0110\u00e2y l\u00e0 gi\u1ea3i ph\u00e1p c\u00e2n b\u1eb1ng gi\u1eefa hi\u1ec7u n\u0103ng, b\u1ed9 nh\u1edb v\u00e0 \u0111\u1ed9 \u1ed5n \u0111\u1ecbnh cho nhi\u1ec1u l\u0129nh v\u1ef1c chuy\u00ean nghi\u1ec7p.<\/p>\n<p style=\"text-align: justify;\" data-start=\"464\" data-end=\"712\"><a href=\"https:\/\/gpu.vnso.vn\/\"><img decoding=\"async\" class=\"aligncenter size-full wp-image-23218\" src=\"https:\/\/vnso.vn\/wp-content\/uploads\/2025\/09\/Nha-cung-cap-Server-GPU-NVIDIA-RTX-5880-uy-tin-vnso.jpg\" alt=\"Nh\u00e0-cung-c\u1ea5p-Server-GPU-NVIDIA-RTX-5880-uy-tin-vnso\" width=\"1200\" height=\"624\" srcset=\"https:\/\/vnso.vn\/wp-content\/uploads\/2025\/09\/Nha-cung-cap-Server-GPU-NVIDIA-RTX-5880-uy-tin-vnso.jpg 1200w, https:\/\/vnso.vn\/wp-content\/uploads\/2025\/09\/Nha-cung-cap-Server-GPU-NVIDIA-RTX-5880-uy-tin-vnso-800x416.jpg 800w, https:\/\/vnso.vn\/wp-content\/uploads\/2025\/09\/Nha-cung-cap-Server-GPU-NVIDIA-RTX-5880-uy-tin-vnso-1024x532.jpg 1024w, https:\/\/vnso.vn\/wp-content\/uploads\/2025\/09\/Nha-cung-cap-Server-GPU-NVIDIA-RTX-5880-uy-tin-vnso-768x399.jpg 768w, https:\/\/vnso.vn\/wp-content\/uploads\/2025\/09\/Nha-cung-cap-Server-GPU-NVIDIA-RTX-5880-uy-tin-vnso-18x9.jpg 18w\" sizes=\"(max-width: 1200px) 100vw, 1200px\" \/><\/a><\/p>\n<div class=\"text-base my-auto mx-auto pb-10 [--thread-content-margin:--spacing(4)] thread-sm:[--thread-content-margin:--spacing(6)] thread-lg:[--thread-content-margin:--spacing(16)] px-(--thread-content-margin)\" style=\"text-align: justify;\">\n<div class=\"[--thread-content-max-width:40rem] thread-sm:[--thread-content-max-width:40rem] thread-lg:[--thread-content-max-width:48rem] mx-auto max-w-(--thread-content-max-width) flex-1 group\/turn-messages focus-visible:outline-hidden relative flex w-full min-w-0 flex-col agent-turn\" tabindex=\"-1\">\n<div class=\"flex max-w-full flex-col grow\">\n<div class=\"min-h-8 text-message relative flex w-full flex-col items-end gap-2 text-start break-words whitespace-normal [.text-message+&amp;]:mt-5\" dir=\"auto\" data-message-author-role=\"assistant\" data-message-id=\"ee006de7-e4fa-40e4-9dde-25dd4b167735\" data-message-model-slug=\"gpt-5\">\n<div class=\"flex w-full flex-col gap-1 empty:hidden first:pt-[3px]\">\n<h2 style=\"text-align: justify;\"><span data-start=\"499\" data-end=\"555\">5. Nh\u00e0 cung c\u1ea5p <strong>Server GPU NVIDIA RTX 5880 uy t\u00edn<\/strong><\/span><\/h2>\n<p><strong>Thu\u00ea Server GPU NVIDIA RTX 5880 Ada 48GB GDDR6 v\u1edbi ECC ch\u1ec9 t\u1eeb 28.900.000 \u0111\/th\u00e1ng t\u1ea1i VNSO<\/strong><\/p>\n<p style=\"text-align: justify;\">Gi\u00e1 thu\u00ea: <span style=\"color: #333399;\"><em><strong>28<\/strong><\/em><em><strong data-start=\"499\" data-end=\"555\">.900.000 \u0111\/th\u00e1ng<\/strong><\/em><\/span><br \/>\nCPU: 2 x Intel Xeon Gold Series<br \/>\nRAM: 64 GB<br \/>\nDisk: 240GB SSD NVMe<br \/>\nGPU: 01 x Nvidia RTX 5880<br \/>\nNetwork: 200Mbps<\/p>\n<p><em>T\u1ea5t c\u1ea3 c\u00e1c th\u00f4ng s\u1ed1 k\u1ef9 thu\u1eadt, c\u1ea5u h\u00ecnh tr\u00ean \u0111\u1ec1u c\u00f3 th\u1ec3 thay \u0111\u1ed5i theo \u0111\u00fang nhu c\u1ea7u c\u1ee7a b\u1ea1n.