{"id":375,"date":"2026-05-19T18:16:03","date_gmt":"2026-05-19T18:16:03","guid":{"rendered":"https:\/\/convly.ai\/amd-rocm-vs-nvidia-cuda-2026\/"},"modified":"2026-07-11T16:59:03","modified_gmt":"2026-07-11T16:59:03","slug":"amd-rocm-vs-nvidia-cuda-2026","status":"publish","type":"post","link":"https:\/\/convly.ai\/ar\/amd-rocm-vs-nvidia-cuda-2026\/","title":{"rendered":"\u0645\u0642\u0627\u0631\u0646\u0629 \u0645\u0646\u0635\u0629 AMD ROCm \u0645\u0639 \u0645\u0646\u0635\u0629 Nvidia CUDA \u0641\u064a \u0639\u0627\u0645 2026: \u0647\u0644 \u0627\u0646\u063a\u0644\u0642\u062a \u0627\u0644\u0641\u062c\u0648\u0629 \u0623\u062e\u064a\u0631\u064b\u0627\u061f"},"content":{"rendered":"<p>\u0644\u0645\u062f\u0629 \u062e\u0645\u0633 \u0633\u0646\u0648\u0627\u062a \u0643\u0627\u0646\u062a \u0627\u0644\u0625\u062c\u0627\u0628\u0629 \u0628\u0633\u064a\u0637\u0629: <strong>\u0625\u0630\u0627 \u0643\u0646\u062a \u062a\u0631\u064a\u062f \u0627\u0644\u0630\u0643\u0627\u0621 \u0627\u0644\u0627\u0635\u0637\u0646\u0627\u0639\u064a\u060c \u0641\u0627\u0634\u062a\u0631\u0650 Nvidia<\/strong>. \u0643\u0627\u0646 \u062a\u0642\u062f\u0645 \u0628\u0631\u0646\u0627\u0645\u062c CUDA \u0647\u0627\u0626\u0644\u0627\u064b \u0644\u0644\u063a\u0627\u064a\u0629 \u0644\u062f\u0631\u062c\u0629 \u0623\u0646 \u0645\u064a\u0632\u0629 \u0623\u062c\u0647\u0632\u0629 AMD \u0639\u0644\u0649 \u0627\u0644\u0648\u0631\u0642 \u0644\u0645 \u062a\u064f\u062a\u0631\u062c\u0645 \u0623\u0628\u062f\u064b\u0627 \u0625\u0644\u0649 \u0633\u064a\u0631 \u0639\u0645\u0644 \u062d\u0642\u064a\u0642\u064a. \u0641\u064a \u0639\u0627\u0645 2026\u060c \u0644\u0645 \u064a\u0639\u062f \u0647\u0630\u0627 \u0635\u062d\u064a\u062d\u064b\u0627 \u062a\u0645\u0627\u0645\u064b\u0627 - \u0648\u0644\u0643\u0646\u0647 \u0623\u064a\u0636\u064b\u0627 \u0644\u064a\u0633 \u062e\u0627\u0637\u0626\u064b\u0627 \u062a\u0645\u0627\u0645\u064b\u0627.<\/p>\n<p>\u0642\u0645\u0646\u0627 \u0628\u062a\u0634\u063a\u064a\u0644 \u0623\u0639\u0628\u0627\u0621 \u0639\u0645\u0644 \u0627\u0644\u0630\u0643\u0627\u0621 \u0627\u0644\u0627\u0635\u0637\u0646\u0627\u0639\u064a \u0646\u0641\u0633\u0647\u0627 \u0639\u0644\u0649 \u062c\u0647\u0627\u0632 Radeon RX 7900 XTX (24 \u062c\u064a\u062c\u0627\u0628\u0627\u064a\u062a\u060c ROCm 6.3) \u0648RTX 4090 (24 \u062c\u064a\u062c\u0627\u0628\u0627\u064a\u062a\u060c CUDA 12.6). \u0646\u0641\u0633 \u0627\u0644\u0645\u0637\u0627\u0644\u0628\u0627\u062a \u0648\u0646\u0641\u0633 \u0627\u0644\u0637\u0631\u0627\u0632\u0627\u062a \u0648\u0646\u0641\u0633 \u0627\u0644\u062c\u0647\u0627\u0632. \u0625\u0644\u064a\u0643 \u0645\u0627 \u062d\u062f\u062b \u0628\u0627\u0644\u0641\u0639\u0644.<\/p>\n<div class=\"convly-tldr\">\n<h3>\u0623\u0628\u0631\u0632 \u0627\u0644\u0627\u0633\u062a\u0646\u062a\u0627\u062c\u0627\u062a<\/h3>\n<ul>\n<li><strong>\u0644\u0644\u0627\u0633\u062a\u062f\u0644\u0627\u0644 (LLMs\u060c \u0627\u0644\u0627\u0646\u062a\u0634\u0627\u0631 \u0627\u0644\u0645\u0633\u062a\u0642\u0631):<\/strong> \u0623\u0635\u0628\u062d\u062a ROCm \u0627\u0644\u0622\u0646 \u0642\u0627\u0628\u0644\u0629 \u0644\u0644\u0625\u0646\u062a\u0627\u062c \u0639\u0644\u0649 7900 XTX. 10-25% \u0623\u0628\u0637\u0623 \u0645\u0646 CUDA\u060c \u0648\u0644\u0643\u0646\u0647\u0627 \u062a\u0639\u0645\u0644.<\/li>\n<li><strong>\u0644\u0644\u062a\u062f\u0631\u064a\u0628\/\u0627\u0644\u0636\u0628\u0637 \u0627\u0644\u062f\u0642\u064a\u0642:<\/strong> \u0644\u0627 \u062a\u0632\u0627\u0644 CUDA \u062a\u0641\u0648\u0632 \u0641\u064a \u0645\u0639\u0638\u0645 \u0639\u0645\u0644\u064a\u0627\u062a \u0633\u064a\u0631 \u0627\u0644\u0639\u0645\u0644. \u064a\u062d\u062a\u0648\u064a ROCm \u0639\u0644\u0649 \u062b\u063a\u0631\u0627\u062a \u0641\u064a \u0643\u0648\u062f \u0627\u0644\u0628\u062d\u062b \u0627\u0644\u062c\u062f\u064a\u062f.<\/li>\n<li><strong>\u0644\u0644\u0623\u0648\u0631\u0627\u0642 \u0630\u0627\u062a \u0627\u0644\u062d\u0648\u0627\u0641 \u0627\u0644\u0646\u0627\u0632\u0641\u0629:<\/strong> \u064a\u062a\u0645 \u0625\u0633\u0642\u0627\u0637 \u0643\u0648\u062f CUDA \u0641\u0642\u0637 \u0623\u0633\u0628\u0648\u0639\u064a\u064b\u0627\u061b \u0648\u064a\u062a\u0628\u0639 \u0630\u0644\u0643 \u062f\u0639\u0645 ROCm \u062e\u0644\u0627\u0644 2-4 \u0623\u0633\u0627\u0628\u064a\u0639.<\/li>\n<li><strong>\u0628\u0627\u0644\u0646\u0633\u0628\u0629 \u0644\u0628\u0646\u0627\u0629 \u0627\u0644\u0630\u0643\u0627\u0621 \u0627\u0644\u0627\u0635\u0637\u0646\u0627\u0639\u064a \u0644\u0644\u0645\u0633\u062a\u0647\u0644\u0643\u064a\u0646:<\/strong> 7900 XTX 7900 XTX \u0641\u064a $900 \u0645\u0639 24 \u062c\u064a\u062c\u0627\u0628\u0627\u064a\u062a \u0647\u0648 \u0628\u062f\u064a\u0644 \u062d\u0642\u064a\u0642\u064a \u0644\u0640 4090 \u0627\u0644\u0645\u0633\u062a\u062e\u062f\u0645 $1300.<\/li>\n<li>\u0644\u0642\u062f \u0623\u063a\u0644\u0642\u062a \u0627\u0644\u0641\u062c\u0648\u0629 \u0628\u0645\u0627 \u064a\u0643\u0641\u064a \u0644\u062c\u0639\u0644 AMD \u201c\u062e\u064a\u0627\u0631\u064b\u0627 \u062d\u0642\u064a\u0642\u064a\u064b\u0627\u201d \u0641\u064a \u0639\u0627\u0645 2026 - \u0648\u0644\u0643\u0646 \u0644\u064a\u0633 \u0628\u0645\u0627 \u064a\u0643\u0641\u064a \u0644\u0644\u062a\u062e\u0644\u0641 \u0639\u0646 \u0627\u0644\u0631\u0643\u0628.<\/li>\n<\/ul>\n<\/div>\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_84 counter-flat ez-toc-counter ez-toc-container-direction\">\n<label for=\"ez-toc-cssicon-toggle-item-6a52fa411933e\" class=\"ez-toc-cssicon-toggle-label\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">\u062a\u0628\u062f\u064a\u0644<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #000000;color:#000000\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewbox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #000000;color:#000000\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewbox=\"0 0 24 24\" version=\"1.2\" baseprofile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/label><input type=\"checkbox\"  id=\"ez-toc-cssicon-toggle-item-6a52fa411933e\"  aria-label=\"\u062a\u0628\u062f\u064a\u0644\" \/><nav><ul class='ez-toc-list ez-toc-list-level-1' ><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/convly.ai\/ar\/amd-rocm-vs-nvidia-cuda-2026\/#What_changed_in_2026\" >\u0645\u0627 \u0627\u0644\u0630\u064a \u062a\u063a\u064a\u0631 \u0641\u064a \u0639\u0627\u0645 2026<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/convly.ai\/ar\/amd-rocm-vs-nvidia-cuda-2026\/#AI_workload_comparison_RX_7900_XTX_vs_RTX_4090_both_24_GB\" >\u0645\u0642\u0627\u0631\u0646\u0629 \u0639\u0628\u0621 \u0627\u0644\u0639\u0645\u0644 \u0628\u0627\u0644\u0630\u0643\u0627\u0621 \u0627\u0644\u0627\u0635\u0637\u0646\u0627\u0639\u064a (RX 7900 XTX \u0645\u0642\u0627\u0628\u0644 RTX 4090\u060c \u0643\u0644\u0627\u0647\u0645\u0627 \u0628\u0633\u0639\u0629 24 \u062c\u064a\u062c\u0627\u0628\u0627\u064a\u062a)<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/convly.ai\/ar\/amd-rocm-vs-nvidia-cuda-2026\/#The_data-center_picture_MI300X_MI355X_vs_H100_B200\" >\u0646\u0638\u0631\u0629 \u0639\u0627\u0645\u0629 \u0639\u0644\u0649 \u0645\u0631\u0627\u0643\u0632 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a: MI300X \/ MI355X \u0645\u0642\u0627\u0628\u0644 H100 \/ B200<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/convly.ai\/ar\/amd-rocm-vs-nvidia-cuda-2026\/#Where_ROCm_wins\" >\u062d\u064a\u062b \u062a\u0641\u0648\u0632 ROCm<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/convly.ai\/ar\/amd-rocm-vs-nvidia-cuda-2026\/#Where_CUDA_wins_still\" >\u062d\u064a\u062b \u062a\u0641\u0648\u0632 CUDA (\u0644\u0627 \u062a\u0632\u0627\u0644)<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/convly.ai\/ar\/amd-rocm-vs-nvidia-cuda-2026\/#Pros_and_cons\" >\u0627\u0644\u0645\u0632\u0627\u064a\u0627 \u0648\u0627\u0644\u0639\u064a\u0648\u0628<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/convly.ai\/ar\/amd-rocm-vs-nvidia-cuda-2026\/#Recommendation_by_user_type\" >\u0627\u0644\u062a\u0648\u0635\u064a\u0629 \u062d\u0633\u0628 \u0646\u0648\u0639 \u0627\u0644\u0645\u0633\u062a\u062e\u062f\u0645<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/convly.ai\/ar\/amd-rocm-vs-nvidia-cuda-2026\/#The_cloud_angle_renting_ROCm_vs_CUDA_by_the_hour\" >\u0645\u0646\u0638\u0648\u0631 \u0627\u0644\u0633\u062d\u0627\u0628\u0629: \u0627\u0633\u062a\u0626\u062c\u0627\u0631 ROCm \u0645\u0642\u0627\u0628\u0644 CUDA \u0628\u0627\u0644\u0633\u0627\u0639\u0629<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/convly.ai\/ar\/amd-rocm-vs-nvidia-cuda-2026\/#FAQ\" >\u0627\u0644\u0623\u0633\u0626\u0644\u0629 \u0627\u0644\u0634\u0627\u0626\u0639\u0629<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/convly.ai\/ar\/amd-rocm-vs-nvidia-cuda-2026\/#Bottom_line\" >\u0627\u0644\u062e\u0644\u0627\u0635\u0629<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-11\" href=\"https:\/\/convly.ai\/ar\/amd-rocm-vs-nvidia-cuda-2026\/#Related_articles\" >\u0645\u0642\u0627\u0644\u0627\u062a \u0630\u0627\u062a \u0635\u0644\u0629<\/a><\/li><\/ul><\/nav><\/div>\n<h2><span class=\"ez-toc-section\" id=\"What_changed_in_2026\"><\/span>\u0645\u0627 \u0627\u0644\u0630\u064a \u062a\u063a\u064a\u0631 \u0641\u064a \u0639\u0627\u0645 2026<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u062c\u0644\u0628\u062a ROCm 6.3 \u062b\u0644\u0627\u062b\u0629 \u0623\u0634\u064a\u0627\u0621 \u0645\u0647\u0645\u0629:<\/p>\n<p>1. <strong>PyTorch \u0644\u064a\u0644\u064a + 6.3 + 7900 XTX = \u064a\u0639\u0645\u0644 \u0641\u064a \u0627\u0644\u063a\u0627\u0644\u0628 \u0641\u0642\u0637.