{"id":15715,"date":"2026-03-03T17:52:10","date_gmt":"2026-03-03T10:52:10","guid":{"rendered":"https:\/\/droneth.or.th\/?post_type=product&#038;p=15715"},"modified":"2026-06-16T14:46:50","modified_gmt":"2026-06-16T07:46:50","slug":"nvidia-dgx-spark","status":"publish","type":"product","link":"https:\/\/droneth.or.th\/ja\/product\/nvidia-dgx-spark\/","title":{"rendered":"NVIDIA DGX Spark"},"content":{"rendered":"<p data-path-to-node=\"10\"><b data-path-to-node=\"10\" data-index-in-node=\"0\">\u0e0b\u0e39\u0e40\u0e1b\u0e2d\u0e23\u0e4c\u0e04\u0e2d\u0e21\u0e1e\u0e34\u0e27\u0e40\u0e15\u0e2d\u0e23\u0e4c AI \u0e2a\u0e48\u0e27\u0e19\u0e1a\u0e38\u0e04\u0e04\u0e25 \u0e08\u0e38\u0e14\u0e40\u0e23\u0e34\u0e48\u0e21\u0e15\u0e49\u0e19\u0e02\u0e2d\u0e07\u0e19\u0e27\u0e31\u0e15\u0e01\u0e23\u0e23\u0e21\u0e41\u0e2b\u0e48\u0e07\u0e2d\u0e19\u0e32\u0e04\u0e15<\/b> NVIDIA DGX Spark \u0e04\u0e37\u0e2d\u0e19\u0e34\u0e22\u0e32\u0e21\u0e43\u0e2b\u0e21\u0e48\u0e02\u0e2d\u0e07\u0e40\u0e04\u0e23\u0e37\u0e48\u0e2d\u0e07\u0e21\u0e37\u0e2d\u0e2a\u0e33\u0e2b\u0e23\u0e31\u0e1a\u0e19\u0e31\u0e01\u0e1e\u0e31\u0e12\u0e19\u0e32 AI \u0e15\u0e31\u0e27\u0e08\u0e23\u0e34\u0e07 \u0e14\u0e49\u0e27\u0e22\u0e01\u0e32\u0e23\u0e1a\u0e23\u0e23\u0e08\u0e38\u0e2a\u0e16\u0e32\u0e1b\u0e31\u0e15\u0e22\u0e01\u0e23\u0e23\u0e21\u0e23\u0e30\u0e14\u0e31\u0e1a\u0e42\u0e25\u0e01\u0e43\u0e2b\u0e49\u0e2d\u0e22\u0e39\u0e48\u0e43\u0e19\u0e40\u0e04\u0e2a\u0e42\u0e25\u0e2b\u0e30\u0e02\u0e19\u0e32\u0e14\u0e01\u0e30\u0e17\u0e31\u0e14\u0e23\u0e31\u0e14\u0e40\u0e1e\u0e35\u0e22\u0e07 1.8 \u0e25\u0e34\u0e15\u0e23 \u0e1c\u0e2a\u0e32\u0e19\u0e1e\u0e25\u0e31\u0e07\u0e0b\u0e35\u0e1e\u0e35\u0e22\u0e39 Arm 20 \u0e04\u0e2d\u0e23\u0e4c \u0e41\u0e25\u0e30\u0e08\u0e35\u0e1e\u0e35\u0e22\u0e39 Blackwell \u0e17\u0e35\u0e48\u0e21\u0e35 CUDA Cores \u0e16\u0e36\u0e07 6,144 \u0e04\u0e2d\u0e23\u0e4c \u0e17\u0e33\u0e07\u0e32\u0e19\u0e1a\u0e19\u0e2b\u0e19\u0e48\u0e27\u0e22\u0e04\u0e27\u0e32\u0e21\u0e08\u0e33 Unified Memory 128GB \u0e41\u0e1a\u0e19\u0e14\u0e4c\u0e27\u0e34\u0e14\u0e18\u0e4c 273 GB\/s \u0e17\u0e33\u0e43\u0e2b\u0e49\u0e40\u0e04\u0e23\u0e37\u0e48\u0e2d\u0e07\u0e19\u0e35\u0e49\u0e40\u0e1b\u0e47\u0e19\u0e2a\u0e38\u0e14\u0e22\u0e2d\u0e14 Sandbox \u0e2a\u0e33\u0e2b\u0e23\u0e31\u0e1a\u0e01\u0e32\u0e23\u0e27\u0e34\u0e08\u0e31\u0e22\u0e02\u0e31\u0e49\u0e19\u0e2a\u0e39\u0e07 \u0e44\u0e21\u0e48\u0e27\u0e48\u0e32\u0e08\u0e30\u0e40\u0e1b\u0e47\u0e19\u0e01\u0e32\u0e23\u0e23\u0e31\u0e19\u0e42\u0e21\u0e40\u0e14\u0e25\u0e20\u0e32\u0e29\u0e32\u0e02\u0e19\u0e32\u0e14\u0e43\u0e2b\u0e0d\u0e48, \u0e01\u0e32\u0e23\u0e1b\u0e23\u0e30\u0e21\u0e27\u0e25\u0e1c\u0e25 Computer Vision, \u0e2b\u0e23\u0e37\u0e2d\u0e41\u0e21\u0e49\u0e41\u0e15\u0e48\u0e01\u0e32\u0e23\u0e1e\u0e31\u0e12\u0e19\u0e32 AI \u0e2a\u0e33\u0e2b\u0e23\u0e31\u0e1a\u0e2b\u0e38\u0e48\u0e19\u0e22\u0e19\u0e15\u0e4c Humanoid \u0e0a\u0e31\u0e49\u0e19\u0e2a\u0e39\u0e07\u0e2d\u0e22\u0e48\u0e32\u0e07\u0e42\u0e21\u0e40\u0e14\u0e25 GR00T N1 \u0e41\u0e25\u0e30\u0e01\u0e32\u0e23\u0e0b\u0e34\u0e21\u0e39\u0e40\u0e25\u0e0a\u0e31\u0e19\u0e1c\u0e48\u0e32\u0e19\u0e41\u0e1e\u0e25\u0e15\u0e1f\u0e2d\u0e23\u0e4c\u0e21\u0e02\u0e2d\u0e07 NVIDIA \u0e01\u0e47\u0e17\u0e33\u0e44\u0e14\u0e49\u0e2d\u0e22\u0e48\u0e32\u0e07\u0e25\u0e37\u0e48\u0e19\u0e44\u0e2b\u0e25<\/p>\n<p data-path-to-node=\"11\">\u0e15\u0e31\u0e27\u0e40\u0e04\u0e23\u0e37\u0e48\u0e2d\u0e07\u0e21\u0e32\u0e1e\u0e23\u0e49\u0e2d\u0e21\u0e23\u0e30\u0e1a\u0e1a\u0e1b\u0e0f\u0e34\u0e1a\u0e31\u0e15\u0e34\u0e01\u0e32\u0e23 NVIDIA DGX OS \u0e41\u0e25\u0e30\u0e0a\u0e38\u0e14\u0e0b\u0e2d\u0e1f\u0e15\u0e4c\u0e41\u0e27\u0e23\u0e4c AI \u0e41\u0e1a\u0e1a\u0e04\u0e23\u0e1a\u0e27\u0e07\u0e08\u0e23 (CUDA, TensorRT, Triton) \u0e1e\u0e23\u0e49\u0e2d\u0e21\u0e22\u0e01\u0e23\u0e30\u0e14\u0e31\u0e1a\u0e02\u0e35\u0e14\u0e08\u0e33\u0e01\u0e31\u0e14\u0e14\u0e49\u0e27\u0e22\u0e1e\u0e2d\u0e23\u0e4c\u0e15 QSFP 200Gbps \u0e16\u0e36\u0e07 2 \u0e0a\u0e48\u0e2d\u0e07 \u0e43\u0e2b\u0e49\u0e04\u0e38\u0e13\u0e40\u0e0a\u0e37\u0e48\u0e2d\u0e21\u0e15\u0e48\u0e2d DGX Spark \u0e2a\u0e2d\u0e07\u0e40\u0e04\u0e23\u0e37\u0e48\u0e2d\u0e07\u0e40\u0e02\u0e49\u0e32\u0e14\u0e49\u0e27\u0e22\u0e01\u0e31\u0e19\u0e40\u0e1b\u0e47\u0e19 Mini-cluster \u0e40\u0e1e\u0e37\u0e48\u0e2d\u0e23\u0e31\u0e1a\u0e21\u0e37\u0e2d\u0e01\u0e31\u0e1a\u0e42\u0e1b\u0e23\u0e40\u0e08\u0e01\u0e15\u0e4c\u0e23\u0e30\u0e14\u0e31\u0e1a\u0e0a\u0e32\u0e15\u0e34\u0e44\u0e14\u0e49\u0e2d\u0e22\u0e48\u0e32\u0e07\u0e2a\u0e21\u0e1a\u0e39\u0e23\u0e13\u0e4c\u0e41\u0e1a\u0e1a<\/p>\n<p data-path-to-node=\"12\"><b data-path-to-node=\"12\" data-index-in-node=\"0\">\u0e02\u0e49\u0e2d\u0e21\u0e39\u0e25\u0e17\u0e32\u0e07\u0e40\u0e17\u0e04\u0e19\u0e34\u0e04 (Product Specifications)<\/b><\/p>\n<p>&nbsp;<\/p>\n<table data-path-to-node=\"13\">\n<thead>\n<tr>\n<td><strong>\u30bb\u30af\u30b7\u30e7\u30f3<\/strong><\/td>\n<td><strong>\u0e23\u0e32\u0e22\u0e25\u0e30\u0e40\u0e2d\u0e35\u0e22\u0e14\u0e2a\u0e40\u0e1b\u0e04<\/strong><\/td>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td><span data-path-to-node=\"13,1,0,0\"><b data-path-to-node=\"13,1,0,0\" data-index-in-node=\"0\">\u0e2b\u0e19\u0e48\u0e27\u0e22\u0e1b\u0e23\u0e30\u0e21\u0e27\u0e25\u0e1c\u0e25 (CPU \/ GPU)<\/b><\/span><\/td>\n<td>\n<p data-path-to-node=\"13,1,1,0\">\u2022 \u0e41\u0e1e\u0e25\u0e15\u0e1f\u0e2d\u0e23\u0e4c\u0e21: NVIDIA GB10 Grace Blackwell Superchip (SoC)<\/p>\n<p>&nbsp;<\/p>\n<p data-path-to-node=\"13,1,1,2\">\u2022 CPU: 20\u2011core Arm (10\u00d7 Cortex\u2011X925 + 10\u00d7 Cortex\u2011A725)<\/p>\n<p>&nbsp;<\/p>\n<p data-path-to-node=\"13,1,1,4\">\u2022 GPU: NVIDIA Blackwell Architecture (6,144 CUDA Cores, 5th Gen Tensor Cores, 4th Gen RT Cores)<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td><span data-path-to-node=\"13,2,0,0\"><b data-path-to-node=\"13,2,0,0\" data-index-in-node=\"0\">\u0e1b\u0e23\u0e30\u0e2a\u0e34\u0e17\u0e18\u0e34\u0e20\u0e32\u0e1e AI<\/b><\/span><\/td>\n<td>\n<p data-path-to-node=\"13,2,1,0\">\u0e2a\u0e39\u0e07\u0e2a\u0e38\u0e14 1,000 TOPS AI inference \/ 1 PFLOP \u0e17\u0e35\u0e48 FP4 (\u0e1e\u0e23\u0e49\u0e2d\u0e21 sparsity)<\/p>\n<p>&nbsp;<\/p>\n<p data-path-to-node=\"13,2,1,2\"><i data-path-to-node=\"13,2,1,2\" data-index-in-node=\"0\">(\u0e23\u0e2d\u0e07\u0e23\u0e31\u0e1a\u0e42\u0e21\u0e40\u0e14\u0e25 Reasoning\/LLM \u0e2a\u0e39\u0e07\u0e2a\u0e38\u0e14 ~200B parameters \u0e43\u0e19\u0e40\u0e04\u0e23\u0e37\u0e48\u0e2d\u0e07\u0e40\u0e14\u0e35\u0e22\u0e27)<\/i><\/p>\n<\/td>\n<\/tr>\n<tr>\n<td><span data-path-to-node=\"13,3,0,0\"><b data-path-to-node=\"13,3,0,0\" data-index-in-node=\"0\">\u0e2b\u0e19\u0e48\u0e27\u0e22\u0e04\u0e27\u0e32\u0e21\u0e08\u0e33 (RAM)<\/b><\/span><\/td>\n<td><span data-path-to-node=\"13,3,1,0\">128GB LPDDR5x Unified System Memory (256\u2011bit, 4266 MHz, \u0e41\u0e1a\u0e19\u0e14\u0e4c\u0e27\u0e34\u0e14\u0e18\u0e4c 273 GB\/s)<\/span><\/td>\n<\/tr>\n<tr>\n<td><span data-path-to-node=\"13,4,0,0\"><b data-path-to-node=\"13,4,0,0\" data-index-in-node=\"0\">\u0e1e\u0e37\u0e49\u0e19\u0e17\u0e35\u0e48\u0e08\u0e31\u0e14\u0e40\u0e01\u0e47\u0e1a\u0e02\u0e49\u0e2d\u0e21\u0e39\u0e25 (Storage)<\/b><\/span><\/td>\n<td><span data-path-to-node=\"13,4,1,0\">4TB NVMe M.2 SSD \u0e41\u0e1a\u0e1a Self\u2011encrypting (\u0e2e\u0e32\u0e23\u0e4c\u0e14\u0e41\u0e27\u0e23\u0e4c\u0e40\u0e02\u0e49\u0e32\u0e23\u0e2b\u0e31\u0e2a\u0e43\u0e19\u0e15\u0e31\u0e27)<\/span><\/td>\n<\/tr>\n<tr>\n<td><span data-path-to-node=\"13,5,0,0\"><b data-path-to-node=\"13,5,0,0\" data-index-in-node=\"0\">\u0e23\u0e30\u0e1a\u0e1a\u0e1b\u0e0f\u0e34\u0e1a\u0e31\u0e15\u0e34\u0e01\u0e32\u0e23\u0e41\u0e25\u0e30\u0e0b\u0e2d\u0e1f\u0e15\u0e4c\u0e41\u0e27\u0e23\u0e4c<\/b><\/span><\/td>\n<td>\n<p data-path-to-node=\"13,5,1,0\">\u2022 NVIDIA DGX OS (Linux\/Ubuntu 22.04\u2011base)<\/p>\n<p>&nbsp;<\/p>\n<p data-path-to-node=\"13,5,1,2\">\u2022 \u0e15\u0e34\u0e14\u0e15\u0e31\u0e49\u0e07 CUDA, cuDNN, TensorRT, Triton Inference Server, NVIDIA AI Enterprise stack<\/p>\n<p>&nbsp;<\/p>\n<p data-path-to-node=\"13,5,1,4\">\u2022 \u0e23\u0e2d\u0e07\u0e23\u0e31\u0e1a Hugging Face, PyTorch, \u0e42\u0e21\u0e40\u0e14\u0e25 Cosmos Reason, GR00T N1, DeepSeek, Meta, Google \u0e2f\u0e25\u0e2f<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td><span data-path-to-node=\"13,6,0,0\"><b data-path-to-node=\"13,6,0,0\" data-index-in-node=\"0\">\u0e01\u0e32\u0e23\u0e40\u0e0a\u0e37\u0e48\u0e2d\u0e21\u0e15\u0e48\u0e2d\u0e40\u0e04\u0e23\u0e37\u0e2d\u0e02\u0e48\u0e32\u0e22\u0e23\u0e30\u0e14\u0e31\u0e1a\u0e2a\u0e39\u0e07<\/b><\/span><\/td>\n<td>\n<p