<\/em><\/p>\n<p><b>VNSO kh\u00e1c g\u00ec so v\u1edbi c\u00e1c nh\u00e0 cung c\u1ea5p kh\u00e1c?<\/b><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">Khi s\u1eed d\u1ee5ng d\u1ecbch v\u1ee5 VNSO, ch\u00fang t\u00f4i mang l\u1ea1i c\u00e1c y\u1ebfu t\u1ed1 quan tr\u1ecdng sau m\u00e0 c\u00e1c nh\u00e0 cung c\u1ea5p kh\u00e1c kh\u00f4ng th\u1ec3 \u0111\u00e1p \u1ee9ng 100%.<\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">&#8211; H\u00e0ng c\u00f3 s\u1eb5n, ch\u00ednh s\u00e1ch nh\u1eadp h\u00e0ng ch\u00ednh h\u00e3ng r\u00f5 r\u00e0ng, ch\u1ea5t l\u01b0\u1ee3ng, \u0111\u1ea7y \u0111\u1ee7 CO\/CQ<\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">&#8211; Ch\u00ednh s\u00e1ch b\u00e1n h\u00e0ng linh \u0111\u1ed9ng, gi\u00e1 thu\u00ea ho\u1eb7c mua c\u1ea1nh tranh nh\u1ea5t hi\u1ec7n nay<\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">&#8211; Linh ho\u1ea1t tri\u1ec3n khai trong ch\u1ec9 v\u00f2ng <\/span><i><span style=\"font-weight: 400;\">30<\/span><\/i><span style=\"font-weight: 400;\"> ph\u00fat<\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">&#8211; H\u1ec7 th\u1ed1ng \u1ed5n \u0111\u1ecbnh, b\u1ea3o m\u1eadt cao<\/span><\/p>\n<p style=\"text-align: justify;\"><span style=\"font-weight: 400;\">&#8211; <\/span>H\u1ed7 tr\u1ee3 k\u1ef9 thu\u1eadt 24\/7, t\u01b0 v\u1ea5n gi\u1ea3i ph\u00e1p AI ph\u00f9 h\u1ee3p<\/p>\n<p><strong>&#8211; <\/strong>B\u1ea1n c\u00f3 th\u1ec3 thu\u00ea ho\u1eb7c mua tr\u1ecdn t\u1ea1i VNSO!<\/p>\n<p>&nbsp;<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<p style=\"text-align: justify;\" data-start=\"182\" data-end=\"604\">&gt;&gt;&gt; \u0110\u0103ng k\u00fd ngay <a href=\"https:\/\/gpu.vnso.vn\/\"><strong>Server AI\/GPU, Cloud GPU VNSO<\/strong><\/a> \u2013 <em>t\u01b0 v\u1ea5n,<\/em><em> b\u00e1o gi\u00e1 &amp; d\u00f9ng th\u1eed mi\u1ec5n ph\u00ed<\/em>!<\/p>\n<p style=\"text-align: justify;\" data-start=\"5253\" data-end=\"5426\">\n<div class=\"wpcf7 no-js\" id=\"wpcf7-f15879-o2\" 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\/23216#wpcf7-f15879-o2\" 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\/23216#wpcf7-f15879-o2\">\n<div style=\"display: none;\">\n<input type=\"hidden\" name=\"_wpcf7\" value=\"15879\" \/>\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-f15879-o2\" \/>\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\" 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=\"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 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Thu\u00ea Server GPU [&hellip;]<\/p>","protected":false},"author":6,"featured_media":23217,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[538],"tags":[511,583,507],"yoast_head":"<!-- This site is optimized with the Yoast SEO Premium plugin v20.3 (Yoast SEO v22.8) - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Thu\u00ea NVIDIA RTX 5880 Ada 48GB GDDR6 v\u1edbi ECC<\/title>\n<meta name=\"description\" content=\"Thu\u00ea NVIDIA RTX 5880 Ada 48GB GDDR6 ECC ch\u1ec9 t\u1eeb 28.900.000\u0111\/th\u00e1ng t\u1ea1i VNSO. 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