<\/strong> \u0642\u0628\u0644 \u0639\u0627\u0645\u064a\u0646\u060c \u0643\u0646\u062a \u0628\u062d\u0627\u062c\u0629 \u0625\u0644\u0649 \u0635\u0648\u0631 Docker\u060c \u0648 env vars \u063a\u0631\u064a\u0628\u0629\u060c \u0648\u0627\u0644\u062d\u0638. \u0623\u0645\u0627 \u0627\u0644\u0622\u0646 <code>pip install torch --index-url=https:\/\/download.pytorch.org\/whl\/rocm6.3<\/code> \u0648Llama 3 8B \u064a\u062a\u062f\u0631\u0628 \u0645\u0646 \u0627\u0644\u0645\u062d\u0627\u0648\u0644\u0629 \u0627\u0644\u0623\u0648\u0644\u0649.<br \/>\n2. <strong>\u062a\u0637\u0627\u0628\u0642 \u0627\u0644\u0648\u0627\u062c\u0647\u0629 \u0627\u0644\u062e\u0644\u0641\u064a\u0629 \u0644\u0640 llama.cpp ROCm \u0627\u0644\u062e\u0644\u0641\u064a\u0629 \u0645\u0639 \u0645\u0633\u0627\u0631\u0627\u062a Metal\/CUDA<\/strong> \u0644\u0644\u0623\u062f\u0627\u0621 \u0639\u0644\u0649 \u0627\u0644\u0646\u0645\u0627\u0630\u062c \u0627\u0644\u0643\u0645\u064a\u0629. \u0628\u0639\u0636 \u0623\u0639\u0628\u0627\u0621 \u0627\u0644\u0639\u0645\u0644 \u0641\u064a \u062d\u062f\u0648\u062f 5% \u0645\u0646 CUDA \u0639\u0644\u0649 \u0623\u062c\u0647\u0632\u0629 \u0645\u0643\u0627\u0641\u0626\u0629.<br \/>\n3. <strong>\u0623\u0636\u0627\u0641 vLLM 0.7+ \u062f\u0639\u0645 ROCm \u0627\u0644\u0631\u0633\u0645\u064a.<\/strong> \u064a\u0645\u0643\u0646 \u0627\u0644\u0622\u0646 \u062a\u0634\u063a\u064a\u0644 \u0627\u0644\u062e\u0648\u0627\u062f\u0645 \u0627\u0644\u0627\u0633\u062a\u062f\u0644\u0627\u0644\u064a\u0629 \u0644\u0644\u0625\u0646\u062a\u0627\u062c \u0639\u0644\u0649 AMD \u0628\u062f\u0648\u0646 \u0634\u0648\u0643\u0627\u062a \u0623\u0648 \u062a\u0635\u062d\u064a\u062d\u0627\u062a.<\/p>\n<p>\u0645\u0627 \u0644\u0645 \u064a\u062a\u063a\u064a\u0631: \u0644\u0627 \u062a\u0632\u0627\u0644 \u0627\u0644\u062a\u0639\u0644\u064a\u0645\u0627\u062a \u0627\u0644\u0628\u0631\u0645\u062c\u064a\u0629 \u0627\u0644\u0628\u062d\u062b\u064a\u0629 \u0627\u0644\u0645\u062a\u0637\u0648\u0631\u0629 \u062a\u0639\u062a\u0645\u062f \u0639\u0644\u0649 CUDA \u0623\u0648\u0644\u0627\u064b. \u062a\u064f\u0634\u062d\u0646 \u0627\u0644\u0623\u0648\u0631\u0627\u0642 \u0627\u0644\u062c\u062f\u064a\u062f\u0629 \u0645\u0639 <code>\u062a\u062b\u0628\u064a\u062a \u0646\u0642\u0637\u0629 \u062a\u062b\u0628\u064a\u062a -r requirements.txt<\/code> \u0627\u0644\u062a\u064a \u062a\u0633\u062d\u0628 <code>\u062a\u0631\u064a\u062a\u0648\u0646<\/code>, <code>\u0641\u0644\u0627\u0634-\u0622\u062a\u0646<\/code>, \u0623\u0648 <code>\u0625\u0643\u0633\u0641\u0648\u0631\u0645\u0631\u0632<\/code> - \u0648\u0643\u0644\u0647\u0627 \u0644\u0627 \u062a\u0632\u0627\u0644 \u062a\u062d\u062a\u0627\u062c \u0625\u0644\u0649 \u0646\u0642\u0644 \u0623\u0648 \u0625\u0646\u0634\u0627\u0621\u0627\u062a ROCm \u0645\u062c\u062a\u0645\u0639\u064a\u0629.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"AI_workload_comparison_RX_7900_XTX_vs_RTX_4090_both_24_GB\"><\/span>\u0645\u0642\u0627\u0631\u0646\u0629 \u0639\u0628\u0621 \u0627\u0644\u0639\u0645\u0644 \u0628\u0627\u0644\u0630\u0643\u0627\u0621 \u0627\u0644\u0627\u0635\u0637\u0646\u0627\u0639\u064a (RX 7900 XTX \u0645\u0642\u0627\u0628\u0644 RTX 4090\u060c \u0643\u0644\u0627\u0647\u0645\u0627 \u0628\u0633\u0639\u0629 24 \u062c\u064a\u062c\u0627\u0628\u0627\u064a\u062a)<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<table class=\"convly-vs\">\n<thead>\n<tr>\n<th>\u0627\u0644\u062d\u0645\u0644 \u0627\u0644\u0648\u0638\u064a\u0641\u064a<\/th>\n<th>RX 7900 XTX (RX 7900 XTX) (ROCm 6.3)<\/th>\n<th>RTX 4090 (CUDA 12.6)<\/th>\n<th>\u0394<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>\u0646\u0645\u0627\u0630\u062c \u0644\u0627\u0645\u0627 3 \u0628\u0633\u0639\u0629 8 \u0645\u0644\u064a\u0627\u0631 \u0645\u0639\u0644\u0645\u0629\u060c \u0643\u0645\u064a\u0629 \u0627\u0644\u062a\u0643\u0645\u064a\u0645 Q4 (\u0639\u062f\u062f \u0627\u0644\u062a\u0648\u0643\u0646\u0627\u062a\/\u0627\u0644\u062b\u0627\u0646\u064a\u0629)<\/td>\n<td>98<\/td>\n<td>122<\/td>\n<td>CUDA+24%<\/td>\n<\/tr>\n<tr>\n<td>\u0644\u0627\u0645\u0627 3 70B 70B Q4 (t\/s)<\/td>\n<td>13.6<\/td>\n<td>16.4<\/td>\n<td>CUDA +21% +21%<\/td>\n<\/tr>\n<tr>\n<td>Qwen 2.5 32B 32B Q5 (t\/s)<\/td>\n<td>32<\/td>\n<td>40<\/td>\n<td>CUDA+25%<\/td>\n<\/tr>\n<tr>\n<td>SDXL \u0628\u062f\u0642\u0629 1024\u00d71024 (\u062a\u0643\u0631\u0627\u0631\/\u062b\u0627\u0646\u064a\u0629)<\/td>\n<td>14.2<\/td>\n<td>18.3<\/td>\n<td>CUDA +29% +29%<\/td>\n<\/tr>\n<tr>\n<td>FLUX.1 dev (\u062a\u0643\u0631\u0627\u0631\/\u062b\u0627\u0646\u064a\u0629)<\/td>\n<td>1.6<\/td>\n<td>2.2<\/td>\n<td>CUDA +38% +38%<\/td>\n<\/tr>\n<tr>\n<td>\u0644\u0627\u0645\u0627 3 8 \u0628 8 \u0628 \u0644\u0648\u0631\u0627 (1 \u062d\u0642\u0628\u0629 \u0632\u0645\u0646\u064a\u0629)<\/td>\n<td>2 \u0633\u0627\u0639\u0629 \u064832 \u062f\u0642\u064a\u0642\u0629<\/td>\n<td>1 \u0633\u0627\u0639\u0629 \u064851 \u062f\u0642\u064a\u0642\u0629<\/td>\n<td>CUDA +37% +37%<\/td>\n<\/tr>\n<tr>\n<td>\u0627\u0644\u0636\u0628\u0637 \u0627\u0644\u062f\u0642\u064a\u0642 \u0644 BERT (1 \u062d\u0642\u0628\u0629 \u0632\u0645\u0646\u064a\u0629)<\/td>\n<td>\u0627\u0644\u0623\u0639\u0645\u0627\u0644<\/td>\n<td>\u0627\u0644\u0623\u0639\u0645\u0627\u0644<\/td>\n<td>~25% \u0623\u0628\u0637\u0623<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u0627\u0644\u0646\u0645\u0637 \u0627\u0644\u0645\u062a\u0643\u0631\u0631 \u0647\u0648: <strong>\u0627\u0644\u0627\u0633\u062a\u062f\u0644\u0627\u0644 \u0623\u0642\u0631\u0628\u060c \u0648\u0627\u0644\u062a\u062f\u0631\u064a\u0628 \u0648\u062a\u0648\u0644\u064a\u062f \u0627\u0644\u0635\u0648\u0631 \u0644\u0635\u0627\u0644\u062d CUDA \u0623\u0643\u062b\u0631.<\/strong> \u0647\u0630\u0627 \u0623\u0645\u0631 \u0645\u0646\u0637\u0642\u064a - \u064a\u0647\u064a\u0645\u0646 \u0639\u0631\u0636 \u0627\u0644\u0646\u0637\u0627\u0642 \u0627\u0644\u062a\u0631\u062f\u062f\u064a \u0644\u0644\u0630\u0627\u0643\u0631\u0629 \u0639\u0644\u0649 \u0627\u0644\u0627\u0633\u062a\u062f\u0644\u0627\u0644 (\u062d\u064a\u062b \u062a\u062a\u0634\u0627\u0628\u0647 \u0627\u0644\u0628\u0637\u0627\u0642\u062a\u0627\u0646) \u0628\u064a\u0646\u0645\u0627 \u064a\u0639\u062a\u0645\u062f \u0627\u0644\u062a\u062f\u0631\u064a\u0628 \u0648\u062a\u0648\u0644\u064a\u062f \u0627\u0644\u0635\u0648\u0631 \u0639\u0644\u0649 FlashAttention 2.5 \u0648\u0627\u0644\u062a\u062d\u0633\u064a\u0646\u0627\u062a \u0627\u0644\u0623\u062e\u0631\u0649 \u0627\u0644\u062e\u0627\u0635\u0629 \u0628\u0640 CUDA \u0627\u0644\u062a\u064a \u0644\u0645 \u062a\u062a\u0648\u0627\u0641\u0642 \u0645\u0639 ROCm \u0628\u0634\u0643\u0644 \u0643\u0627\u0645\u0644.<\/p>\n<h2 data-deepen=\"dc-2026\"><span class=\"ez-toc-section\" id=\"The_data-center_picture_MI300X_MI355X_vs_H100_B200\"><\/span>\u0646\u0638\u0631\u0629 \u0639\u0627\u0645\u0629 \u0639\u0644\u0649 \u0645\u0631\u0627\u0643\u0632 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a: MI300X \/ MI355X \u0645\u0642\u0627\u0628\u0644 H100 \/ B200<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u062a\u0631\u0643\u0632 \u0645\u0639\u0638\u0645 \u0627\u0644\u0646\u0642\u0627\u0634\u0627\u062a \u062d\u0648\u0644 \u201cROCm \u0645\u0642\u0627\u0628\u0644 CUDA\u201d \u0639\u0644\u0649 \u0628\u0637\u0627\u0642\u0627\u062a \u0627\u0644\u0631\u0633\u0648\u0645\u0627\u062a \u0627\u0644\u0645\u062e\u0635\u0635\u0629 \u0644\u0644\u0645\u0633\u062a\u0647\u0644\u0643\u064a\u0646\u060c \u0644\u0643\u0646 \u0627\u0644\u0641\u062c\u0648\u0629 \u062a\u0642\u0644\u0635\u062a \u0628\u0623\u0633\u0631\u0639 \u0648\u062a\u064a\u0631\u0629 \u0641\u064a \u0627\u0644\u0645\u062c\u0627\u0644 \u0627\u0644\u0630\u064a \u062a\u0646\u0627\u0641\u0633 \u0641\u064a\u0647 AMD \u0628\u0623\u0634\u062f \u0642\u0648\u0629 \u2014 \u0645\u0631\u0627\u0643\u0632 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a. Instinct \u0645\u0646 AMD <strong>MI300X<\/strong> \u0648\u0627\u0644\u0623\u062d\u062f\u062b <strong>MI355X<\/strong> \u0647\u064a \u062a\u0644\u0643 \u0627\u0644\u0631\u0642\u0627\u0626\u0642 \u0627\u0644\u062a\u064a \u062f\u0641\u0639\u062a \u0627\u0644\u062d\u0648\u0627\u0631 \u0625\u0644\u0649 \u0627\u062a\u062e\u0627\u0630 \u0645\u0646\u062d\u0649 \u062c\u062f\u064a\u062f.<\/p>\n<p>\u0639\u0646\u062f <strong>MLPerf Inference 6.0<\/strong> (\u0627\u0644\u0646\u062a\u0627\u0626\u062c \u0646\u064f\u0634\u0631\u062a \u0641\u064a 1 \u0623\u0628\u0631\u064a\u0644 2026)\u060c \u062d\u0642\u0642 \u0645\u0639\u0627\u0644\u062c MI355X \u0623\u0641\u0636\u0644 \u0623\u062f\u0627\u0621 \u0639\u0644\u0649 \u0627\u0644\u0625\u0637\u0644\u0627\u0642 \u0644\u0634\u0631\u0643\u0629 AMD \u2014 \u062d\u064a\u062b \u0627\u0642\u062a\u0631\u0628 \u0628\u0641\u0627\u0631\u0642 \u0646\u0642\u0627\u0637 \u0645\u0626\u0648\u064a\u0629 \u0645\u0646 \u062e\u0627\u0646\u0629 \u0648\u0627\u062d\u062f\u0629 \u0645\u0646 \u0623\u062f\u0627\u0621 \u0645\u0639\u0627\u0644\u062c B200 \u0645\u0646 Nvidia \u0641\u064a \u0623\u062d\u0645\u0627\u0644 \u0639\u0645\u0644 \u0627\u0644\u0627\u0633\u062a\u062f\u0644\u0627\u0644 \u0639\u0644\u0649 \u0627\u0644\u062e\u0648\u0627\u062f\u0645. \u0623\u0645\u0627 \u0628\u0627\u0644\u0646\u0633\u0628\u0629 \u0644\u0644\u0627\u0633\u062a\u062f\u0644\u0627\u0644 \u0627\u0644\u0642\u064a\u0627\u0633\u064a \u0644\u0646\u0645\u0627\u0630\u062c \u0627\u0644\u0644\u063a\u0629 \u0627\u0644\u0643\u0628\u064a\u0631\u0629 (LLM) \u0639\u0644\u0649 PyTorch \u0648vLLM\u060c \u0641\u0625\u0646 \u0645\u0639\u062f\u0644 ROCm \u0639\u0644\u0649 \u0627\u0644\u0623\u062c\u0647\u0632\u0629 \u0645\u0646 \u0641\u0626\u0629 MI300X \u064a\u0635\u0644 \u0627\u0644\u0622\u0646 \u0625\u0644\u0649 \u0645\u0627 \u064a\u0642\u0627\u0631\u0628 <strong>90\u201395% \u0645\u0646 \u0645\u0639\u062f\u0644 \u0625\u0646\u062a\u0627\u062c H100<\/strong>. \u0648\u0628\u0634\u0643\u0644 \u0639\u0627\u0645\u060c \u0627\u0646\u062e\u0641\u0636 \u0645\u062a\u0648\u0633\u0637 \u0641\u062c\u0648\u0629 \u0627\u0644\u0627\u0633\u062a\u062f\u0644\u0627\u0644 \u0625\u0644\u0649 \u062d\u0648\u0627\u0644\u064a 20%\u060c \u0648\u0647\u0648 \u0623\u0636\u064a\u0642 \u0645\u0633\u062a\u0648\u0649 \u0633\u064f\u062c\u0644 \u0639\u0644\u0649 \u0627\u0644\u0625\u0637\u0644\u0627\u0642.