{"id":84684,"date":"2026-07-12T13:49:37","date_gmt":"2026-07-12T10:49:37","guid":{"rendered":"https:\/\/twodots.gr\/?p=84684"},"modified":"2026-07-12T13:49:41","modified_gmt":"2026-07-12T10:49:41","slug":"vllm-transformers-native-speed-ai-inference","status":"publish","type":"post","link":"https:\/\/twodots.gr\/en\/vllm-transformers-native-speed-ai-inference\/","title":{"rendered":"\u03a4\u03bf vLLM \u03ba\u03b1\u03b9 \u03c4\u03b1 Transformers \u03c6\u03ad\u03c1\u03bd\u03bf\u03c5\u03bd native-speed AI inference \u03c7\u03c9\u03c1\u03af\u03c2 custom ports"},"content":{"rendered":"<div class=\"td-article-lede\">\n<p>\u03a4\u03bf \u03bd\u03ad\u03bf Transformers modeling backend \u03c4\u03bf\u03c5 vLLM \u03bc\u03b5\u03b9\u03ce\u03bd\u03b5\u03b9 \u03ad\u03bd\u03b1 \u03b1\u03c0\u03cc \u03c4\u03b1 \u03c0\u03b9\u03bf \u03b1\u03ba\u03c1\u03b9\u03b2\u03ac \u03c3\u03b7\u03bc\u03b5\u03af\u03b1 \u03c3\u03c4\u03b7\u03bd \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03b9\u03ba\u03ae \u03b1\u03be\u03b9\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b7 \u03bc\u03b5\u03b3\u03ac\u03bb\u03c9\u03bd \u03b3\u03bb\u03c9\u03c3\u03c3\u03b9\u03ba\u03ce\u03bd \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03c9\u03bd: \u03c4\u03b7\u03bd \u03b1\u03bd\u03ac\u03b3\u03ba\u03b7 \u03b3\u03b9\u03b1 \u03be\u03b5\u03c7\u03c9\u03c1\u03b9\u03c3\u03c4\u03cc, \u03c7\u03b5\u03b9\u03c1\u03bf\u03c0\u03bf\u03af\u03b7\u03c4\u03bf port \u03ba\u03ac\u03b8\u03b5 \u03b1\u03c1\u03c7\u03b9\u03c4\u03b5\u03ba\u03c4\u03bf\u03bd\u03b9\u03ba\u03ae\u03c2 \u03bc\u03cc\u03bd\u03bf \u03ba\u03b1\u03b9 \u03bc\u03cc\u03bd\u03bf \u03b3\u03b9\u03b1 \u03b3\u03c1\u03ae\u03b3\u03bf\u03c1\u03bf inference. \u03a3\u03c4\u03b9\u03c2 \u03b4\u03bf\u03ba\u03b9\u03bc\u03ad\u03c2 \u03c4\u03b7\u03c2 Hugging Face \u03bc\u03b5 \u03c3\u03c5\u03bc\u03b2\u03b1\u03c4\u03ac Qwen3 \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03b1, \u03c4\u03bf backend \u03ad\u03c6\u03c4\u03b1\u03c3\u03b5 \u03ae \u03be\u03b5\u03c0\u03ad\u03c1\u03b1\u03c3\u03b5 \u03c4\u03bf throughput \u03c4\u03c9\u03bd native vLLM \u03c5\u03bb\u03bf\u03c0\u03bf\u03b9\u03ae\u03c3\u03b5\u03c9\u03bd, \u03b4\u03b9\u03b1\u03c4\u03b7\u03c1\u03ce\u03bd\u03c4\u03b1\u03c2 \u03c4\u03bf model code \u03c4\u03c9\u03bd Transformers \u03c9\u03c2 \u03ba\u03bf\u03b9\u03bd\u03ae \u03b2\u03ac\u03c3\u03b7.