{"id":9029,"date":"2025-07-15T08:39:43","date_gmt":"2025-07-15T08:39:43","guid":{"rendered":"https:\/\/gpucore.co\/?post_type=product&#038;p=9029"},"modified":"2025-07-15T08:55:54","modified_gmt":"2025-07-15T08:55:54","slug":"jetson-agx-xavier","status":"publish","type":"product","link":"https:\/\/gpucore.co\/ko\/shop\/jetson-agx-xavier\/","title":{"rendered":"Jetson AGX Xavier \u0e42\u0e21\u0e14\u0e39\u0e25\u0e1b\u0e23\u0e30\u0e21\u0e27\u0e25\u0e1c\u0e25 AI"},"content":{"rendered":"<p><span style=\"font-weight: 400;\">Jetson AGX Xavier<\/span><span style=\"font-weight: 400;\"> \u0e04\u0e37\u0e2d\u0e42\u0e21\u0e14\u0e39\u0e25 AI \u0e02\u0e19\u0e32\u0e14\u0e01\u0e30\u0e17\u0e31\u0e14\u0e23\u0e31\u0e14\u0e41\u0e15\u0e48\u0e17\u0e23\u0e07\u0e1e\u0e25\u0e31\u0e07 \u0e2a\u0e33\u0e2b\u0e23\u0e31\u0e1a\u0e07\u0e32\u0e19 Edge Computing, \u0e40\u0e04\u0e23\u0e37\u0e48\u0e2d\u0e07\u0e08\u0e31\u0e01\u0e23\u0e2d\u0e31\u0e15\u0e42\u0e19\u0e21\u0e31\u0e15\u0e34, \u0e2b\u0e38\u0e48\u0e19\u0e22\u0e19\u0e15\u0e4c, \u0e23\u0e30\u0e1a\u0e1a\u0e43\u0e19\u0e42\u0e23\u0e07\u0e07\u0e32\u0e19 \u0e41\u0e25\u0e30\u0e41\u0e2d\u0e1b\u0e1e\u0e25\u0e34\u0e40\u0e04\u0e0a\u0e31\u0e19 AI \u0e41\u0e1a\u0e1a\u0e1d\u0e31\u0e07\u0e15\u0e31\u0e27 \u0e23\u0e2d\u0e07\u0e23\u0e31\u0e1a\u0e01\u0e32\u0e23\u0e1e\u0e31\u0e12\u0e19\u0e32\u0e42\u0e0b\u0e25\u0e39\u0e0a\u0e31\u0e19\u0e1b\u0e23\u0e30\u0e2a\u0e34\u0e17\u0e18\u0e34\u0e20\u0e32\u0e1e\u0e2a\u0e39\u0e07\u0e17\u0e31\u0e49\u0e07\u0e43\u0e19\u0e2d\u0e38\u0e15\u0e2a\u0e32\u0e2b\u0e01\u0e23\u0e23\u0e21\u0e41\u0e25\u0e30\u0e07\u0e32\u0e19\u0e14\u0e49\u0e32\u0e19 Automation<\/span><\/p>\n<p><strong>\u0e08\u0e38\u0e14\u0e40\u0e14\u0e48\u0e19\u0e2b\u0e25\u0e31\u0e01<\/strong><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">\u0e1b\u0e23\u0e30\u0e2a\u0e34\u0e17\u0e18\u0e34\u0e20\u0e32\u0e1e AI \u0e2a\u0e39\u0e07\u0e2a\u0e38\u0e14 32 TOPS<\/span><span style=\"font-weight: 400;\"> \u0e23\u0e2d\u0e07\u0e23\u0e31\u0e1a\u0e07\u0e32\u0e19\u0e1b\u0e23\u0e30\u0e21\u0e27\u0e25\u0e1c\u0e25 AI \u0e17\u0e35\u0e48\u0e0b\u0e31\u0e1a\u0e0b\u0e49\u0e2d\u0e19\u0e41\u0e25\u0e30\u0e23\u0e27\u0e14\u0e40\u0e23\u0e47\u0e27<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">\u0e02\u0e19\u0e32\u0e14\u0e01\u0e30\u0e17\u0e31\u0e14\u0e23\u0e31\u0e14<\/span><span style=\"font-weight: 400;\"> \u0e40\u0e1e\u0e35\u0e22\u0e07 100 x 87 \u0e21\u0e21. \u0e0a\u0e48\u0e27\u0e22\u0e43\u0e2b\u0e49\u0e15\u0e34\u0e14\u0e15\u0e31\u0e49\u0e07\u0e43\u0e19\u0e23\u0e30\u0e1a\u0e1a\u0e15\u0e48\u0e32\u0e07 \u0e46 \u0e44\u0e14\u0e49\u0e07\u0e48\u0e32\u0e22<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">\u0e01\u0e32\u0e23\u0e43\u0e0a\u0e49\u0e1e\u0e25\u0e31\u0e07\u0e07\u0e32\u0e19\u0e22\u0e37\u0e14\u0e2b\u0e22\u0e38\u0e48\u0e19<\/span><span