data-path-to-node=\"13,6,1,0\">\u2022 1\u00d7 10GbE RJ\u201145 Ethernet<\/p>\n<p>&nbsp;<\/p>\n<p data-path-to-node=\"13,6,1,2\">\u2022 2\u00d7 200Gbps QSFP (\u0e1c\u0e48\u0e32\u0e19 NVIDIA ConnectX) \u0e2a\u0e33\u0e2b\u0e23\u0e31\u0e1a\u0e40\u0e0a\u0e37\u0e48\u0e2d\u0e21 DGX Spark \u0e2a\u0e2d\u0e07\u0e40\u0e04\u0e23\u0e37\u0e48\u0e2d\u0e07\u0e40\u0e1b\u0e47\u0e19 Mini\u2011cluster<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td><span data-path-to-node=\"13,7,0,0\"><b data-path-to-node=\"13,7,0,0\" data-index-in-node=\"0\">\u0e1e\u0e2d\u0e23\u0e4c\u0e15\u0e40\u0e0a\u0e37\u0e48\u0e2d\u0e21\u0e15\u0e48\u0e2d (I\/O Ports)<\/b><\/span><\/td>\n<td>\n<p data-path-to-node=\"13,7,1,0\">\u2022 4\u00d7 USB\u2011C (\u0e2b\u0e19\u0e36\u0e48\u0e07\u0e1e\u0e2d\u0e23\u0e4c\u0e15\u0e43\u0e0a\u0e49\u0e23\u0e31\u0e1a\u0e44\u0e1f\u0e40\u0e25\u0e35\u0e49\u0e22\u0e07 Power-in)<\/p>\n<p>&nbsp;<\/p>\n<p data-path-to-node=\"13,7,1,2\">\u2022 1\u00d7 HDMI 2.1<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td><span data-path-to-node=\"13,8,0,0\"><b data-path-to-node=\"13,8,0,0\" data-index-in-node=\"0\">\u0e02\u0e19\u0e32\u0e14\u0e41\u0e25\u0e30\u0e1f\u0e2d\u0e23\u0e4c\u0e21\u0e41\u0e1f\u0e01\u0e40\u0e15\u0e2d\u0e23\u0e4c<\/b><\/span><\/td>\n<td>\n<p data-path-to-node=\"13,8,1,0\"><b data-path-to-node=\"13,8,1,0\" data-index-in-node=\"0\">\u0e02\u0e19\u0e32\u0e14:<\/b> \u0e1b\u0e23\u0e30\u0e21\u0e32\u0e13 1.8 \u0e25\u0e34\u0e15\u0e23 (\u0e40\u0e04\u0e2a\u0e42\u0e25\u0e2b\u0e30\u0e1e\u0e23\u0e49\u0e2d\u0e21\u0e0a\u0e38\u0e14\u0e23\u0e30\u0e1a\u0e32\u0e22\u0e04\u0e27\u0e32\u0e21\u0e23\u0e49\u0e2d\u0e19\u0e2d\u0e2d\u0e01\u0e41\u0e1a\u0e1a\u0e40\u0e09\u0e1e\u0e32\u0e30)<\/p>\n<p>&nbsp;<\/p>\n<p data-path-to-node=\"13,8,1,2\"><b data-path-to-node=\"13,8,1,2\" data-index-in-node=\"0\">\u0e19\u0e49\u0e33\u0e2b\u0e19\u0e31\u0e01:<\/b> \u0e1b\u0e23\u0e30\u0e21\u0e32\u0e13 1.2 \u0e01\u0e01.