<\/p>\n<p>\u0393\u03b9\u03b1 \u03bc\u03b9\u03b1 \u03b5\u03c0\u03b9\u03c7\u03b5\u03af\u03c1\u03b7\u03c3\u03b7, \u03b1\u03c5\u03c4\u03cc \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u03b1\u03c0\u03bb\u03ce\u03c2 \u03b2\u03b5\u03bb\u03c4\u03af\u03c9\u03c3\u03b7 \u03b5\u03bd\u03cc\u03c2 framework. \u039c\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03bc\u03b9\u03ba\u03c1\u03cd\u03bd\u03b5\u03b9 \u03c4\u03b7\u03bd \u03b1\u03c0\u03cc\u03c3\u03c4\u03b1\u03c3\u03b7 \u03b1\u03bd\u03ac\u03bc\u03b5\u03c3\u03b1 \u03c3\u03c4\u03bf \u03c0\u03b5\u03af\u03c1\u03b1\u03bc\u03b1 \u03ba\u03b1\u03b9 \u03c3\u03b5 \u03bc\u03b9\u03b1 \u03c3\u03c4\u03b1\u03b8\u03b5\u03c1\u03ae \u03c5\u03c0\u03b7\u03c1\u03b5\u03c3\u03af\u03b1 AI \u03b3\u03b9\u03b1 \u03b1\u03bd\u03b1\u03b6\u03ae\u03c4\u03b7\u03c3\u03b7, customer support, product recommendations, \u03c0\u03b5\u03c1\u03b9\u03b5\u03c7\u03cc\u03bc\u03b5\u03bd\u03bf \u03ae \u03b5\u03c3\u03c9\u03c4\u03b5\u03c1\u03b9\u03ba\u03ac \u03b5\u03c1\u03b3\u03b1\u03bb\u03b5\u03af\u03b1. \u0397 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ae \u03b1\u03be\u03af\u03b1, \u03cc\u03bc\u03c9\u03c2, \u03c6\u03b1\u03af\u03bd\u03b5\u03c4\u03b1\u03b9 \u03bc\u03cc\u03bd\u03bf \u03cc\u03c4\u03b1\u03bd \u03b7 \u03bf\u03bc\u03ac\u03b4\u03b1 \u03bc\u03b5\u03c4\u03c1\u03ae\u03c3\u03b5\u03b9 latency, throughput, \u03ba\u03cc\u03c3\u03c4\u03bf\u03c2 GPU \u03ba\u03b1\u03b9 \u03c0\u03bf\u03b9\u03cc\u03c4\u03b7\u03c4\u03b1 \u03c3\u03c4\u03b1 \u03b4\u03b9\u03ba\u03ac \u03c4\u03b7\u03c2 workloads.<\/p>\n<\/div>\n<div class=\"td-article-toc\">\n<div class=\"td-toc-title\">Contents<\/div>\n<ul>\n<li><a href=\"#giati-afora-marketing-ecommerce\">\u0393\u03b9\u03b1\u03c4\u03af \u03b1\u03c6\u03bf\u03c1\u03ac marketing, e-commerce \u03ba\u03b1\u03b9 software \u03bf\u03bc\u03ac\u03b4\u03b5\u03c2<\/a><\/li>\n<li><a href=\"#dyo-ylopoiiseis-idio-montelo\">\u03a4\u03bf \u03c0\u03b1\u03bb\u03b9\u03cc \u03c0\u03c1\u03cc\u03b2\u03bb\u03b7\u03bc\u03b1: \u03b4\u03cd\u03bf \u03c5\u03bb\u03bf\u03c0\u03bf\u03b9\u03ae\u03c3\u03b5\u03b9\u03c2 \u03b3\u03b9\u03b1 \u03c4\u03bf \u03af\u03b4\u03b9\u03bf \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf<\/a><\/li>\n<li><a href=\"#dokimes-qwen3\">\u03a4\u03b9 \u03ad\u03b4\u03b5\u03b9\u03be\u03b1\u03bd \u03bf\u03b9 \u03b4\u03bf\u03ba\u03b9\u03bc\u03ad\u03c2 \u03bc\u03b5 Qwen3<\/a><\/li>\n<li><a href=\"#ena-flag-allazei-diadromi\">\u0388\u03bd\u03b1 flag \u03b1\u03bb\u03bb\u03ac\u03b6\u03b5\u03b9 \u03c4\u03b7 \u03b4\u03b9\u03b1\u03b4\u03c1\u03bf\u03bc\u03ae \u03c4\u03bf\u03c5 \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf\u03c5<\/a><\/li>\n<li><a href=\"#pos-petychainetai-tachytita\">\u03a0\u03ce\u03c2 \u03c0\u03b5\u03c4\u03c5\u03c7\u03b1\u03af\u03bd\u03b5\u03c4\u03b1\u03b9 \u03b7 \u03c4\u03b1\u03c7\u03cd\u03c4\u03b7\u03c4\u03b1 \u03c7\u03c9\u03c1\u03af\u03c2 custom vLLM port<\/a><\/li>\n<li><a href=\"#idio-model-code\">\u0393\u03b9\u03b1\u03c4\u03af \u03c4\u03bf \u03af\u03b4\u03b9\u03bf model code \u03b5\u03af\u03bd\u03b1\u03b9 \u03b5\u03c0\u03b9\u03c7\u03b5\u03b9\u03c1\u03b7\u03bc\u03b1\u03c4\u03b9\u03ba\u03cc \u03c0\u03bb\u03b5\u03bf\u03bd\u03ad\u03ba\u03c4\u03b7\u03bc\u03b1<\/a><\/li>\n<li><a href=\"#ai-proionta-pelati\">\u03a4\u03b9 \u03c3\u03b7\u03bc\u03b1\u03af\u03bd\u03b5\u03b9 \u03b3\u03b9\u03b1 AI \u03c0\u03c1\u03bf\u03ca\u03cc\u03bd\u03c4\u03b1 \u03c0\u03bf\u03c5 \u03b1\u03b3\u03b3\u03af\u03b6\u03bf\u03c5\u03bd \u03c4\u03bf\u03bd \u03c0\u03b5\u03bb\u03ac\u03c4\u03b7<\/a><\/li>\n<li><a href=\"#benchmark-prin-paragogi\">\u03a4\u03b9 \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03bc\u03b5\u03c4\u03c1\u03ae\u03c3\u03b5\u03b9 \u03b7 \u03bf\u03bc\u03ac\u03b4\u03b1 \u03c0\u03c1\u03b9\u03bd \u03b1\u03c0\u03cc \u03c4\u03b7\u03bd \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae<\/a><\/li>\n<li><a href=\"#oria-kai-prosochi\">\u03a0\u03bf\u03cd \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03c0\u03c1\u03bf\u03c3\u03bf\u03c7\u03ae \u03c0\u03c1\u03b9\u03bd \u03b1\u03c0\u03cc \u03c4\u03b7\u03bd \u03c5\u03b9\u03bf\u03b8\u03ad\u03c4\u03b7\u03c3\u03b7<\/a><\/li>\n<li><a href=\"#symperasma-elliniki-agora\">\u03a4\u03bf \u03c3\u03c5\u03bc\u03c0\u03ad\u03c1\u03b1\u03c3\u03bc\u03b1 \u03b3\u03b9\u03b1 \u03c4\u03b7\u03bd \u03b5\u03bb\u03bb\u03b7\u03bd\u03b9\u03ba\u03ae \u03b1\u03b3\u03bf\u03c1\u03ac<\/a><\/li>\n<li><a href=\"#ai-workflows-me-metrisi\">AI workflows \u03bc\u03b5 \u03bc\u03ad\u03c4\u03c1\u03b7\u03c3\u03b7 \u03b1\u03c0\u03cc \u03c4\u03bf pilot \u03c3\u03c4\u03b7\u03bd \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae<\/a><\/li>\n<\/ul>\n<\/div>\n<h2 id=\"giati-afora-marketing-ecommerce\">\u0393\u03b9\u03b1\u03c4\u03af \u03b1\u03c6\u03bf\u03c1\u03ac marketing, e-commerce \u03ba\u03b1\u03b9 software \u03bf\u03bc\u03ac\u03b4\u03b5\u03c2<\/h2>\n<p>\u03a0\u03bf\u03bb\u03bb\u03ac AI projects \u03be\u03b5\u03ba\u03b9\u03bd\u03bf\u03cd\u03bd \u03c9\u03c2 \u03c0\u03b5\u03b9\u03c1\u03ac\u03bc\u03b1\u03c4\u03b1: \u03ad\u03bd\u03b1 chatbot \u03b3\u03b9\u03b1 \u03c0\u03b5\u03bb\u03ac\u03c4\u03b5\u03c2, \u03ad\u03bd\u03b1\u03c2 \u03b2\u03bf\u03b7\u03b8\u03cc\u03c2 \u03b3\u03b9\u03b1 \u03c0\u03b5\u03c1\u03b9\u03b3\u03c1\u03b1\u03c6\u03ad\u03c2 \u03c0\u03c1\u03bf\u03ca\u03cc\u03bd\u03c4\u03c9\u03bd, \u03ad\u03bd\u03b1 \u03b5\u03c1\u03b3\u03b1\u03bb\u03b5\u03af\u03bf \u03ba\u03b1\u03c4\u03b7\u03b3\u03bf\u03c1\u03b9\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b7\u03c2 leads \u03ae \u03ad\u03bd\u03b1 \u03c3\u03cd\u03c3\u03c4\u03b7\u03bc\u03b1 \u03c0\u03bf\u03c5 \u03c3\u03c5\u03bd\u03bf\u03c8\u03af\u03b6\u03b5\u03b9 