<\/p>\n<p>\u0647\u0646\u0627\u0643 \u0639\u0627\u0645\u0644\u0627\u0646 \u064a\u0636\u0645\u0646\u0627\u0646 \u0628\u0642\u0627\u0621 CUDA \u0641\u064a \u0627\u0644\u0635\u062f\u0627\u0631\u0629 \u0641\u064a \u0627\u0644\u0641\u0626\u0629 \u0627\u0644\u0631\u0627\u0642\u064a\u0629:<\/p>\n<ul>\n<li><strong>\u0644\u0627 \u062a\u0632\u0627\u0644 \u0634\u0631\u0643\u0629 \u00ab\u0625\u064a\u0646\u0641\u064a\u062f\u064a\u0627\u00bb \u0647\u064a \u0627\u0644\u0645\u0641\u0636\u0644\u0629 \u0641\u064a \u0645\u062c\u0627\u0644 \u0627\u0644\u062a\u062f\u0631\u064a\u0628.<\/strong> \u062a\u062a\u0633\u0639 \u0627\u0644\u0641\u062c\u0648\u0629 \u0641\u064a \u0639\u0645\u0644\u064a\u0627\u062a \u0627\u0644\u062a\u062f\u0631\u064a\u0628 \u0648\u0627\u0633\u0639\u0629 \u0627\u0644\u0646\u0637\u0627\u0642\u060c \u062d\u064a\u062b \u062a\u0638\u0644 \u0623\u062f\u0648\u0627\u062a CUDA \u0627\u0644\u0645\u062a\u0637\u0648\u0631\u0629 \u0627\u0644\u0645\u062e\u0635\u0635\u0629 \u0644\u0644\u0639\u0645\u0644 \u0645\u0639 \u0648\u062d\u062f\u0627\u062a \u0645\u0639\u0627\u0644\u062c\u0629 \u0627\u0644\u0631\u0633\u0648\u0645\u0627\u062a \u0627\u0644\u0645\u062a\u0639\u062f\u062f\u0629 (NCCL\u060c Transformer Engine\u060c \u0648\u0635\u0641\u0627\u062a FP8) \u0623\u0643\u062b\u0631 \u0633\u0644\u0627\u0633\u0629 \u0645\u0646 \u0646\u0638\u064a\u0631\u0627\u062a\u0647\u0627 \u0641\u064a ROCm.<\/li>\n<li><strong>\u0627\u0644\u0645\u0643\u062a\u0628\u0627\u062a \u0627\u0644\u062e\u0627\u0635\u0629 \u0628\u0640 CUDA.<\/strong> \u0644\u0627 \u062a\u0648\u062c\u062f \u062d\u062a\u0649 \u0627\u0644\u0622\u0646 \u0646\u0638\u0627\u0626\u0631 \u0643\u0627\u0645\u0644\u0629 \u0644\u0640 ROCm \u0644\u0623\u062d\u0645\u0627\u0644 \u0627\u0644\u0639\u0645\u0644 \u0627\u0644\u0645\u0628\u0646\u064a\u0629 \u0639\u0644\u0649 TensorRT-LLM \u0623\u0648 FlashAttention 3\u060c \u0644\u0630\u0627 \u0641\u0625\u0646 \u0623\u064a \u0634\u064a\u0621 \u0645\u0631\u062a\u0628\u0637 \u0628\u0647\u0630\u0647 \u0627\u0644\u0645\u062c\u0645\u0648\u0639\u0627\u062a \u064a\u062a\u0637\u0644\u0628 \u062c\u0647\u062f\u064b\u0627 \u0625\u0636\u0627\u0641\u064a\u064b\u0627 \u0639\u0646\u062f \u0646\u0642\u0644\u0647\u0627 \u0625\u0644\u0649 \u0645\u0646\u0635\u0629 AMD.<\/li>\n<\/ul>\n<p>\u0627\u0644\u062c\u0627\u0646\u0628 \u0627\u0644\u0625\u064a\u062c\u0627\u0628\u064a: \u0633\u062a\u0648\u0641\u0631 \u0643\u0644 \u0645\u0646 PyTorch \u0648vLLM \u0648SGLang \u062f\u0639\u0645\u064b\u0627 \u0631\u0633\u0645\u064a\u064b\u0627 \u0644\u0640 ROCm \u0641\u064a \u0639\u0627\u0645 2026\u060c \u0645\u0645\u0627 \u064a\u0639\u0646\u064a \u0623\u0646 \u0645\u0633\u0627\u0631\u0627\u062a \u0627\u0644\u0627\u0633\u062a\u062f\u0644\u0627\u0644 \u0627\u0644\u0623\u0643\u062b\u0631 \u0634\u064a\u0648\u0639\u064b\u0627 \u0633\u062a\u0639\u0645\u0644 \u0641\u0648\u0631\u064b\u0627 \u062f\u0648\u0646 \u0627\u0644\u062d\u0627\u062c\u0629 \u0625\u0644\u0649 \u0625\u0639\u062f\u0627\u062f\u0627\u062a \u0625\u0636\u0627\u0641\u064a\u0629. \u0627\u0644\u0645\u0644\u062e\u0635 \u0627\u0644\u0635\u0631\u064a\u062d \u0644\u0645\u0634\u062a\u0631\u064a \u0645\u0631\u0627\u0643\u0632 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a \u0647\u0648 \u0646\u0641\u0633\u0647 \u0628\u0627\u0644\u0646\u0633\u0628\u0629 \u0644\u0645\u0635\u0646\u0639\u064a \u0623\u062c\u0647\u0632\u0629 \u0627\u0644\u0643\u0645\u0628\u064a\u0648\u062a\u0631 \u0627\u0644\u0645\u0643\u062a\u0628\u064a\u0629 \u2014 \u062a\u0638\u0644 Nvidia \u0647\u064a \u0627\u0644\u062e\u064a\u0627\u0631 \u0627\u0644\u0627\u0641\u062a\u0631\u0627\u0636\u064a\u060c \u0644\u0643\u0646 AMD \u0623\u0635\u0628\u062d\u062a \u0627\u0644\u0622\u0646 \u062e\u064a\u0627\u0631\u064b\u0627 \u0645\u0648\u062b\u0648\u0642\u064b\u0627 \u0628\u0647 \u0628\u062f\u0644\u0627\u064b \u0645\u0646 \u0623\u0646 \u062a\u0643\u0648\u0646 \u0645\u062c\u0631\u062f \u062d\u0644 \u0648\u0633\u0637.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Where_ROCm_wins\"><\/span>\u062d\u064a\u062b \u062a\u0641\u0648\u0632 ROCm<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u0647\u0646\u0627\u0643 \u0623\u0645\u0627\u0643\u0646 \u062a\u062a\u0641\u0648\u0642 \u0641\u064a\u0647\u0627 AMD \u0639\u0644\u0649 Nvidia \u0641\u064a \u0639\u0627\u0645 2026:<\/p>\n<ul>\n<li><strong>\u062a\u062c\u0631\u0628\u0629 Linux \u0627\u0644\u0623\u0635\u0644\u064a\u0629.<\/strong> \u062a\u0645 \u062a\u0635\u0645\u064a\u0645 ROCm \u0644\u0646\u0638\u0627\u0645 \u0644\u064a\u0646\u0643\u0633 \u0623\u0648\u0644\u0627\u064b. CUDA \u0639\u0644\u0649 \u0644\u064a\u0646\u0643\u0633 \u062c\u064a\u062f \u0648\u0644\u0643\u0646 \u0628\u0631\u0627\u0645\u062c \u062a\u0634\u063a\u064a\u0644 Nvidia \u062a\u0633\u0628\u0628 \u0623\u062d\u064a\u0627\u0646\u064b\u0627 \u0645\u0634\u0627\u0643\u0644 \u0641\u064a \u0627\u0644\u0646\u0648\u0627\u0629.<\/li>\n<li><strong>\u0631\u0648\u062d \u0627\u0644\u0645\u0635\u062f\u0631 \u0627\u0644\u0645\u0641\u062a\u0648\u062d.<\/strong> \u0645\u0643\u062f\u0633 ROCm \u0627\u0644\u0643\u0627\u0645\u0644 \u0645\u0641\u062a\u0648\u062d. CUDA \u0645\u063a\u0644\u0642\u0629. \u0645\u0647\u0645 \u0625\u0630\u0627 \u0643\u0646\u062a \u062a\u0647\u062a\u0645.<\/li>\n<li><strong>\u0627\u0644\u0633\u0639\u0631 \u0644\u0643\u0644 VRAM \u0644\u0644\u0627\u0633\u062a\u062f\u0644\u0627\u0644.<\/strong> RX 7900 XTX at $900 new with 24 GB beats RTX 5070 Ti ($749, 16 GB) and approaches a used RTX 4090 ($1,300, 24 GB) on price.<\/li>\n<li><strong>\u0643\u0641\u0627\u0621\u0629 \u0627\u0644\u0637\u0627\u0642\u0629<\/strong> \u0641\u064a \u0628\u0639\u0636 \u0623\u0639\u0628\u0627\u0621 \u0627\u0644\u0639\u0645\u0644 (RX 7900 XTX TDP 355 \u0648\u0627\u0637 \u0645\u0642\u0627\u0628\u0644 4090 450 \u0648\u0627\u0637).<\/li>\n<\/ul>\n<h2><span class=\"ez-toc-section\" id=\"Where_CUDA_wins_still\"><\/span>\u062d\u064a\u062b \u062a\u0641\u0648\u0632 CUDA (\u0644\u0627 \u062a\u0632\u0627\u0644)<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<ul>\n<li><strong>\u0627\u062a\u0633\u0627\u0639 \u0645\u0646\u0638\u0648\u0645\u0629 \u0627\u0644\u0628\u0631\u0645\u062c\u064a\u0627\u062a.<\/strong> TensorRT-LLM \u0648 NVIDIA NIM \u0648 NeMo \u0648 Megatron \u0648 FlashAttention \u0648 xformers - CUDA \u0641\u0642\u0637.<\/li>\n<li><strong>\u062a\u0648\u0627\u0641\u0631 \u0627\u0644\u0633\u062d\u0627\u0628\u0629.<\/strong> \u062a\u0639\u0645\u0644 \u0643\u0644 \u0645\u0646 AWS \u0648GCP \u0648Azure \u0639\u0644\u0649 \u062f\u0641\u0639 CUDA. \u0645\u062b\u064a\u0644\u0627\u062a AMD \u0645\u0648\u062c\u0648\u062f\u0629 \u0648\u0644\u0643\u0646\u0647\u0627 \u0645\u0646 \u0627\u0644\u062f\u0631\u062c\u0629 \u0627\u0644\u062b\u0627\u0646\u064a\u0629.<\/li>\n<li><strong>\u0648\u0642\u062a \u0627\u0644\u0628\u062d\u062b \u0625\u0644\u0649 \u0648\u0642\u062a \u0627\u0644\u062a\u0634\u063a\u064a\u0644.<\/strong> \u062a\u0639\u0645\u0644 \u0645\u0633\u062a\u0648\u062f\u0639\u0627\u062a GitHub \u0644\u0644\u0623\u0628\u062d\u0627\u062b \u0627\u0644\u062c\u062f\u064a\u062f\u0629 \u0641\u064a \u0627\u0644\u064a\u0648\u0645 \u0627\u0644\u0623\u0648\u0644 \u0645\u0639 CUDA. \u063a\u0627\u0644\u0628\u064b\u0627 \u0645\u0627 \u062a\u0646\u062a\u0638\u0631 ROCm \u0623\u0633\u0627\u0628\u064a\u0639.<\/li>\n<li><strong>\u0623\u062c\u0647\u0632\u0629 \u0639\u0627\u0644\u064a\u0629 \u0627\u0644\u0645\u0633\u062a\u0648\u0649.<\/strong> H100 \u0648H200 \u0648H200 \u0648B200 \u0644\u064a\u0633 \u0644\u0647\u0627 \u0645\u062b\u064a\u0644 \u0645\u0646 AMD \u0628\u0623\u0633\u0639\u0627\u0631 \u0627\u0644\u0645\u0633\u062a\u0647\u0644\u0643\u064a\u0646. \u0642\u0645\u0629 \u0627\u0644\u0645\u0643\u062f\u0633 \u0627\u0644\u0627\u0633\u062a\u0647\u0644\u0627\u0643\u064a: RX 7900 XTX \u0645\u0642\u0627\u0628\u0644 RTX 5090 \u0644\u064a\u0633\u062a \u0645\u0646\u0627\u0641\u0633\u0629.<\/li>\n<li><strong>\u0645\u0633\u0627\u062d\u0629 \u0633\u0637\u062d \u0627\u0644\u062d\u0634\u0631\u0629.<\/strong> \u064a\u0646\u062a\u062c \u0623\u062d\u064a\u0627\u0646\u064b\u0627 \u0639\u0646 \u0643\u0648\u062f ROCm + \u0643\u0648\u062f \u0646\u0632\u064a\u0641 \u0627\u0644\u062d\u0627\u0641\u0629 \u0623\u062e\u0637\u0627\u0621 \u0639\u062f\u062f\u064a\u0629 \u0635\u0627\u0645\u062a\u0629. \u0643\u0627\u0646 \u0644\u062f\u0649 CUDA \u0639\u0642\u062f \u0645\u0646 \u0627\u0644\u0632\u0645\u0646 \u0644\u0644\u062a\u062e\u0644\u0635 \u0645\u0646\u0647\u0627.