style=\"font-weight: 400;\"> \u0e1b\u0e23\u0e31\u0e1a\u0e40\u0e25\u0e37\u0e2d\u0e01\u0e42\u0e2b\u0e21\u0e14\u0e44\u0e14\u0e49 10W, 15W \u0e2b\u0e23\u0e37\u0e2d 30W \u0e15\u0e23\u0e07\u0e01\u0e31\u0e1a\u0e01\u0e32\u0e23\u0e43\u0e0a\u0e49\u0e07\u0e32\u0e19<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">\u0e40\u0e2b\u0e21\u0e32\u0e30\u0e2a\u0e33\u0e2b\u0e23\u0e31\u0e1a\u0e23\u0e30\u0e1a\u0e1a\u0e2d\u0e31\u0e15\u0e42\u0e19\u0e21\u0e31\u0e15\u0e34-\u0e2b\u0e38\u0e48\u0e19\u0e22\u0e19\u0e15\u0e4c-\u0e2d\u0e38\u0e15\u0e2a\u0e32\u0e2b\u0e01\u0e23\u0e23\u0e21 \u0e41\u0e25\u0e30\u0e41\u0e2d\u0e1b\u0e1e\u0e25\u0e34\u0e40\u0e04\u0e0a\u0e31\u0e19\u0e17\u0e35\u0e48\u0e15\u0e49\u0e2d\u0e07\u0e01\u0e32\u0e23 Embedded AI<\/span><\/li>\n<\/ul>\n<p><strong>\u0e04\u0e38\u0e13\u0e2a\u0e21\u0e1a\u0e31\u0e15\u0e34\u0e17\u0e32\u0e07\u0e40\u0e17\u0e04\u0e19\u0e34\u0e04<\/strong><\/p>\n<table>\n<tbody>\n<tr>\n<td><b>\ubc94\uc8fc<\/b><\/td>\n<td><b>\uc138\ubd80<\/b><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">GPU<\/span><\/td>\n<td><span style=\"font-weight: 400;\">NVIDIA Volta\u2122 512 CUDA Cores + 64 Tensor Cores<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">CPU<\/span><\/td>\n<td><span style=\"font-weight: 400;\">ARM\u00ae v8.2 64-bit, 8 \u0e04\u0e2d\u0e23\u0e4c, L2 cache 8MB + L3 cache 4MB<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">DL Accelerator<\/span><\/td>\n<td><span style=\"font-weight: 400;\">NVDLA Engines 2 \u0e15\u0e31\u0e27<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">Vision Accelerator<\/span><\/td>\n<td><span style=\"font-weight: 400;\">\u0e42\u0e1b\u0e23\u0e40\u0e0b\u0e2a\u0e40\u0e0b\u0e2d\u0e23\u0e4c VLIW 7-way<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">RAM<\/span><\/td>\n<td><span style=\"font-weight: 400;\">32GB \u0e2b\u0e23\u0e37\u0e2d 64GB LPDDR4x 256-bit (BW 136.5 GB\/s)<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">\uc800\uc7a5\uc18c<\/span><\/td>\n<td><span style=\"font-weight: 400;\">32GB eMMC 5.1<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">Network<\/span><\/td>\n<td><span style=\"font-weight: 400;\">Gigabit Ethernet<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">PCIe<\/span><\/td>\n<td><span style=\"font-weight: 400;\">PCIe Gen4<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">MIPI CSI-2<\/span><\/td>\n<td><span style=\"font-weight: 400;\">\u0e23\u0e2d\u0e07\u0e23\u0e31\u0e1a\u0e01\u0e25\u0e49\u0e2d\u0e07\u0e41\u0e25\u0e30\u0e42\u0e21\u0e14\u0e39\u0e25\u0e15\u0e23\u0e27\u0e08\u0e08\u0e31\u0e1a\u0e2a\u0e31\u0e0d\u0e0d\u0e32\u0e13\u0e20\u0e32\u0e1e<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">USB<\/span><\/td>\n<td><span