<\/p>\n<\/td>\n<\/tr>\n<tr>\n<td><span data-path-to-node=\"13,9,0,0\"><b data-path-to-node=\"13,9,0,0\" data-index-in-node=\"0\">\u0e1e\u0e25\u0e31\u0e07\u0e07\u0e32\u0e19<\/b><\/span><\/td>\n<td><span data-path-to-node=\"13,9,1,0\">\u0e1e\u0e32\u0e27\u0e40\u0e27\u0e2d\u0e23\u0e4c\u0e0b\u0e31\u0e1e\u0e1e\u0e25\u0e32\u0e22 240W (\u0e2d\u0e30\u0e41\u0e14\u0e1b\u0e40\u0e15\u0e2d\u0e23\u0e4c\u0e20\u0e32\u0e22\u0e19\u0e2d\u0e01 \u0e15\u0e48\u0e2d\u0e40\u0e02\u0e49\u0e32\u0e17\u0e32\u0e07 USB\u2011C)<\/span><\/td>\n<\/tr>\n<tr>\n<td><span data-path-to-node=\"13,10,0,0\"><b data-path-to-node=\"13,10,0,0\" data-index-in-node=\"0\">\u0e01\u0e25\u0e38\u0e48\u0e21\u0e1c\u0e39\u0e49\u0e43\u0e0a\u0e49\u0e40\u0e1b\u0e49\u0e32\u0e2b\u0e21\u0e32\u0e22<\/b><\/span><\/td>\n<td><span data-path-to-node=\"13,10,1,0\">\u0e19\u0e31\u0e01\u0e1e\u0e31\u0e12\u0e19\u0e32\u0e2d\u0e07\u0e04\u0e4c\u0e01\u0e23\u0e41\u0e25\u0e30\u0e2a\u0e48\u0e27\u0e19\u0e15\u0e31\u0e27 \u0e17\u0e35\u0e48\u0e15\u0e49\u0e2d\u0e07\u0e01\u0e32\u0e23 Prototype \/ Fine\u2011tune \/ Inference \u0e42\u0e21\u0e40\u0e14\u0e25\u0e02\u0e19\u0e32\u0e14\u0e43\u0e2b\u0e0d\u0e48\u0e41\u0e1a\u0e1a Local \u0e01\u0e48\u0e2d\u0e19 Deploy \u0e02\u0e36\u0e49\u0e19 Data Center<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p data-path-to-node=\"12\">","protected":false},"excerpt":{"rendered":"<p><b data-path-to-node=\"7\" data-index-in-node=\"0\">\u0e22\u0e48\u0e2d\u0e2a\u0e48\u0e27\u0e19 Data Center \u0e21\u0e32\u0e44\u0e27\u0e49\u0e1a\u0e19\u0e42\u0e15\u0e4a\u0e30\u0e17\u0e33\u0e07\u0e32\u0e19\u0e02\u0e2d\u0e07\u0e04\u0e38\u0e13\u0e14\u0e49\u0e27\u0e22 NVIDIA DGX Spark<\/b> \u0e2a\u0e31\u0e21\u0e1c\u0e31\u0e2a\u0e1b\u0e23\u0e30\u0e2a\u0e1a\u0e01\u0e32\u0e23\u0e13\u0e4c &#8220;Personal AI Supercomputer&#8221; \u0e2d\u0e22\u0e48\u0e32\u0e07\u0e41\u0e17\u0e49\u0e08\u0e23\u0e34\u0e07\u0e01\u0e31\u0e1a NVIDIA DGX Spark \u0e40\u0e27\u0e34\u0e23\u0e4c\u0e01\u0e2a\u0e40\u0e15\u0e0a\u0e31\u0e19 AI \u0e23\u0e30\u0e14\u0e31\u0e1a\u0e40\u0e23\u0e37\u0e2d\u0e18\u0e07\u0e17\u0e35\u0e48\u0e02\u0e31\u0e1a\u0e40\u0e04\u0e25\u0e37\u0e48\u0e2d\u0e19\u0e14\u0e49\u0e27\u0e22\u0e02\u0e38\u0e21\u0e1e\u0e25\u0e31\u0e07 GB10 Grace