<\/li>\n<\/ul>\n<h2><span class=\"ez-toc-section\" id=\"Pros_and_cons\"><\/span>\u0627\u0644\u0645\u0632\u0627\u064a\u0627 \u0648\u0627\u0644\u0639\u064a\u0648\u0628<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<div class=\"convly-procons\">\n<div class=\"pros\">\n<h4>AMD ROCm \u0641\u064a \u0639\u0627\u0645 2026<\/h4>\n<ul>\n<li>\u0642\u0627\u0628\u0644 \u0644\u0644\u0625\u0646\u062a\u0627\u062c \u0642\u0627\u0628\u0644 \u0644\u0644\u0627\u0633\u062a\u062f\u0644\u0627\u0644<\/li>\n<li>\u0643\u0648\u0645\u0629 \u0643\u0627\u0645\u0644\u0629 \u0645\u0641\u062a\u0648\u062d\u0629 \u0627\u0644\u0645\u0635\u062f\u0631 \u0648\u0645\u0641\u062a\u0648\u062d\u0629 \u0627\u0644\u0645\u0635\u062f\u0631<\/li>\n<li>\u0633\u0639\u0631 \u062b\u0627\u0628\u062a \u0644\u0643\u0644 VRAM<\/li>\n<li>\u064a\u0639\u0645\u0644 PyTorch + llama.cpp + vLLM \u062c\u0645\u064a\u0639\u064b\u0627<\/li>\n<\/ul>\n<\/div>\n<div class=\"cons\">\n<h4>\u062d\u062f\u0648\u062f AMD ROCm<\/h4>\n<ul>\n<li>10-25% \u0623\u0628\u0637\u0623 \u0645\u0646 CUDA \u0639\u0646\u062f \u0627\u0644\u062a\u0643\u0627\u0641\u0624<\/li>\n<li>\u0643\u0648\u062f \u0627\u0644\u0628\u062d\u062b \u0627\u0644\u062c\u062f\u064a\u062f \u064a\u062d\u062a\u0627\u062c \u0625\u0644\u0649 \u0646\u0642\u0644<\/li>\n<li>\u0644\u0627 \u062a\u0648\u062c\u062f \u0628\u0637\u0627\u0642\u0629 \u0627\u0633\u062a\u0647\u0644\u0627\u0643\u064a\u0629 \u0645\u062a\u0637\u0648\u0631\u0629 (\u0644\u0627 \u062a\u0648\u062c\u062f \u0628\u0637\u0627\u0642\u0629 AMD 5090 \u0645\u0643\u0627\u0641\u0626\u0629)<\/li>\n<li>\u0645\u062c\u062a\u0645\u0639 \u0623\u0635\u063a\u0631\u060c \u0639\u062f\u062f \u0623\u0642\u0644 \u0645\u0646 \u0627\u0644\u0645\u0631\u0634\u062f\u064a\u0646<\/li>\n<\/ul>\n<\/div>\n<\/div>\n<h2><span class=\"ez-toc-section\" id=\"Recommendation_by_user_type\"><\/span>\u0627\u0644\u062a\u0648\u0635\u064a\u0629 \u062d\u0633\u0628 \u0646\u0648\u0639 \u0627\u0644\u0645\u0633\u062a\u062e\u062f\u0645<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<ul>\n<li><strong>\u0623\u0646\u062a \u062a\u0628\u0646\u064a \u0627\u0633\u062a\u062f\u0644\u0627\u0644 \u0627\u0644\u0630\u0643\u0627\u0621 \u0627\u0644\u0627\u0635\u0637\u0646\u0627\u0639\u064a \u0644\u0644\u0625\u0646\u062a\u0627\u062c \u0648\u062a\u0647\u062a\u0645 \u0628\u0627\u0644\u062a\u0643\u0644\u0641\u0629:<\/strong> AMD \u062e\u064a\u0627\u0631 \u062d\u0642\u064a\u0642\u064a. \u064a\u0645\u0643\u0646 \u0623\u0646 \u064a\u0648\u0641\u0631 RX 7900 XTX \u0623\u0648 Instinct MI300X (\u0645\u0631\u0643\u0632 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a) \u0623\u0645\u0648\u0627\u0644\u0627\u064b \u0637\u0627\u0626\u0644\u0629.<\/li>\n<li><strong>\u0623\u0646\u062a \u062a\u062c\u0631\u064a \u0628\u062d\u062b\u0627\u064b \u0628\u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0646\u0645\u0627\u0630\u062c \u062c\u062f\u064a\u062f\u0629 \u062a\u0645\u0627\u0645\u0627\u064b:<\/strong> \u0627\u0628\u0642 \u0639\u0644\u0649 CUDA. \u0625\u0646 \u062a\u0648\u0641\u064a\u0631 $400 \u0644\u0627 \u064a\u0633\u062a\u062d\u0642 \u062e\u0633\u0627\u0631\u0629 \u0623\u0633\u0628\u0648\u0639 \u0623\u0648 \u0623\u0633\u0628\u0648\u0639\u064a\u0646 \u0645\u0646 \u062a\u0635\u062d\u064a\u062d \u0645\u0634\u0627\u0643\u0644 \u0627\u0644\u0628\u064a\u0626\u0629.<\/li>\n<li><strong>\u0623\u0646\u062a \u0647\u0627\u0648\u064d \u0644\u062a\u0639\u0644\u0645 \u0627\u0644\u0642\u0627\u0646\u0648\u0646 \u0627\u0644\u0645\u062d\u0644\u064a:<\/strong> \u0643\u0644\u0627\u0647\u0645\u0627 \u064a\u0639\u0645\u0644\u0627\u0646. \u0627\u062e\u062a\u0631 \u0627\u0644\u0633\u0639\u0631\/\u0630\u0627\u0643\u0631\u0629 \u0627\u0644\u0648\u0635\u0648\u0644 \u0627\u0644\u0639\u0634\u0648\u0627\u0626\u064a \u0623\u0648\u0644\u0627\u064b.<\/li>\n<li><strong>\u0623\u0646\u062a \u062a\u0642\u0648\u0645 \u0628\u0636\u0628\u0637\u0647\u0627 \u0628\u0627\u0646\u062a\u0638\u0627\u0645:<\/strong> CUDA. \u0644\u0627 \u062a\u0632\u0627\u0644 \u0627\u0644\u0641\u062c\u0648\u0629 \u0641\u064a \u062c\u0627\u0646\u0628 \u0627\u0644\u062a\u062f\u0631\u064a\u0628 \u0630\u0627\u062a \u0645\u063a\u0632\u0649 \u0641\u064a \u0639\u0627\u0645 2026.<\/li>\n<li><strong>\u0623\u0646\u062a \u0645\u062a\u0648\u0627\u0641\u0642 \u0641\u0644\u0633\u0641\u064a\u064b\u0627 \u0645\u0639 \u0627\u0644\u0645\u0635\u062f\u0631 \u0627\u0644\u0645\u0641\u062a\u0648\u062d:<\/strong> AMD. \u0625\u0646\u0647\u0627 \u0627\u0644\u0622\u0646 \u062c\u064a\u062f\u0629 \u0628\u0645\u0627 \u064a\u0643\u0641\u064a \u0644\u0644\u062a\u0635\u0648\u064a\u062a \u0628\u0645\u062d\u0641\u0638\u062a\u0643.<\/li>\n<\/ul>\n<p><!--ai-enriched--><\/p>\n<h2><span class=\"ez-toc-section\" id=\"The_cloud_angle_renting_ROCm_vs_CUDA_by_the_hour\"><\/span>\u0645\u0646\u0638\u0648\u0631 \u0627\u0644\u0633\u062d\u0627\u0628\u0629: \u0627\u0633\u062a\u0626\u062c\u0627\u0631 ROCm \u0645\u0642\u0627\u0628\u0644 CUDA \u0628\u0627\u0644\u0633\u0627\u0639\u0629<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u0634\u0631\u0627\u0621 \u0648\u062d\u062f\u0629 \u0645\u0639\u0627\u0644\u062c\u0629 \u0631\u0633\u0648\u0645\u0627\u062a (GPU) \u0644\u064a\u0633 \u0633\u0648\u0649 \u062e\u064a\u0627\u0631 \u0648\u0627\u062d\u062f \u0645\u0646 \u0628\u064a\u0646 \u062e\u064a\u0627\u0631\u0627\u062a \u0639\u062f\u064a\u062f\u0629. \u0641\u0625\u0630\u0627 \u0643\u0627\u0646 \u062d\u062c\u0645 \u0627\u0644\u0639\u0645\u0644 \u0627\u0644\u0630\u064a \u062a\u0642\u0648\u0645 \u0628\u0647 \u064a\u062a\u0633\u0645 \u0628\u0627\u0644\u062a\u0642\u0644\u0628\u0627\u062a\u060c \u0623\u0648 \u0643\u0646\u062a \u062a\u0631\u063a\u0628 \u0641\u0642\u0637 \u0641\u064a \u0627\u062e\u062a\u0628\u0627\u0631 ROCm \u0642\u0628\u0644 \u0627\u062a\u062e\u0627\u0630 \u0642\u0631\u0627\u0631 \u0646\u0647\u0627\u0626\u064a\u060c \u0641\u0642\u062f \u0623\u0635\u0628\u062d\u062a \u0623\u0633\u0639\u0627\u0631 \u062e\u062f\u0645\u0627\u062a \u0627\u0644\u0633\u062d\u0627\u0628\u0629 \u0627\u0644\u0642\u0627\u0626\u0645\u0629 \u0639\u0644\u0649 \u0648\u062d\u062f\u0627\u062a \u0645\u0639\u0627\u0644\u062c\u0629 \u0627\u0644\u0631\u0633\u0648\u0645\u0627\u062a (GPU) \u0628\u0647\u062f\u0648\u0621 \u0627\u0644\u0645\u062c\u0627\u0644 \u0627\u0644\u0630\u064a \u062a\u062a\u0645\u062a\u0639 \u0641\u064a\u0647 AMD \u0628\u0623\u0642\u0648\u0649 \u0645\u0648\u0642\u0641 \u0641\u064a \u0639\u0627\u0645 2026 \u2014 \u0644\u0623\u0646 \u0627\u0644\u0645\u0642\u0627\u0631\u0646\u0629 \u0647\u0646\u0627 \u062a\u062a\u0639\u0644\u0642 \u0628\u0627\u0644\u062a\u0643\u0644\u0641\u0629 \u0644\u0643\u0644 \u062a\u0648\u0643\u0646\u060c \u0648\u0644\u064a\u0633 \u0628\u0646\u0636\u062c \u0627\u0644\u0646\u0638\u0627\u0645 \u0627\u0644\u0628\u064a\u0626\u064a.<\/p>\n<p>\u0639\u0644\u0649 \u0645\u0633\u062a\u0648\u0649 \u0627\u0644\u0645\u0633\u062a\u0647\u0644\u0643\u060c \u062a\u062a\u0648\u0641\u0631 \u0643\u0644\u062a\u0627 \u0627\u0644\u0628\u0637\u0627\u0642\u062a\u064a\u0646 \u0628\u0623\u0633\u0639\u0627\u0631 \u0645\u0646\u062e\u0641\u0636\u0629 \u0648\u0628\u0643\u0645\u064a\u0627\u062a \u0648\u0641\u064a\u0631\u0629. \u0648\u0639\u0644\u0649 \u0645\u0646\u0635\u0627\u062a \u0627\u0644\u0633\u062d\u0627\u0628\u0629 \u0627\u0644\u062a\u062c\u0627\u0631\u064a\u0629 \u0645\u062b\u0644 Vast.ai\u060c \u064a\u0645\u0643\u0646\u0643 \u0627\u0633\u062a\u0626\u062c\u0627\u0631 <strong>\u0628\u0637\u0627\u0642\u0629 RX 7900 XTX \u0623\u0648 RTX 4090 \u0645\u0642\u0627\u0628\u0644 \u0645\u0627 \u064a\u0642\u0627\u0631\u0628 $0.30\u2013$0.55\/\u0633\u0627\u0639\u0629<\/strong>, \u060c \u0634\u0631\u064a\u0637\u0629 \u062a\u0648\u0641\u0631 \u0627\u0644\u0645\u062e\u0632\u0648\u0646. \u0648\u0628\u0647\u0630\u0647 \u0627\u0644\u0623\u0633\u0639\u0627\u0631\u060c \u0641\u0625\u0646 \u0627\u0644\u0639\u062c\u0632 \u0641\u064a \u0642\u062f\u0631\u0629 \u0627\u0644\u0627\u0633\u062a\u062f\u0644\u0627\u0644 \u0627\u0644\u0628\u0627\u0644\u063a \u062d\u0648\u0627\u0644\u064a 20% \u064a\u0643\u0627\u062f \u0644\u0627 \u064a\u064f\u0644\u0627\u062d\u0638\u061b \u0641\u0623\u0646\u062a \u062a\u062f\u0641\u0639 \u062b\u0645\u0646 \u0627\u0644\u0628\u0637\u0627\u0642\u0629 \u0627\u0644\u0623\u0628\u0637\u0623 \u0644\u0641\u062a\u0631\u0629 \u0623\u0637\u0648\u0644 \u0642\u0644\u064a\u0644\u0627\u064b \u062b\u0645 \u062a\u0645\u0636\u064a \u0642\u062f\u0645\u0627\u064b. \u0647\u0630\u0647 \u0647\u064a \u0627\u0644\u0637\u0631\u064a\u0642\u0629 \u0627\u0644\u0623\u0642\u0644 \u0645\u062e\u0627\u0637\u0631\u0629 \u0644\u062a\u062c\u0631\u0628\u0629 ROCm: \u0642\u0645 \u0628\u062a\u0634\u063a\u064a\u0644 \u0635\u0648\u0631\u0629 Docker \u0627\u0644\u062e\u0627\u0635\u0629 \u0628\u0640 ROCm\u060c \u0648\u0634\u063a\u0651\u0644 \u0646\u0645\u0648\u0630\u062c\u0643\u060c \u062b\u0645 \u0642\u0645 \u0628\u0625\u064a\u0642\u0627\u0641\u0647\u0627 \u062f\u0648\u0646 \u0634\u0631\u0627\u0621 \u0623\u064a \u0634\u064a\u0621.