style=\"font-weight: 400;\">USB 3.1<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">Video Encode<\/span><\/td>\n<td><span style=\"font-weight: 400;\">4K60 (HEVC)<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">Video Decode<\/span><\/td>\n<td><span style=\"font-weight: 400;\">4K60 (HEVC)<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">\u0e02\u0e19\u0e32\u0e14\u0e1a\u0e2d\u0e23\u0e4c\u0e14<\/span><\/td>\n<td><span style=\"font-weight: 400;\">100 \u0e21\u0e21. x 87 \u0e21\u0e21.<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">\u0e01\u0e33\u0e25\u0e31\u0e07\u0e44\u0e1f<\/span><\/td>\n<td><span style=\"font-weight: 400;\">10W \/ 15W \/ 30W (\u0e40\u0e25\u0e37\u0e2d\u0e01\u0e1b\u0e23\u0e31\u0e1a\u0e44\u0e14\u0e49)<\/span><\/td>\n<\/tr>\n<tr>\n<td><span style=\"font-weight: 400;\">\u0e1b\u0e23\u0e30\u0e2a\u0e34\u0e17\u0e18\u0e34\u0e20\u0e32\u0e1e AI<\/span><\/td>\n<td><span style=\"font-weight: 400;\">\u0e2a\u0e39\u0e07\u0e2a\u0e38\u0e14 32 TOPS<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p><strong>\u0e1f\u0e35\u0e40\u0e08\u0e2d\u0e23\u0e4c\u0e0b\u0e2d\u0e1f\u0e15\u0e4c\u0e41\u0e27\u0e23\u0e4c<\/strong><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">\u0e23\u0e2d\u0e07\u0e23\u0e31\u0e1a\u0e0a\u0e38\u0e14 AI \u0e02\u0e2d\u0e07 NVIDIA<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"2\"><span style=\"font-weight: 400;\">TensorRT<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"2\"><span style=\"font-weight: 400;\">DeepStream<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"2\"><span style=\"font-weight: 400;\">JetPack SDK \u0e0a\u0e48\u0e27\u0e22\u0e40\u0e23\u0e48\u0e07\u0e01\u0e32\u0e23\u0e1b\u0e23\u0e31\u0e1a\u0e43\u0e0a\u0e49\u0e41\u0e25\u0e30\u0e40\u0e1e\u0e34\u0e48\u0e21\u0e1b\u0e23\u0e30\u0e2a\u0e34\u0e17\u0e18\u0e34\u0e20\u0e32\u0e1e\u0e42\u0e21\u0e40\u0e14\u0e25 AI<\/span><\/li>\n<\/ul>\n<p><strong>\u0e40\u0e2b\u0e21\u0e32\u0e30\u0e2a\u0e33\u0e2b\u0e23\u0e31\u0e1a\u0e43\u0e04\u0e23<\/strong><\/p>\n<ul>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">\u0e19\u0e31\u0e01\u0e1e\u0e31\u0e12\u0e19\u0e32\u0e41\u0e25\u0e30\u0e27\u0e34\u0e28\u0e27\u0e01\u0e23\u0e23\u0e30\u0e1a\u0e1a AI \u0e1a\u0e19 Edge \u0e2b\u0e23\u0e37\u0e2d\u0e07\u0e32\u0e19 Embedded<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">\u0e07\u0e32\u0e19 Automation \u0e43\u0e19\u0e42\u0e23\u0e07\u0e07\u0e32\u0e19\u0e2b\u0e23\u0e37\u0e2d\u0e2d\u0e38\u0e15\u0e2a\u0e32\u0e2b\u0e01\u0e23\u0e23\u0e21 4.0<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">\u0e23\u0e30\u0e1a\u0e1a\u0e2b\u0e38\u0e48\u0e19\u0e22\u0e19\u0e15\u0e4c, AGV\/AMR, Vision