Blackwell Superchip \u0e1b\u0e25\u0e14\u0e1b\u0e25\u0e48\u0e2d\u0e22\u0e1b\u0e23\u0e30\u0e2a\u0e34\u0e17\u0e18\u0e34\u0e20\u0e32\u0e1e\u0e01\u0e32\u0e23\u0e04\u0e33\u0e19\u0e27\u0e13\u0e2a\u0e39\u0e07\u0e2a\u0e38\u0e14 1 PFLOP \u0e2d\u0e2d\u0e01\u0e41\u0e1a\u0e1a\u0e21\u0e32\u0e40\u0e1e\u0e37\u0e48\u0e2d\u0e01\u0e32\u0e23\u0e17\u0e33 Prototype, Fine-tune \u0e41\u0e25\u0e30\u0e23\u0e31\u0e19 Inference \u0e42\u0e21\u0e40\u0e14\u0e25 LLM \u0e2b\u0e23\u0e37\u0e2d\u0e42\u0e21\u0e40\u0e14\u0e25 Reasoning \u0e02\u0e19\u0e32\u0e14 200B parameters \u0e44\u0e14\u0e49\u0e08\u0e1a\u0e43\u0e19\u0e40\u0e04\u0e23\u0e37\u0e48\u0e2d\u0e07\u0e40\u0e14\u0e35\u0e22\u0e27 \u0e1e\u0e23\u0e49\u0e2d\u0e21\u0e0b\u0e2d\u0e1f\u0e15\u0e4c\u0e41\u0e27\u0e23\u0e4c\u0e2a\u0e41\u0e15\u0e47\u0e01\u0e23\u0e30\u0e14\u0e31\u0e1a\u0e2d\u0e07\u0e04\u0e4c\u0e01\u0e23 (NVIDIA AI Enterprise) \u0e17\u0e35\u0e48\u0e43\u0e2b\u0e49\u0e04\u0e38\u0e13\u0e1e\u0e31\u0e12\u0e19\u0e32\u0e42\u0e21\u0e40\u0e14\u0e25\u0e1a\u0e19\u0e42\u0e15\u0e4a\u0e30\u0e17\u0e33\u0e07\u0e32\u0e19\u0e41\u0e25\u0e49\u0e27\u0e2a\u0e40\u0e01\u0e25\u0e02\u0e36\u0e49\u0e19 Cloud \u0e2b\u0e23\u0e37\u0e2d Data Center \u0e44\u0e14\u0e49\u0e2d\u0e22\u0e48\u0e32\u0e07\u0e44\u0e23\u0e49\u0e23\u0e2d\u0e22\u0e15\u0e48\u0e2d!<\/p>\n<div style=\"width: 100%; text-align: center; padding: 24px 0;\"><a style=\"display: inline-block; background-color: #06c755; color: #ffffff; font-size: 16px; font-weight: bold; text-decoration: none; padding: 14px 32px; border-radius: 50px; box-shadow: 0 4px 12px rgba(6,199,85,0.4); white-space: nowrap;\" href=\"https:\/\/page.line.me\/682mqqmh?openQrModal=true\" target=\"_blank\" rel=\"noopener\">\u0e2a\u0e2d\u0e1a\u0e16\u0e32\u0e21\u0e23\u0e32\u0e04\u0e32 \/ \u0e2a\u0e31\u0e48\u0e07\u0e0b\u0e37\u0e49\u0e2d LINE: @metaxr<\/a><\/div>","protected":false},"featured_media":15717,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"default","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"set","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center 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