<\/p>\n<p>\u062a\u062a\u0633\u0645 \u0627\u0644\u0645\u0631\u062d\u0644\u0629 \u0627\u0644\u0645\u062a\u0639\u0644\u0642\u0629 \u0628\u0645\u0631\u0627\u0643\u0632 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a \u0628\u0623\u0646 \u0627\u0644\u062d\u0633\u0627\u0628\u0627\u062a \u0641\u064a\u0647\u0627 \u062a\u0635\u0628\u062d \u0645\u062b\u064a\u0631\u0629 \u0644\u0644\u0627\u0647\u062a\u0645\u0627\u0645. \u0648\u0641\u064a\u0645\u0627 \u064a\u0644\u064a \u0627\u0644\u0623\u0631\u0642\u0627\u0645 \u0627\u0644\u0631\u0626\u064a\u0633\u064a\u0629:<\/p>\n<table class=\"convly-vs\">\n<thead>\n<tr>\n<th>\u0627\u0644\u0646\u0638\u0627\u0645 \u0627\u0644\u0645\u062a\u0631\u064a<\/th>\n<th>AMD MI300X (192 \u062c\u064a\u062c\u0627\u0628\u0627\u064a\u062a)<\/th>\n<th>Nvidia H100 (80 \u062c\u064a\u062c\u0627\u0628\u0627\u064a\u062a)<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>\u0627\u0644\u0633\u0639\u0631 \u0627\u0644\u0623\u062f\u0646\u0649 \u0644\u0644\u0633\u062d\u0627\u0628\u0629<\/td>\n<td>~$1.85\u2013$1.99\/\u0633\u0627\u0639\u0629<\/td>\n<td>~$1.38\u2013$1.74\/\u0633\u0627\u0639\u0629<\/td>\n<\/tr>\n<tr>\n<td>\u0627\u0644\u062a\u0643\u0644\u0641\u0629 \u0644\u0643\u0644 \u063a\u064a\u063a\u0627\u0628\u0627\u064a\u062a \u0645\u0646 \u0630\u0627\u0643\u0631\u0629 VRAM<\/td>\n<td>~$0.010\/GB<\/td>\n<td>~$0.022\/GB<\/td>\n<\/tr>\n<tr>\n<td>\u0627\u0644\u0623\u0641\u0636\u0644 \u0641\u064a<\/td>\n<td>\u0627\u0644\u0646\u0645\u0627\u0630\u062c \u0627\u0644\u0643\u0628\u064a\u0631\u0629\u060c \u0623\u062d\u062c\u0627\u0645 \u0627\u0644\u062f\u064f\u0641\u0639\u0627\u062a \u0627\u0644\u0643\u0628\u064a\u0631\u0629<\/td>\n<td>\u0632\u0645\u0646 \u0627\u0646\u062a\u0642\u0627\u0644 \u0627\u0644\u062f\u064f\u0641\u0639\u0627\u062a \u0627\u0644\u0635\u063a\u064a\u0631\u0629\u060c \u0645\u062c\u0645\u0648\u0639\u0629 \u0648\u0627\u0633\u0639\u0629 \u0645\u0646 \u0627\u0644\u0623\u062f\u0648\u0627\u062a<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>\u0628\u0627\u0644\u0633\u0627\u0639\u0629\u060c \u0639\u0627\u062f\u0629\u064b \u0645\u0627 \u064a\u0643\u0648\u0646 \u0633\u0639\u0631 H100 \u0623\u0631\u062e\u0635. <strong>\u064a\u0628\u0644\u063a \u0633\u0639\u0631 \u062c\u0647\u0627\u0632 MI300X\u060c \u0644\u0643\u0644 \u063a\u064a\u063a\u0627\u0628\u0627\u064a\u062a \u0645\u0646 \u0627\u0644\u0630\u0627\u0643\u0631\u0629\u060c \u0646\u0635\u0641 \u0627\u0644\u0633\u0639\u0631 \u062a\u0642\u0631\u064a\u0628\u064b\u0627<\/strong> \u2014 \u0648\u0647\u0630\u0627 \u064a\u0642\u0644\u0628 \u0627\u0644\u0646\u062a\u064a\u062c\u0629 \u0628\u0627\u0644\u0646\u0633\u0628\u0629 \u0644\u0627\u0633\u062a\u062f\u0644\u0627\u0644 \u0646\u0645\u0627\u0630\u062c \u0627\u0644\u0644\u063a\u0629 \u0627\u0644\u0643\u0628\u064a\u0631\u0629 (LLM) \u0627\u0644\u0645\u0642\u064a\u062f\u0629 \u0628\u0627\u0644\u0630\u0627\u0643\u0631\u0629. \u0641\u062a\u0631\u0643\u064a\u0628 \u0646\u0645\u0648\u0630\u062c \u064a\u0632\u064a\u062f \u062d\u062c\u0645\u0647 \u0639\u0646 70 \u0645\u0644\u064a\u0627\u0631 \u0645\u0639\u0627\u062f\u0644\u0629 \u0639\u0644\u0649 \u0628\u0637\u0627\u0642\u0629 \u0648\u0627\u062d\u062f\u0629 \u0633\u0639\u0629 192 \u062c\u064a\u062c\u0627\u0628\u0627\u064a\u062a \u064a\u062a\u062c\u0646\u0628 \u0627\u0644\u0639\u0628\u0621 \u0627\u0644\u0625\u0636\u0627\u0641\u064a \u0627\u0644\u0645\u062a\u0631\u062a\u0628 \u0639\u0644\u0649 \u0627\u0644\u0645\u0639\u0627\u0644\u062c\u0629 \u0627\u0644\u0645\u062a\u0648\u0627\u0632\u064a\u0629 \u0644\u0644\u062a\u0646\u0633\u0648\u0631\u060c \u0628\u0627\u0644\u0625\u0636\u0627\u0641\u0629 \u0625\u0644\u0649 \u062a\u0643\u0644\u0641\u0629 \u0627\u0644\u0634\u0628\u0643\u0629 \u0627\u0644\u0646\u0627\u062a\u062c\u0629 \u0639\u0646 \u062a\u0642\u0633\u064a\u0645\u0647 \u0628\u064a\u0646 \u0628\u0637\u0627\u0642\u062a\u064a H100 \u0633\u0639\u0629 80 \u062c\u064a\u062c\u0627\u0628\u0627\u064a\u062a \u0644\u0643\u0644 \u0645\u0646\u0647\u0645\u0627. \u0641\u064a \u0627\u0644\u0627\u062e\u062a\u0628\u0627\u0631\u0627\u062a \u0627\u0644\u0645\u0639\u064a\u0627\u0631\u064a\u0629 \u0627\u0644\u0645\u0646\u0634\u0648\u0631\u0629\u060c \u062a\u0638\u0644 \u0628\u0637\u0627\u0642\u0629 MI300X \u0641\u064a \u0646\u0637\u0627\u0642 10\u2013151 TP3T \u0645\u0642\u0627\u0631\u0646\u0629\u064b \u0628\u0628\u0637\u0627\u0642\u0629 H100 \u0641\u064a \u0645\u0639\u0638\u0645 \u0623\u062d\u0645\u0627\u0644 \u0639\u0645\u0644 \u0627\u0644\u0645\u062d\u0648\u0644\u0627\u062a\u060c \u0648\u062a\u0646\u0627\u0641\u0633\u0647\u0627 \u0628\u0642\u0648\u0629 \u0639\u0646\u062f \u0623\u062d\u062c\u0627\u0645 \u0627\u0644\u062f\u064f\u0641\u0639\u0627\u062a \u0627\u0644\u0635\u063a\u064a\u0631\u0629\u060c \u0648\u062a\u062a\u0642\u062f\u0645 \u0639\u0644\u064a\u0647\u0627 \u0628\u0648\u0636\u0648\u062d \u0639\u0646\u062f \u0623\u062d\u062c\u0627\u0645 \u0627\u0644\u062f\u064f\u0641\u0639\u0627\u062a \u0627\u0644\u062a\u064a \u062a\u0628\u0644\u063a 256 \u0623\u0648 \u0623\u0643\u062b\u0631\u060c \u0623\u0648 \u0641\u064a \u0627\u0644\u0646\u0645\u0627\u0630\u062c \u0627\u0644\u0636\u062e\u0645\u0629 \u062c\u062f\u064b\u0651\u0627 \u0645\u062b\u0644 Llama 3 405B.<\/p>\n<p>\u0627\u0644\u0645\u0634\u0643\u0644\u0629 \u0647\u064a \u0646\u0641\u0633\u0647\u0627 \u0627\u0644\u062a\u064a \u062a\u0637\u0627\u0631\u062f \u0642\u0637\u0627\u0639 \u0623\u062c\u0647\u0632\u0629 \u0627\u0644\u0643\u0645\u0628\u064a\u0648\u062a\u0631 \u0627\u0644\u0645\u0643\u062a\u0628\u064a\u0629: \u0627\u0644\u062a\u0648\u0627\u0641\u0631 \u0648\u0627\u0644\u0623\u062f\u0648\u0627\u062a. \u0641\u0642\u062f\u0631\u0629 AMD \u0627\u0644\u0633\u062d\u0627\u0628\u064a\u0629 \u0645\u062d\u062f\u0648\u062f\u0629\u060c \u0648\u0645\u0631\u0643\u0632\u0629 \u0641\u064a \u0639\u062f\u062f \u0642\u0644\u064a\u0644 \u0645\u0646 \u0645\u0632\u0648\u062f\u064a \u0627\u0644\u062e\u062f\u0645\u0629\u060c \u0648\u0644\u0627 \u062a\u0632\u0627\u0644 \u062a\u062d\u0633\u064a\u0646\u0627\u062a \u0641\u0626\u0629 TensorRT-LLM \u0645\u0642\u062a\u0635\u0631\u0629 \u0639\u0644\u0649 CUDA \u0641\u0642\u0637. \u0648\u0644\u0643\u0646 \u0625\u0630\u0627 \u0643\u0646\u062a \u062a\u0642\u0648\u0645 \u0628\u062a\u0634\u063a\u064a\u0644 \u0646\u0645\u0648\u0630\u062c \u0636\u062e\u0645 \u0639\u0644\u0649 \u0646\u0637\u0627\u0642 \u0648\u0627\u0633\u0639 \u0648\u0643\u0627\u0646\u062a \u0645\u0646\u0635\u0629 \u0627\u0644\u062a\u0637\u0628\u064a\u0642\u0627\u062a \u0627\u0644\u062e\u0627\u0635\u0629 \u0628\u0643 \u062a\u0639\u0645\u0644 \u0639\u0644\u0649 vLLM \u0623\u0648 SGLang\u060c \u0641\u0625\u0646 \u0627\u0633\u062a\u0626\u062c\u0627\u0631 MI300X \u064a\u0645\u0643\u0646 \u0623\u0646 \u064a\u0642\u0644\u0644 \u0641\u0639\u0644\u064a\u064b\u0651\u0627 \u0645\u0646 \u0627\u0644\u062a\u0643\u0644\u0641\u0629 \u0644\u0643\u0644 \u0645\u0644\u064a\u0648\u0646 \u0631\u0645\u0632 \u2014 \u0648\u0647\u0648 \u0627\u0644\u0645\u062c\u0627\u0644 \u0627\u0644\u0648\u062d\u064a\u062f \u0627\u0644\u0630\u064a \u062a\u0638\u0647\u0631 \u0641\u064a\u0647 \u0645\u064a\u0632\u0629 \u0623\u062c\u0647\u0632\u0629 AMD \u0623\u062e\u064a\u0631\u064b\u0627 \u0641\u064a \u0641\u0627\u062a\u0648\u0631\u062a\u0643.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"FAQ\"><\/span>\u0627\u0644\u0623\u0633\u0626\u0644\u0629 \u0627\u0644\u0634\u0627\u0626\u0639\u0629<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p><!--geo-faq--><\/p>\n<h3>Is ROCm faster than CUDA?<\/h3>\n<p>No\u2014CUDA is still faster than ROCm across nearly every workload. On the RX 7900 XTX versus RTX 4090, CUDA leads by roughly 21\u201324% on Llama 3 inference, 29% on SDXL image generation, and 37% on LoRA training. Data-center ROCm on MI300X closes to about 90\u201395% of H100 throughput, but never overtakes it.<\/p>\n<h3>\u0647\u0644 \u064a\u0645\u0643\u0646\u0646\u064a \u0628\u0627\u0644\u0641\u0639\u0644 \u062a\u062f\u0631\u064a\u0628 LLMs \u0639\u0644\u0649 \u0648\u062d\u062f\u0627\u062a \u0645\u0639\u0627\u0644\u062c\u0629 \u0627\u0644\u0631\u0633\u0648\u0645\u0627\u062a AMD \u0641\u064a \u0639\u0627\u0645 2026\u061f<\/h3>\n<p>\u0646\u0639\u0645\u060c \u0641\u064a \u0627\u0644\u063a\u0627\u0644\u0628. \u064a\u062f\u0639\u0645 PyTorch + ROCm 6.3 \u0627\u0644\u0628\u0646\u0649 \u0627\u0644\u0631\u0626\u064a\u0633\u064a\u0629 (Llama \u0648Mistral \u0648Qwen) \u0644\u0636\u0628\u0637 LoRA \u0628\u062f\u0642\u0629 \u062e\u0627\u0631\u062c \u0627\u0644\u0635\u0646\u062f\u0648\u0642. \u064a\u0639\u0645\u0644 \u0627\u0644\u0636\u0628\u0637 \u0627\u0644\u062f\u0642\u064a\u0642 \u0627\u0644\u0643\u0627\u0645\u0644 \u0648\u0644\u0643\u0646 \u0623\u0628\u0637\u0623 \u0628\u0640 30-401 \u062a\u064a\u0631\u0627\u0628\u0627\u064a\u062a 3 \u062a\u064a\u0631\u0627\u0628\u0627\u064a\u062a \u0645\u0646 \u0645\u0643\u0627\u0641\u0626\u0627\u062a CUDA. \u0623\u064a\u0646 \u0633\u062a\u0635\u0637\u062f\u0645 \u0628\u0627\u0644\u062d\u0648\u0627\u062c\u0632: \u0627\u0644\u062a\u0642\u0646\u064a\u0627\u062a \u0627\u0644\u062a\u064a \u062a\u062a\u0637\u0644\u0628 \u0646\u0648\u0627\u0629 CUDA \u0645\u062e\u0635\u0635\u0629 (DeepSpeed ZeRO-Infinity\u060c \u0648\u0628\u0639\u0636 \u0645\u062a\u063a\u064a\u0631\u0627\u062a \u0627\u0644\u0627\u0646\u062a\u0628\u0627\u0647\u060c \u0648\u0628\u0639\u0636 \u0645\u0643\u062a\u0628\u0627\u062a \u0627\u0644\u062a\u0643\u0645\u064a\u0645) \u0642\u062f \u0644\u0627 \u062a\u062d\u062a\u0648\u064a \u0639\u0644\u0649 \u0645\u0643\u0627\u0641\u0626\u0627\u062a ROCm \u062d\u062a\u0649 \u0627\u0644\u0622\u0646.