Inspection<\/span><\/li>\n<li style=\"font-weight: 400;\" aria-level=\"1\"><span style=\"font-weight: 400;\">\u0e42\u0e0b\u0e25\u0e39\u0e0a\u0e31\u0e19\u0e17\u0e35\u0e48\u0e15\u0e49\u0e2d\u0e07\u0e01\u0e32\u0e23\u0e04\u0e27\u0e32\u0e21\u0e40\u0e2a\u0e16\u0e35\u0e22\u0e23 \u0e1b\u0e23\u0e30\u0e2a\u0e34\u0e17\u0e18\u0e34\u0e20\u0e32\u0e1e\u0e2a\u0e39\u0e07 \u0e41\u0e25\u0e30\u0e1b\u0e23\u0e30\u0e2b\u0e22\u0e31\u0e14\u0e1e\u0e25\u0e31\u0e07\u0e07\u0e32\u0e19<\/span><\/li>\n<\/ul>\n<p><span style=\"font-weight: 400;\">Jetson AGX Xavier<\/span><span style=\"font-weight: 400;\"> \u0e04\u0e37\u0e2d\u0e2b\u0e31\u0e27\u0e43\u0e08\u0e2b\u0e25\u0e31\u0e01\u0e2a\u0e33\u0e2b\u0e23\u0e31\u0e1a\u0e15\u0e25\u0e32\u0e14 Edge AI \u0e22\u0e38\u0e04\u0e43\u0e2b\u0e21\u0e48 \u0e15\u0e2d\u0e1a\u0e42\u0e08\u0e17\u0e22\u0e4c\u0e17\u0e31\u0e49\u0e07\u0e01\u0e32\u0e23\u0e1b\u0e23\u0e30\u0e21\u0e27\u0e25\u0e1c\u0e25\u0e23\u0e27\u0e14\u0e40\u0e23\u0e47\u0e27 \u0e1b\u0e23\u0e30\u0e2b\u0e22\u0e31\u0e14\u0e1e\u0e37\u0e49\u0e19\u0e17\u0e35\u0e48 \u0e41\u0e25\u0e30\u0e01\u0e49\u0e32\u0e27\u0e2b\u0e19\u0e49\u0e32\u0e43\u0e19\u0e27\u0e07\u0e01\u0e32\u0e23\u0e2d\u0e38\u0e15\u0e2a\u0e32\u0e2b\u0e01\u0e23\u0e23\u0e21\u0e2d\u0e31\u0e08\u0e09\u0e23\u0e34\u0e22\u0e30<\/span><\/p>\n<p>&nbsp;<\/p>","protected":false},"excerpt":{"rendered":"<p>Jetson AGX Xavier \u0e42\u0e21\u0e14\u0e39\u0e25\u0e1b\u0e23\u0e30\u0e21\u0e27\u0e25\u0e1c\u0e25 AI \u0e1b\u0e23\u0e30\u0e2a\u0e34\u0e17\u0e18\u0e34\u0e20\u0e32\u0e1e\u0e2a\u0e39\u0e07\u0e2a\u0e33\u0e2b\u0e23\u0e31\u0e1a Edge Computing \u0e43\u0e2b\u0e49\u0e1e\u0e25\u0e31\u0e07\u0e01\u0e32\u0e23\u0e1b\u0e23\u0e30\u0e21\u0e27\u0e25\u0e1c\u0e25\u0e2a\u0e39\u0e07\u0e2a\u0e38\u0e14 32 TOPS \u0e43\u0e19\u0e02\u0e19\u0e32\u0e14\u0e01\u0e30\u0e17\u0e31\u0e14\u0e23\u0e31\u0e14 \u0e40\u0e2b\u0e21\u0e32\u0e30\u0e2a\u0e33\u0e2b\u0e23\u0e31\u0e1a\u0e40\u0e04\u0e23\u0e37\u0e48\u0e2d\u0e07\u0e08\u0e31\u0e01\u0e23\u0e2d\u0e31\u0e15\u0e42\u0e19\u0e21\u0e31\u0e15\u0e34 \u0e2b\u0e38\u0e48\u0e19\u0e22\u0e19\u0e15\u0e4c \u0e23\u0e30\u0e1a\u0e1a\u0e2d\u0e31\u0e15\u0e42\u0e19\u0e21\u0e31\u0e15\u0e34\u0e43\u0e19\u0e2d\u0e38\u0e15\u0e2a\u0e32\u0e2b\u0e01\u0e23\u0e23\u0e21 \u0e41\u0e25\u0e30\u0e41\u0e2d\u0e1b\u0e1e\u0e25\u0e34\u0e40\u0e04\u0e0a\u0e31\u0e19 AI \u0e41\u0e1a\u0e1a\u0e1d\u0e31\u0e07\u0e15\u0e31\u0e27 \u0e40\u0e0a\u0e37\u0e48\u0e2d\u0e16\u0e37\u0e2d\u0e44\u0e14\u0e49 \u0e1b\u0e23\u0e30\u0e2b\u0e22\u0e31\u0e14\u0e1e\u0e25\u0e31\u0e07\u0e07\u0e32\u0e19 \u0e1e\u0e23\u0e49\u0e2d\u0e21\u0e0b\u0e2d\u0e1f\u0e15\u0e4c\u0e41\u0e27\u0e23\u0e4c NVIDIA AI 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