<\/p>\n<h3>\u0647\u0644 RX 7900 XTX \u0623\u0633\u0631\u0639 \u062d\u0642\u064b\u0627 \u0645\u0646 RTX 3090 \u0644\u0644\u0630\u0643\u0627\u0621 \u0627\u0644\u0627\u0635\u0637\u0646\u0627\u0639\u064a\u061f<\/h3>\n<p>\u0628\u0627\u0644\u0646\u0633\u0628\u0629 \u0644\u0644\u0631\u0645\u0632\u060c \u0641\u0625\u0646 7900 XTX \u0623\u0633\u0631\u0639 \u0628\u062d\u0648\u0627\u0644\u064a 5-81 \u062a\u064a\u0631\u0627\u0628\u0627\u064a\u062a \u0623\u0633\u0631\u0639 \u0645\u0646 3090 \u0641\u064a \u0623\u0639\u0628\u0627\u0621 \u0639\u0645\u0644 \u0627\u0644\u0627\u0633\u062a\u062f\u0644\u0627\u0644 (\u0643\u0644\u0627\u0647\u0645\u0627 24 \u062c\u064a\u062c\u0627\u0628\u0627\u064a\u062a). \u0628\u0627\u0644\u0646\u0633\u0628\u0629 \u0644\u0644\u0627\u0646\u062a\u0634\u0627\u0631 \u0627\u0644\u0645\u0633\u062a\u0642\u0631 \u0641\u0647\u0645\u0627 \u0645\u062a\u0639\u0627\u062f\u0644\u062a\u0627\u0646 \u062a\u0642\u0631\u064a\u0628\u064b\u0627. \u064a\u0641\u0648\u0632 7900 XTX \u0639\u0644\u0649 \u0643\u0641\u0627\u0621\u0629 \u0627\u0644\u0637\u0627\u0642\u0629 (355 \u0648\u0627\u0637 \u0645\u0642\u0627\u0628\u0644 350 \u0648\u0627\u0637 \u0645\u0639 \u0623\u062f\u0627\u0621 \u0623\u0641\u0636\u0644 \u0644\u0643\u0644 \u0648\u0627\u0637) \u0648\u0627\u0644\u0636\u0648\u0636\u0627\u0621. \u0644\u0643\u0646 3090 \u064a\u0641\u0648\u0632 \u0641\u064a \u0627\u0644\u0646\u0638\u0627\u0645 \u0627\u0644\u0628\u064a\u0626\u064a (CUDA)\u060c \u0648\u0627\u0644\u062a\u0633\u0639\u064a\u0631 \u0627\u0644\u0645\u0633\u062a\u062e\u062f\u0645 ($700 \u0645\u0642\u0627\u0628\u0644 $900 \u0627\u0644\u062c\u062f\u064a\u062f)\u060c \u0648\u062f\u0639\u0645 \u0627\u0644\u0645\u062c\u062a\u0645\u0639.<\/p>\n<h3>\u0647\u0644 \u0644\u062f\u0649 AMD \u0625\u062c\u0627\u0628\u0629 \u0639\u0644\u0649 RTX 5090\u061f<\/h3>\n<p>\u0644\u064a\u0633 \u0641\u064a \u0627\u0644\u0645\u0633\u062a\u0647\u0644\u0643. \u0644\u0627 \u064a\u0633\u062a\u0647\u062f\u0641 \u0627\u0644\u062c\u064a\u0644 \u0627\u0644\u0631\u0627\u0628\u0639 \u0645\u0646 AMD RDNA 4 \u0645\u0646 AMD (\u0627\u0644\u0645\u0639\u0644\u0646 \u0639\u0646\u0647 \u0644\u0639\u0627\u0645 2026 \u0648\u0644\u0643\u0646 \u062a\u0645 \u062a\u063a\u064a\u064a\u0631 \u0625\u0635\u062f\u0627\u0631 \u0627\u0644\u0645\u0633\u062a\u0647\u0644\u0643) \u0641\u0626\u0629 \u0630\u0627\u0643\u0631\u0629 \u0627\u0644\u0648\u0635\u0648\u0644 \u0627\u0644\u0639\u0634\u0648\u0627\u0626\u064a VRAM &gt;32 \u062c\u064a\u062c\u0627\u0628\u0627\u064a\u062a. \u0625\u0646 \u0645\u0637\u0631\u0642\u0629 \u0627\u0644\u0630\u0643\u0627\u0621 \u0627\u0644\u0627\u0635\u0637\u0646\u0627\u0639\u064a \u0627\u0644\u062e\u0627\u0635\u0629 \u0628\u0647\u0645 \u0647\u064a Instinct MI300X (192 \u062c\u064a\u062c\u0627\u0628\u0627\u064a\u062a) \u0648 MI400 \u0627\u0644\u0642\u0627\u062f\u0645\u0629\u060c \u0648\u0644\u0643\u0646 \u0647\u0630\u0647 \u0628\u0637\u0627\u0642\u0627\u062a \u0645\u0631\u0643\u0632 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a \u0627\u0644\u062a\u064a \u062a\u0628\u062f\u0623 \u0645\u0646 $15K+\u060c \u0648\u0644\u064a\u0633\u062a \u0628\u062f\u0627\u0626\u0644 \u0644\u0644\u0645\u0633\u062a\u0647\u0644\u0643\u064a\u0646.<\/p>\n<h3>\u0647\u0644 \u064a\u062c\u0628 \u0623\u0646 \u0623\u0646\u062a\u0642\u0644 \u0645\u0646 Nvidia \u0625\u0644\u0649 AMD \u0641\u064a 2026\u061f<\/h3>\n<p>\u0641\u0642\u0637 \u0625\u0630\u0627 \u0643\u0627\u0646 \u0644\u062f\u064a\u0643 \u0633\u0628\u0628 \u0645\u062d\u062f\u062f. \u0625\u0630\u0627 \u0643\u0627\u0646 \u0625\u0639\u062f\u0627\u062f Nvidia \u0627\u0644\u062d\u0627\u0644\u064a \u0627\u0644\u062e\u0627\u0635 \u0628\u0643 \u064a\u0639\u0645\u0644\u060c \u0641\u0625\u0646 \u0627\u0644\u062a\u0628\u062f\u064a\u0644 \u064a\u0643\u0644\u0641 2-4 \u0623\u0633\u0627\u0628\u064a\u0639 \u0645\u0646 \u0627\u0644\u062a\u0639\u0644\u0645 + \u062e\u0637\u0631 \u0627\u0644\u0648\u0642\u0648\u0639 \u0641\u064a \u0643\u0648\u062f \u063a\u064a\u0631 \u0645\u062a\u0648\u0627\u0641\u0642 \u0645\u0639 ROCm. \u0627\u0644\u062e\u0637\u0648\u0629 \u0627\u0644\u0635\u062d\u064a\u062d\u0629 \u0647\u064a <strong>\u0627\u0634\u062a\u0631\u0650 AMD \u0625\u0630\u0627 \u0643\u0627\u0646\u062a \u0648\u062d\u062f\u0629 \u0645\u0639\u0627\u0644\u062c\u0629 \u0627\u0644\u0631\u0633\u0648\u0645\u0627\u062a \u0627\u0644\u062a\u0627\u0644\u064a\u0629 \u0648\u0643\u0627\u0646\u062a \u062d\u0633\u0627\u0628\u0627\u062a \u0627\u0644\u0633\u0639\u0631\/\u0630\u0627\u0643\u0631\u0629 \u0627\u0644\u0648\u0635\u0648\u0644 \u0627\u0644\u0639\u0634\u0648\u0627\u0626\u064a (VRAM) \u0647\u064a \u0627\u0644\u0623\u0641\u0636\u0644 \u0644\u0623\u0639\u0628\u0627\u0621 \u0627\u0644\u0639\u0645\u0644 \u0644\u062f\u064a\u0643<\/strong> - \u0639\u062f\u0645 \u062a\u0631\u062d\u064a\u0644 \u0627\u0644\u0625\u0639\u062f\u0627\u062f\u0627\u062a \u0627\u0644\u062d\u0627\u0644\u064a\u0629.<\/p>\n<h3>\u0645\u0627\u0630\u0627 \u0639\u0646 Intel Arc \u0644\u0644\u0630\u0643\u0627\u0621 \u0627\u0644\u0627\u0635\u0637\u0646\u0627\u0639\u064a\u061f<\/h3>\n<p>\u064a\u0639\u0645\u0644 Intel Arc B580 (12 \u062c\u064a\u062c\u0627\u0628\u0627\u064a\u062a\u060c $249) \u0645\u0639 OpenVINO + IPEX-LLM \u0648\u064a\u0634\u063a\u0644 Llama 3 8B \u0628\u0633\u0631\u0639\u0629 38 \u062a\/\u062b\u0627\u0646\u064a\u0629 \u062a\u0642\u0631\u064a\u0628\u064b\u0627. \u0625\u0646\u0647 \u0628\u062f\u064a\u0644 \u0627\u0642\u062a\u0635\u0627\u062f\u064a \u0648\u0644\u0643\u0646 \u0627\u0644\u0646\u0638\u0627\u0645 \u0627\u0644\u0628\u064a\u0626\u064a \u0644\u0644\u0628\u0631\u0627\u0645\u062c \u0623\u0631\u0642 \u0645\u0646 ROCm. \u0645\u0641\u064a\u062f \u0644\u0644\u062a\u0631\u0642\u064a\u0639 \u0648\u0644\u064a\u0633 \u0644\u0644\u0639\u0645\u0644 \u0627\u0644\u062c\u0627\u062f. \u0627\u0646\u0638\u0631 <a href=\"\/ar\/best-budget-gpu-for-ai-under-500\/\">\u062f\u0644\u064a\u0644 \u0648\u062d\u062f\u0627\u062a \u0645\u0639\u0627\u0644\u062c\u0629 \u0627\u0644\u0631\u0633\u0648\u0645\u0627\u062a \u0627\u0644\u0645\u064f\u062e\u0635\u064e\u0651\u0635\u0629 \u0644\u0644\u0630\u0643\u0627\u0621 \u0627\u0644\u0627\u0635\u0637\u0646\u0627\u0639\u064a \u0636\u0645\u0646 \u0627\u0644\u0645\u064a\u0632\u0627\u0646\u064a\u0629<\/a> \u0644\u0644\u062d\u0635\u0648\u0644 \u0639\u0644\u0649 \u0627\u0644\u062a\u0641\u0627\u0635\u064a\u0644.<\/p>\n<h3>\u0647\u0644 \u0633\u064a\u0643\u0648\u0646 \u0646\u0638\u0627\u0645 ROCm \u062c\u0627\u0647\u0632\u064b\u0627 \u0644\u0644\u0625\u0646\u062a\u0627\u062c \u0641\u064a \u0639\u0627\u0645 2026\u061f<\/h3>\n<p>\u0628\u0627\u0644\u0646\u0633\u0628\u0629 \u0625\u0644\u0649 PyTorch \u0648\u0627\u0644\u0627\u0633\u062a\u062f\u0644\u0627\u0644 \u0628\u0627\u0633\u062a\u062e\u062f\u0627\u0645 vLLM\u060c \u0646\u0639\u0645. \u0648\u0635\u0644\u062a ROCm \u0625\u0644\u0649 \u0645\u0631\u062d\u0644\u0629 \u0627\u0644\u0625\u0646\u062a\u0627\u062c \u0644\u0647\u0630\u0647 \u0627\u0644\u0645\u062c\u0645\u0648\u0639\u0627\u062a \u0641\u064a \u0639\u0627\u0645 2026\u060c \u0645\u0639 \u062f\u0639\u0645 \u0631\u0633\u0645\u064a \u0645\u0646 PyTorch \u0648 vLLM \u0648 SGLang. \u0648\u0647\u064a \u0623\u0642\u0644 \u0646\u0636\u062c\u064b\u0627 \u0641\u064a\u0645\u0627 \u064a\u062a\u0639\u0644\u0642 \u0628\u0627\u0644\u062a\u062f\u0631\u064a\u0628 \u0639\u0644\u0649 \u0646\u0637\u0627\u0642 \u0648\u0627\u0633\u0639 \u0648\u0623\u064a \u0634\u064a\u0621 \u064a\u0639\u062a\u0645\u062f \u0639\u0644\u0649 \u0645\u0643\u062a\u0628\u0627\u062a \u062a\u0639\u0645\u0644 \u0628\u0646\u0638\u0627\u0645 CUDA \u0641\u0642\u0637 \u0645\u062b\u0644 TensorRT-LLM.<\/p>\n<h3>\u0645\u0627 \u0645\u062f\u0649 \u062a\u0642\u0627\u0631\u0628 ROCm \u0645\u0639 CUDA \u0641\u064a \u0639\u0645\u0644\u064a\u0627\u062a \u0627\u0644\u0627\u0633\u062a\u062f\u0644\u0627\u0644 \u0639\u0644\u0649 \u0627\u0644\u0646\u0645\u0627\u0630\u062c \u0627\u0644\u0644\u063a\u0648\u064a\u0629 \u0627\u0644\u0643\u0628\u064a\u0631\u0629 (LLM)\u061f<\/h3>\n<p>\u0639\u0644\u0649 \u0623\u062c\u0647\u0632\u0629 \u0645\u0631\u0627\u0643\u0632 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a (MI300X \/ MI355X)\u060c \u064a\u0635\u0644 ROCm \u0625\u0644\u0649 \u0645\u0627 \u064a\u0642\u0627\u0631\u0628 90\u201395% \u0645\u0646 \u0645\u0639\u062f\u0644 \u0646\u0642\u0644 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a \u0644\u0628\u0637\u0627\u0642\u0629 H100 \u0641\u064a \u0639\u0645\u0644\u064a\u0627\u062a \u0627\u0644\u0627\u0633\u062a\u062f\u0644\u0627\u0644 \u0627\u0644\u0642\u064a\u0627\u0633\u064a\u0629 \u0628\u0627\u0633\u062a\u062e\u062f\u0627\u0645 PyTorch\/vLLM\u060c \u0648\u0642\u062f \u062d\u0642\u0642 MI355X \u0623\u062f\u0627\u0621\u064b \u064a\u0642\u0627\u0631\u0628 \u0623\u062f\u0627\u0621 \u0628\u0637\u0627\u0642\u0629 B200 \u0645\u0646 Nvidia \u0628\u0646\u0633\u0628\u0629 \u0645\u0626\u0648\u064a\u0629 \u0645\u0646 \u062e\u0627\u0646\u0629 \u0648\u0627\u062d\u062f\u0629 \u0641\u064a \u0627\u062e\u062a\u0628\u0627\u0631 MLPerf Inference 6.0. \u0648\u064a\u0628\u0644\u063a \u0645\u062a\u0648\u0633\u0637 \u0627\u0644\u0641\u0627\u0631\u0642 \u0641\u064a \u0627\u0644\u0627\u0633\u062a\u062f\u0644\u0627\u0644 \u062d\u0627\u0644\u064a\u064b\u0627 \u062d\u0648\u0627\u0644\u064a 20% \u2014 \u0648\u0647\u0648 \u0627\u0644\u0623\u0635\u063a\u0631 \u0639\u0644\u0649 \u0627\u0644\u0625\u0637\u0644\u0627\u0642.<\/p>\n<h3>\u0647\u0644 \u064a\u0639\u0645\u0644 ROCm \u0645\u0639 Stable Diffusion\u061f<\/h3>\n<p>\u0646\u0639\u0645. \u064a\u0639\u0645\u0644 Stable Diffusion \u0639\u0644\u0649 ROCm \u0639\u0628\u0631 PyTorch\u060c \u0648\u062a\u062d\u062a\u0648\u064a \u0648\u0627\u062c\u0647\u0627\u062a \u0627\u0644\u0645\u0633\u062a\u062e\u062f\u0645 \u0627\u0644\u0634\u0627\u0626\u0639\u0629 (ComfyUI \u0648Automatic1111) \u0639\u0644\u0649 \u0645\u0633\u0627\u0631\u0627\u062a ROCm \u0641\u0639\u0627\u0644\u0629. \u062a\u0648\u0642\u0639 \u0623\u0646 \u062a\u0643\u0648\u0646 \u0639\u0645\u0644\u064a\u0629 \u0627\u0644\u0625\u0639\u062f\u0627\u062f \u0623\u0643\u062b\u0631 \u062a\u0639\u0642\u064a\u062f\u064b\u0627 \u0642\u0644\u064a\u0644\u0627\u064b \u0645\u0642\u0627\u0631\u0646\u0629 \u0628\u062a\u062c\u0631\u0628\u0629 CUDA \u0627\u0644\u062a\u064a \u062a\u0639\u0645\u0644 \u0628\u0645\u062c\u0631\u062f \u0627\u0644\u062a\u0648\u0635\u064a\u0644\u060c \u0644\u0643\u0646 \u0625\u0646\u0634\u0627\u0621 \u0627\u0644\u0635\u0648\u0631 \u0647\u0648 \u0623\u062d\u062f \u0623\u062d\u0645\u0627\u0644 \u0627\u0644\u0639\u0645\u0644 \u0627\u0644\u062a\u064a \u062a\u064f\u0639\u062f \u0641\u064a\u0647\u0627 AMD \u0627\u0644\u0623\u0643\u062b\u0631 \u0641\u0627\u0626\u062f\u0629\u064b \u0641\u064a \u0627\u0644\u0648\u0642\u062a \u0627\u0644\u062d\u0627\u0644\u064a.<\/p>\n<h3>\u0647\u0644 \u064a\u0639\u0645\u0644 \u0628\u0631\u0646\u0627\u0645\u062c ROCm \u0639\u0644\u0649 \u0646\u0638\u0627\u0645 \u0648\u064a\u0646\u062f\u0648\u0632 \u062d\u062a\u0649 \u0627\u0644\u0622\u0646\u060c \u0623\u0645 \u0645\u0627 \u0632\u0644\u062a \u0628\u062d\u0627\u062c\u0629 \u0625\u0644\u0649 \u0646\u0638\u0627\u0645 \u0644\u064a\u0646\u0643\u0633\u061f<\/h3>\n<p>\u0643\u0644\u0627 \u0627\u0644\u0623\u0645\u0631\u064a\u0646\u060c \u0645\u0639 \u0648\u062c\u0648\u062f \u0634\u0631\u0637. \u0627\u0639\u062a\u0628\u0627\u0631\u064b\u0627 \u0645\u0646 \u0639\u0627\u0645 2026\u060c \u0633\u062a\u0642\u0648\u0645 AMD \u0628\u062a\u0648\u0641\u064a\u0631 \u062d\u0632\u0645 PyTorch \u0627\u0644\u0631\u0633\u0645\u064a\u0629 \u0627\u0644\u0645\u0628\u0646\u064a\u0629 \u0639\u0644\u0649 ROCm 7.2.1 \u0648\u0627\u0644\u062a\u064a \u062a\u0639\u0645\u0644 \u0628\u0634\u0643\u0644 \u0623\u0635\u0644\u064a \u0639\u0644\u0649 \u0646\u0638\u0627\u0645 Windows \u0644\u0623\u062c\u0647\u0632\u0629 Radeon \u0648Ryzen \u0627\u0644\u0645\u062e\u0635\u0635\u0629 \u0644\u0644\u0630\u0643\u0627\u0621 \u0627\u0644\u0627\u0635\u0637\u0646\u0627\u0639\u064a\u060c \u0643\u0645\u0627 \u0623\u0646 ROCm-on-WSL2 \u0642\u062f \u0646\u0636\u062c\u062a \u0628\u0634\u0643\u0644 \u0643\u0628\u064a\u0631. \u0648\u0647\u0630\u0627 \u064a\u063a\u0637\u064a \u0645\u0639\u0638\u0645 \u0639\u0645\u0644\u064a\u0627\u062a \u0627\u0644\u0627\u0633\u062a\u062f\u0644\u0627\u0644 \u0627\u0644\u0645\u062d\u0644\u064a \u0648\u0627\u0644\u0636\u0628\u0637 \u0627\u0644\u062f\u0642\u064a\u0642. \u0644\u0643\u0646 <em>\u0643\u0627\u0645\u0644<\/em> ROCm stack \u2014 all the libraries, profilers, and lower-level tooling \u2014 is still Linux-first, and many community AI projects assume a Linux environment. For casual local LLM work, native Windows or WSL2 is now viable; for serious development or anything off the beaten path, a native Linux install remains the path of least resistance.<\/p>\n<h3>\u0647\u0644 \u0627\u0633\u062a\u0626\u062c\u0627\u0631 \u0648\u062d\u062f\u0629 \u0645\u0639\u0627\u0644\u062c\u0629 \u0631\u0633\u0648\u0645\u0627\u062a AMD \u0639\u0628\u0631 \u0627\u0644\u0633\u062d\u0627\u0628\u0629 \u0623\u0631\u062e\u0635 \u0623\u0645 \u0634\u0631\u0627\u0621 \u0628\u0637\u0627\u0642\u0629 7900 XTX\u061f<\/h3>\n<p>\u064a\u0639\u062a\u0645\u062f \u0630\u0644\u0643 \u0628\u0634\u0643\u0644 \u0634\u0628\u0647 \u0643\u0627\u0645\u0644 \u0639\u0644\u0649 \u0645\u0639\u062f\u0644 \u0627\u0644\u0627\u0633\u062a\u062e\u062f\u0627\u0645. \u0634\u0647\u062f\u062a \u0623\u0633\u0639\u0627\u0631 \u0628\u0637\u0627\u0642\u0627\u062a RX 7900 XTX \u0627\u0644\u062c\u062f\u064a\u062f\u0629 \u062a\u0642\u0644\u0628\u0627\u062a \u0641\u064a \u0639\u0627\u0645 2026 \u2014 \u062d\u064a\u062b \u062a\u0631\u0627\u0648\u062d\u062a \u0639\u0627\u062f\u0629\u064b \u0628\u064a\u0646 $800\u2013$1,000\u060c \u0639\u0644\u0649 \u0627\u0644\u0631\u063a\u0645 \u0645\u0646 \u0623\u0646 \u0627\u0644\u0623\u0633\u0639\u0627\u0631 \u0641\u064a \u0627\u0644\u0639\u0631\u0648\u0636 \u0627\u0644\u062a\u0631\u0648\u064a\u062c\u064a\u0629 \u0648\u0627\u0644\u0648\u062d\u062f\u0627\u062a \u0627\u0644\u0645\u0633\u062a\u0639\u0645\u0644\u0629 \u062a\u0646\u062e\u0641\u0636 \u0625\u0644\u0649 \u0645\u0627 \u062f\u0648\u0646 \u0630\u0644\u0643 \u2014 \u0641\u064a \u062d\u064a\u0646 \u0623\u0646 \u0627\u0633\u062a\u0626\u062c\u0627\u0631 \u0628\u0637\u0627\u0642\u0629 \u0627\u0633\u062a\u0647\u0644\u0627\u0643\u064a\u0629 \u0645\u0643\u0627\u0641\u0626\u0629 \u064a\u0643\u0644\u0641 \u062d\u0648\u0627\u0644\u064a $0.30\u2013$0.55\/\u0633\u0627\u0639\u0629. \u064a\u0642\u0639 \u0646\u0642\u0637\u0629 \u0627\u0644\u062a\u0639\u0627\u062f\u0644 \u0627\u0644\u062a\u0642\u0631\u064a\u0628\u064a\u0629 \u0641\u064a \u0645\u0643\u0627\u0646 \u0645\u0627 \u0628\u0627\u0644\u0642\u0631\u0628 \u0645\u0646 1,500\u20133,000 \u0633\u0627\u0639\u0629 \u0645\u0646 \u0627\u0644\u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0644\u0641\u0639\u0644\u064a\u060c \u0644\u0630\u0627 \u0625\u0630\u0627 \u0643\u0646\u062a \u0633\u062a\u0628\u0642\u064a \u0627\u0644\u0628\u0637\u0627\u0642\u0629 \u0645\u0634\u063a\u0648\u0644\u0629 \u0644\u0639\u062f\u0629 \u0623\u0634\u0647\u0631\u060c \u0641\u0625\u0646 \u0627\u0644\u0634\u0631\u0627\u0621 \u064a\u0643\u0648\u0646 \u0627\u0644\u062e\u064a\u0627\u0631 \u0627\u0644\u0623\u0641\u0636\u0644 \u0628\u0643\u062b\u064a\u0631 \u0648\u0633\u062a\u0635\u0628\u062d \u0645\u0627\u0644\u0643\u064b\u0627 \u0644\u0644\u062c\u0647\u0627\u0632. \u0625\u0630\u0627 \u0643\u0627\u0646 \u0627\u0633\u062a\u062e\u062f\u0627\u0645\u0643 \u0645\u062a\u0642\u0637\u0639\u064b\u0627 \u0623\u0648 \u062a\u062c\u0631\u064a\u0628\u064a\u064b\u0627 \u0623\u0648 \u0645\u062a\u0630\u0628\u0630\u0628\u064b\u0627\u060c \u0641\u0625\u0646 \u0627\u0644\u0627\u0633\u062a\u0626\u062c\u0627\u0631 \u064a\u062a\u062c\u0646\u0628 \u0627\u0644\u0646\u0641\u0642\u0627\u062a \u0627\u0644\u0631\u0623\u0633\u0645\u0627\u0644\u064a\u0629\u060c \u0648\u064a\u062a\u062c\u0646\u0628 \u0627\u0644\u0627\u0633\u062a\u0647\u0644\u0627\u0643\u060c \u0648\u064a\u0633\u0645\u062d \u0644\u0643 \u0628\u0627\u0644\u0627\u0646\u062a\u0642\u0627\u0644 \u0625\u0644\u0649 \u062c\u0647\u0627\u0632 MI300X \u0623\u0643\u0628\u0631 \u062d\u062c\u0645\u064b\u0627 \u0639\u0646\u062f\u0645\u0627 \u062a\u062a\u0637\u0644\u0628 \u0627\u0644\u0645\u0647\u0645\u0629 \u0641\u0639\u0644\u064a\u064b\u0627 \u0633\u0639\u0629 192 \u062c\u064a\u062c\u0627\u0628\u0627\u064a\u062a. \u0627\u0634\u062a\u0631\u0650 \u0627\u0644\u062c\u0647\u0627\u0632 \u0644\u0623\u062d\u0645\u0627\u0644 \u0627\u0644\u0639\u0645\u0644 \u0627\u0644\u0645\u062d\u0644\u064a\u0629 \u0627\u0644\u062b\u0627\u0628\u062a\u0629\u061b \u0648\u0627\u0633\u062a\u0623\u062c\u0631\u0647 \u0644\u0644\u062a\u062c\u0631\u0628\u0629 \u0623\u0648 \u0644\u0644\u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0644\u0645\u0643\u062b\u0641.<\/p>\n<h3>\u0645\u0627 \u0645\u062f\u0649 \u0635\u0639\u0648\u0628\u0629 \u0627\u0644\u0627\u0646\u062a\u0642\u0627\u0644 \u0645\u0646 CUDA \u0625\u0644\u0649 ROCm \u0641\u064a \u0627\u0644\u0648\u0627\u0642\u0639 \u0627\u0644\u0639\u0645\u0644\u064a\u061f<\/h3>\n<p>\u0628\u0627\u0644\u0646\u0633\u0628\u0629 \u0644\u0634\u0641\u0631\u0629 PyTorch \u0627\u0644\u0639\u0627\u062f\u064a\u0629\u060c \u0641\u0625\u0646 \u0627\u0644\u0623\u0645\u0631 \u0623\u0633\u0647\u0644 \u0628\u0643\u062b\u064a\u0631 \u0645\u0645\u0627 \u062a\u0648\u062d\u064a \u0628\u0647 \u0633\u0645\u0639\u062a\u0647\u0627 \u2014 \u062d\u064a\u062b \u062a\u0639\u0645\u0644 \u0645\u0639\u0638\u0645 \u0627\u0644\u0628\u0631\u0627\u0645\u062c \u0627\u0644\u0646\u0635\u064a\u0629 \u062f\u0648\u0646 \u0623\u064a \u062a\u0639\u062f\u064a\u0644 \u0644\u0623\u0646 \u0637\u0628\u0642\u0629 HIP \u0641\u064a ROCm \u062a\u062a\u0648\u0644\u0649 \u0645\u0639\u0627\u0644\u062c\u062a\u0647\u0627 <code>cuda<\/code> \u064a\u0642\u0648\u0645 \u0627\u0644\u062c\u0647\u0627\u0632 \u0628\u0627\u0633\u062a\u062f\u0639\u0627\u0621 \u0647\u0630\u0647 \u0627\u0644\u0623\u0648\u0627\u0645\u0631 \u0648\u062a\u0648\u062c\u064a\u0647\u0647\u0627 \u0625\u0644\u0649 \u0628\u0631\u0646\u0627\u0645\u062c \u062a\u0634\u063a\u064a\u0644 AMD\u061b \u0645\u0627 \u0639\u0644\u064a\u0643 \u0633\u0648\u0649 \u062a\u0628\u062f\u064a\u0644 \u0639\u062c\u0644\u0629 \u0627\u0644\u062a\u062b\u0628\u064a\u062a \u0648\u0627\u0644\u0627\u0646\u0637\u0644\u0627\u0642. \u062a\u0643\u0645\u0646 \u0627\u0644\u0635\u0639\u0648\u0628\u0629 \u0641\u064a \u0646\u0648\u0649 CUDA \u0627\u0644\u0645\u062e\u0635\u0635\u0629 \u0648\u0627\u0644\u0645\u0643\u062a\u0628\u0627\u062a \u0627\u0644\u0645\u062e\u0635\u0635\u0629 \u0644\u0640 CUDA \u0641\u0642\u0637. \u062a\u0642\u0648\u0645 \u0623\u062f\u0648\u0627\u062a HIPIFY \u0645\u0646 AMD (hipify-clang \u0648 hipify-perl) \u0628\u062a\u0631\u062c\u0645\u0629 \u0627\u0644\u062c\u0632\u0621 \u0627\u0644\u0623\u0643\u0628\u0631 \u0645\u0646 \u0643\u0648\u062f CUDA \u0627\u0644\u0645\u0643\u062a\u0648\u0628 \u064a\u062f\u0648\u064a\u064b\u0651\u0627 \u0625\u0644\u0649 HIP \u0622\u0644\u064a\u064b\u0651\u0627\u060c \u0648\u0644\u0643\u0646 \u062a\u0648\u0642\u0639 \u0627\u0644\u062d\u0627\u062c\u0629 \u0625\u0644\u0649 \u062a\u0646\u0638\u064a\u0641 \u064a\u062f\u0648\u064a \u0648\u0645\u0631\u0627\u062c\u0639\u0629 \u062f\u0642\u064a\u0642\u0629 \u0644\u0644\u062a\u0623\u0643\u062f \u0645\u0646 \u0635\u062d\u0629 \u0627\u0644\u0643\u0648\u062f \u0628\u0639\u062f \u0630\u0644\u0643. \u0642\u0645 \u0628\u0627\u0644\u0646\u0642\u0644 \u062a\u062f\u0631\u064a\u062c\u064a\u064b\u0651\u0627\u060c \u0648\u0627\u062e\u062a\u0628\u0631 \u0643\u0644 \u0642\u0633\u0645 \u0639\u0644\u0649 \u062d\u062f\u0629\u060c \u0648\u062e\u0635\u0635 \u0648\u0642\u062a\u064b\u0627 \u0643\u0627\u0641\u064a\u064b\u0651\u0627 \u0644\u0623\u064a \u062a\u0628\u0639\u064a\u0627\u062a \u062a\u0623\u062a\u064a \u0645\u0639 \u0646\u0648\u0627\u0629 \u062e\u0627\u0635\u0629 \u0628\u0647\u0627.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Bottom_line\"><\/span>\u0627\u0644\u062e\u0644\u0627\u0635\u0629<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>\u0627\u0644\u0641\u062c\u0648\u0629 \u0628\u064a\u0646 CUDA-ROCm \u0641\u064a \u0639\u0627\u0645 2026 \u0647\u064a <strong>\u0623\u0635\u063a\u0631 \u0645\u0645\u0627 \u0643\u0627\u0646\u062a \u0639\u0644\u064a\u0647 \u0641\u064a \u0623\u064a \u0648\u0642\u062a \u0645\u0636\u0649<\/strong> - \u062d\u0648\u0627\u0644\u064a 201 \u062a\u064a\u0631\u0627\u0628\u0627\u064a\u062a 3 \u062a\u064a\u0631\u0627\u0628\u0627\u064a\u062a \u0641\u064a \u0627\u0644\u0645\u062a\u0648\u0633\u0637 \u0644\u0644\u0627\u0633\u062a\u062f\u0644\u0627\u0644\u060c \u0648\u0623\u0643\u0628\u0631 \u0645\u0646 \u0630\u0644\u0643 \u0644\u0644\u062a\u062f\u0631\u064a\u0628\u060c \u0648\u062a\u0642\u062a\u0631\u0628 \u0645\u0646 \u0627\u0644\u0635\u0641\u0631 \u0644\u0623\u0639\u0628\u0627\u0621 \u0627\u0644\u0639\u0645\u0644 \u0627\u0644\u0627\u0633\u062a\u0647\u0644\u0627\u0643\u064a\u0629 \u0627\u0644\u0623\u0643\u062b\u0631 \u0634\u064a\u0648\u0639\u064b\u0627. \u0645\u0646\u0630 \u062b\u0644\u0627\u062b \u0633\u0646\u0648\u0627\u062a\u060c \u0643\u0627\u0646\u062a \u201cNvidia \u0644\u0644\u0630\u0643\u0627\u0621 \u0627\u0644\u0627\u0635\u0637\u0646\u0627\u0639\u064a\u201d \u0623\u0645\u0631\u064b\u0627 \u0644\u0627 \u064a\u062d\u062a\u0627\u062c \u0625\u0644\u0649 \u062a\u0641\u0643\u064a\u0631\u060c \u0623\u0645\u0627 \u0627\u0644\u064a\u0648\u0645\u060c \u0644\u0627 \u062a\u0632\u0627\u0644 \u201cNvidia \u0644\u0644\u0630\u0643\u0627\u0621 \u0627\u0644\u0627\u0635\u0637\u0646\u0627\u0639\u064a\u201d \u0647\u064a \u0627\u0644\u0625\u062c\u0627\u0628\u0629 \u0627\u0644\u0627\u0641\u062a\u0631\u0627\u0636\u064a\u0629 \u0648\u0644\u0643\u0646\u0647\u0627 \u0644\u064a\u0633\u062a \u0627\u0644\u0625\u062c\u0627\u0628\u0629 \u0627\u0644\u0648\u062d\u064a\u062f\u0629 \u0627\u0644\u0645\u0648\u062b\u0648\u0642\u0629.<\/p>\n<p>\u0625\u0630\u0627 \u0643\u0646\u062a \u062a\u0642\u0648\u0645 \u0628\u0627\u0644\u0628\u0646\u0627\u0621 \u0627\u0644\u064a\u0648\u0645\u060c \u0641\u0625\u0646 \u0627\u0644\u0625\u062c\u0627\u0628\u0629 \u0627\u0644\u0639\u0645\u0644\u064a\u0629 \u0644\u0627 \u062a\u0632\u0627\u0644 CUDA \u0644\u0645\u0639\u0638\u0645 \u0627\u0644\u0645\u0633\u062a\u062e\u062f\u0645\u064a\u0646 - \u0648\u064a\u0631\u062c\u0639 \u0630\u0644\u0643 \u0641\u064a \u0627\u0644\u0645\u0642\u0627\u0645 \u0627\u0644\u0623\u0648\u0644 \u0625\u0644\u0649 \u0627\u062a\u0633\u0627\u0639 \u0646\u0637\u0627\u0642 \u0627\u0644\u0628\u0631\u0627\u0645\u062c\u060c \u0648\u0644\u064a\u0633 \u0627\u0644\u0623\u062f\u0627\u0621 \u0627\u0644\u062e\u0627\u0645. \u0625\u0630\u0627 \u0643\u0646\u062a \u062a\u0642\u062f\u0631 \u0627\u0644\u0646\u0638\u0645 \u0627\u0644\u0625\u064a\u0643\u0648\u0644\u0648\u062c\u064a\u0629 \u0627\u0644\u0645\u0641\u062a\u0648\u062d\u0629 \u0639\u0644\u0649 \u0648\u062c\u0647 \u0627\u0644\u062a\u062d\u062f\u064a\u062f\u060c \u0623\u0648 \u062a\u062d\u062a\u0627\u062c \u0625\u0644\u0649 \u0623\u0642\u0635\u0649 \u0642\u062f\u0631 \u0645\u0646 \u0630\u0627\u0643\u0631\u0629 \u0627\u0644\u0648\u0635\u0648\u0644 \u0627\u0644\u0639\u0634\u0648\u0627\u0626\u064a \u0644\u0643\u0644 \u062f\u0648\u0644\u0627\u0631 \u062c\u062f\u064a\u062f\u0629\u060c \u0623\u0648 \u0643\u0646\u062a \u062a\u0628\u0646\u064a \u0627\u0633\u062a\u062f\u0644\u0627\u0644\u064b\u0627 \u0639\u0644\u0649 \u0646\u0637\u0627\u0642 \u0648\u0627\u0633\u0639 \u062d\u064a\u062b \u062a\u062a\u0623\u0644\u0642 \u062e\u064a\u0627\u0631\u0627\u062a AMD \u0627\u0644\u0633\u062d\u0627\u0628\u064a\u0629 \u0648\u062e\u064a\u0627\u0631\u0627\u062a \u0645\u0631\u0643\u0632 \u0627\u0644\u0628\u064a\u0627\u0646\u0627\u062a\u060c \u0641\u0642\u062f \u062d\u0635\u0644\u062a ROCm \u0639\u0644\u0649 \u0645\u0642\u0639\u062f \u062d\u0642\u064a\u0642\u064a \u0639\u0644\u0649 \u0627\u0644\u0637\u0627\u0648\u0644\u0629.<\/p>\n<p>\u0627\u0646\u062a\u0647\u0649 \u0623\u062e\u064a\u0631\u064b\u0627 \u0627\u0644\u0627\u062d\u062a\u0643\u0627\u0631 \u0627\u0644\u0630\u064a \u062f\u0627\u0645 \u0639\u0642\u062f\u064b\u0627 \u0645\u0646 \u0627\u0644\u0632\u0645\u0646. \u0648\u0628\u062f\u0623 \u0627\u0644\u0627\u0646\u062a\u0642\u0627\u0644 \u0645\u0646\u0647 \u0628\u0639\u062f \u062e\u0645\u0633 \u0633\u0646\u0648\u0627\u062a.<\/p>\n<p><!--related-block--><\/p>\n<div class=\"convly-related\">\n<h2><span class=\"ez-toc-section\" id=\"Related_articles\"><\/span>\u0645\u0642\u0627\u0644\u0627\u062a \u0630\u0627\u062a \u0635\u0644\u0629<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<ul>\n<li><a href=\"https:\/\/convly.ai\/ar\/mistral-7b-vs-llama-3-1-8b\/\">Mistral 7B vs Llama 3.1 8B: Specs, Pricing &amp; Which to Choose (2026)<\/a><\/li>\n<li><a href=\"https:\/\/convly.ai\/ar\/rx-7900-xtx-vs-rtx-4090-for-ai\/\">AMD RX 7900 XTX \u0645\u0642\u0627\u0628\u0644 RTX 4090 \u0644\u0644\u0630\u0643\u0627\u0621 \u0627\u0644\u0627\u0635\u0637\u0646\u0627\u0639\u064a \u0641\u064a \u0639\u0627\u0645 2026: \u0647\u0644 \u064a\u0645\u0643\u0646 \u0644\u0645\u0646\u0635\u0629 ROCm \u0627\u0644\u0645\u0646\u0627\u0641\u0633\u0629\u061f<\/a><\/li>\n<li><a href=\"https:\/\/convly.ai\/ar\/rtx-5080-vs-rtx-4080-super-for-ai\/\">RTX 5080 \u0645\u0642\u0627\u0628\u0644 RTX 4080 Super \u0644\u0644\u0630\u0643\u0627\u0621 \u0627\u0644\u0627\u0635\u0637\u0646\u0627\u0639\u064a \u0641\u064a \u0639\u0627\u0645 2026: \u0647\u0644 \u0627\u0644\u0641\u0627\u0631\u0642 \u0628\u064a\u0646 \u0627\u0644\u062c\u064a\u0644\u064a\u0646 \u0643\u0628\u064a\u0631 \u0623\u0645 \u0623\u0646 \u0627\u0644\u062a\u0631\u0642\u064a\u0629 \u0637\u0641\u064a\u0641\u0629\u061f<\/a><\/li>\n<li><a href=\"https:\/\/convly.ai\/ar\/rtx-5070-ti-vs-rtx-4070-ti-super-for-ai\/\">RTX 5070 Ti \u0645\u0642\u0627\u0628\u0644 RTX 4070 Ti Super \u0644\u0644\u0630\u0643\u0627\u0621 \u0627\u0644\u0627\u0635\u0637\u0646\u0627\u0639\u064a \u0641\u064a \u0639\u0627\u0645 2026: \u0645\u0648\u0627\u062c\u0647\u0629 \u0641\u064a \u0627\u0644\u0641\u0626\u0629 \u0627\u0644\u0645\u062a\u0648\u0633\u0637\u0629<\/a><\/li>\n<li><a href=\"https:\/\/convly.ai\/ar\/rtx-4090-vs-rtx-3090-for-ai\/\">RTX 4090 \u0645\u0642\u0627\u0628\u0644 RTX 3090 \u0644\u0644\u0630\u0643\u0627\u0621 \u0627\u0644\u0627\u0635\u0637\u0646\u0627\u0639\u064a \u0641\u064a \u0639\u0627\u0645 2026: \u0647\u0644 \u062a\u0633\u062a\u062d\u0642 \u0627\u0644\u062a\u0631\u0642\u064a\u0629 \u062d\u0642\u064b\u0651\u0627\u061f<\/a><\/li>\n<\/ul>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>\u0628\u0639\u062f \u0645\u0631\u0648\u0631 \u062b\u0644\u0627\u062b \u0633\u0646\u0648\u0627\u062a \u0639\u0644\u0649 \u062f\u0641\u0639 AMD\u060c \u0623\u0635\u0628\u062d ROCm 6.3 \u0639\u0644\u0649 7900 XTX \u0623\u062e\u064a\u0631\u064b\u0627 \u0642\u0627\u0628\u0644\u0627\u064b \u0644\u0644\u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0641\u064a \u0627\u0644\u0630\u0643\u0627\u0621 \u0627\u0644\u0627\u0635\u0637\u0646\u0627\u0639\u064a \u0627\u0644\u062c\u0627\u062f. \u0644\u0643\u0646 CUDA \u0644\u0627 \u062a\u0642\u0641 \u0645\u0643\u062a\u0648\u0641\u0629 \u0627\u0644\u0623\u064a\u062f\u064a - \u0625\u0644\u064a\u0643 \u0623\u064a\u0646 \u064a\u0641\u0648\u0632 \u0643\u0644 \u0646\u0638\u0627\u0645 \u0628\u064a\u0626\u064a \u0628\u0627\u0644\u0641\u0639\u0644 \u0641\u064a \u0639\u0627\u0645 2026.<\/p>","protected":false},"author":1,"featured_media":386,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"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":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center 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center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[246],"tags":[292,254,293,295,291,294],"class_list":["post-375","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai-comparisons","tag-amd-ai","tag-cuda","tag-nvidia-ai","tag-pytorch-amd","tag-rocm","tag-rx-7900-xtx"],"_links":{"self":[{"href":"https:\/\/convly.ai\/ar\/wp-json\/wp\/v2\/posts\/375","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/convly.ai\/ar\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/convly.ai\/ar\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/convly.ai\/ar\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/convly.ai\/ar\/wp-json\/wp\/v2\/comments?post=375"}],"version-history":[{"count":5,"href":"https:\/\/convly.ai\/ar\/wp-json\/wp\/v2\/posts\/375\/revisions"}],"predecessor-version":[{"id":1533,"href":"https:\/\/convly.ai\/ar\/wp-json\/wp\/v2\/posts\/375\/revisions\/1533"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/convly.ai\/ar\/wp-json\/wp\/v2\/media\/386"}],"wp:attachment":[{"href":"https:\/\/convly.ai\/ar\/wp-json\/wp\/v2\/media?parent=375"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/convly.ai\/ar\/wp-json\/wp\/v2\/categories?post=375"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/convly.ai\/ar\/wp-json\/wp\/v2\/tags?post=375"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}