reviews. \u03a4\u03bf \u03c0\u03c1\u03cc\u03b2\u03bb\u03b7\u03bc\u03b1 \u03b5\u03bc\u03c6\u03b1\u03bd\u03af\u03b6\u03b5\u03c4\u03b1\u03b9 \u03cc\u03c4\u03b1\u03bd \u03c4\u03bf \u03c0\u03b5\u03af\u03c1\u03b1\u03bc\u03b1 \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03b3\u03af\u03bd\u03b5\u03b9 \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03b9\u03ba\u03cc \u03c0\u03c1\u03bf\u03ca\u03cc\u03bd. \u03a4\u03cc\u03c4\u03b5 \u03b7 \u03bf\u03bc\u03ac\u03b4\u03b1 \u03b4\u03b5\u03bd \u03bc\u03b5\u03c4\u03c1\u03ac \u03bc\u03cc\u03bd\u03bf \u03b1\u03bd \u03c4\u03bf \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03b1\u03c0\u03b1\u03bd\u03c4\u03ac \u03ba\u03b1\u03bb\u03ac, \u03b1\u03bb\u03bb\u03ac \u03b1\u03bd \u03b1\u03c0\u03b1\u03bd\u03c4\u03ac \u03b3\u03c1\u03ae\u03b3\u03bf\u03c1\u03b1, \u03c3\u03c4\u03b1\u03b8\u03b5\u03c1\u03ac \u03ba\u03b1\u03b9 \u03bc\u03b5 \u03ba\u03cc\u03c3\u03c4\u03bf\u03c2 \u03c0\u03bf\u03c5 \u03b2\u03b3\u03b1\u03af\u03bd\u03b5\u03b9 \u03b5\u03bc\u03c0\u03bf\u03c1\u03b9\u03ba\u03ac.<\/p>\n<p>\u03a4\u03bf vLLM \u03ad\u03c7\u03b5\u03b9 \u03c3\u03c7\u03b5\u03b4\u03b9\u03b1\u03c3\u03c4\u03b5\u03af \u03b3\u03b9\u03b1 \u03b1\u03c0\u03bf\u03b4\u03bf\u03c4\u03b9\u03ba\u03cc inference \u03ba\u03b1\u03b9 \u03c7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03b5\u03af \u03c4\u03b5\u03c7\u03bd\u03b9\u03ba\u03ad\u03c2 \u03cc\u03c0\u03c9\u03c2 continuous batching \u03ba\u03b1\u03b9 PagedAttention \u03ce\u03c3\u03c4\u03b5 \u03bd\u03b1 \u03b5\u03be\u03c5\u03c0\u03b7\u03c1\u03b5\u03c4\u03b5\u03af \u03c0\u03bf\u03bb\u03bb\u03ac \u03b1\u03b9\u03c4\u03ae\u03bc\u03b1\u03c4\u03b1 \u03bc\u03b5 \u03ba\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03b7 \u03b1\u03be\u03b9\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b7 \u03c4\u03b7\u03c2 GPU. \u03a4\u03b1 Transformers \u03c4\u03b7\u03c2 Hugging Face \u03bb\u03b5\u03b9\u03c4\u03bf\u03c5\u03c1\u03b3\u03bf\u03cd\u03bd \u03c9\u03c2 \u03ba\u03bf\u03b9\u03bd\u03cc framework \u03bf\u03c1\u03b9\u03c3\u03bc\u03bf\u03cd \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03c9\u03bd, \u03bc\u03b5 \u03c3\u03c5\u03bd\u03b5\u03c0\u03ae APIs \u03ba\u03b1\u03b9 \u03bc\u03b5\u03b3\u03ac\u03bb\u03b7 \u03ba\u03ac\u03bb\u03c5\u03c8\u03b7 \u03b1\u03c1\u03c7\u03b9\u03c4\u03b5\u03ba\u03c4\u03bf\u03bd\u03b9\u03ba\u03ce\u03bd. \u0397 \u03c3\u03c4\u03b5\u03bd\u03cc\u03c4\u03b5\u03c1\u03b7 \u03c3\u03cd\u03bd\u03b4\u03b5\u03c3\u03b7 \u03c4\u03c9\u03bd \u03b4\u03cd\u03bf \u03bc\u03b5\u03b9\u03ce\u03bd\u03b5\u03b9 \u03c4\u03b7\u03bd \u03c4\u03b5\u03c7\u03bd\u03b9\u03ba\u03ae \u03c4\u03c1\u03b9\u03b2\u03ae \u03b1\u03bd\u03ac\u03bc\u03b5\u03c3\u03b1 \u03c3\u03c4\u03bf \u00ab\u03ad\u03c7\u03bf\u03c5\u03bc\u03b5 \u03ad\u03bd\u03b1 \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03c0\u03bf\u03c5 \u03bb\u03b5\u03b9\u03c4\u03bf\u03c5\u03c1\u03b3\u03b5\u03af\u00bb \u03ba\u03b1\u03b9 \u03c3\u03c4\u03bf \u00ab\u03ad\u03c7\u03bf\u03c5\u03bc\u03b5 \u03bc\u03b9\u03b1 \u03c5\u03c0\u03b7\u03c1\u03b5\u03c3\u03af\u03b1 \u03c0\u03bf\u03c5 \u03b1\u03bd\u03c4\u03ad\u03c7\u03b5\u03b9 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ae \u03c7\u03c1\u03ae\u03c3\u03b7\u00bb.<\/p>\n<p>\u0393\u03b9\u03b1 \u03ad\u03bd\u03b1 e-shop \u03b1\u03c5\u03c4\u03cc \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03c3\u03b7\u03bc\u03b1\u03af\u03bd\u03b5\u03b9 \u03c4\u03b1\u03c7\u03cd\u03c4\u03b5\u03c1\u03b7 \u03b1\u03be\u03b9\u03bf\u03bb\u03cc\u03b3\u03b7\u03c3\u03b7 \u03b5\u03bd\u03cc\u03c2 AI search assistant. \u0393\u03b9\u03b1 \u03bc\u03b9\u03b1 \u03bf\u03bc\u03ac\u03b4\u03b1 content, \u03c0\u03b9\u03bf \u03c3\u03c4\u03b1\u03b8\u03b5\u03c1\u03cc pipeline \u03bc\u03b5 \u03b1\u03bd\u03b8\u03c1\u03ce\u03c0\u03b9\u03bd\u03bf \u03ad\u03bb\u03b5\u03b3\u03c7\u03bf. \u0393\u03b9\u03b1 \u03ad\u03bd\u03b1 SaaS, \u03bb\u03b9\u03b3\u03cc\u03c4\u03b5\u03c1\u03b7 \u03bc\u03b7\u03c7\u03b1\u03bd\u03b9\u03ba\u03ae \u03b4\u03bf\u03c5\u03bb\u03b5\u03b9\u03ac \u03c0\u03c1\u03b9\u03bd \u03ad\u03bd\u03b1 \u03bd\u03ad\u03bf \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03c0\u03b5\u03c1\u03ac\u03c3\u03b5\u03b9 \u03c3\u03b5 production. \u0397 \u03b4\u03c5\u03bd\u03b1\u03c4\u03cc\u03c4\u03b7\u03c4\u03b1 \u03b4\u03b5\u03bd \u03ba\u03b1\u03c4\u03b1\u03c1\u03b3\u03b5\u03af \u03c4\u03bf engineering, \u03b1\u03bb\u03bb\u03ac \u03bc\u03b5\u03c4\u03b1\u03ba\u03b9\u03bd\u03b5\u03af \u03c7\u03c1\u03cc\u03bd\u03bf \u03b1\u03c0\u03cc \u03c4\u03bf \u03b5\u03c0\u03b1\u03bd\u03b1\u03bb\u03b1\u03bc\u03b2\u03b1\u03bd\u03cc\u03bc\u03b5\u03bd\u03bf porting \u03c0\u03c1\u03bf\u03c2 \u03c4\u03bf benchmarking, \u03c4\u03b7\u03bd \u03c0\u03bf\u03b9\u03cc\u03c4\u03b7\u03c4\u03b1 \u03ba\u03b1\u03b9 \u03c4\u03b7\u03bd \u03b5\u03bc\u03c0\u03b5\u03b9\u03c1\u03af\u03b1 \u03c7\u03c1\u03ae\u03c3\u03c4\u03b7.<\/p>\n<div class=\"td-note\"><strong>\u0391\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7 \u03c0\u03c1\u03ce\u03c4\u03b1:<\/strong> \u03c4\u03bf \u03ba\u03ad\u03c1\u03b4\u03bf\u03c2 \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u03cc\u03c4\u03b9 \u03ba\u03ac\u03b8\u03b5 \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03b3\u03af\u03bd\u03b5\u03c4\u03b1\u03b9 \u03b1\u03c5\u03c4\u03cc\u03bc\u03b1\u03c4\u03b1 \u03b3\u03c1\u03ae\u03b3\u03bf\u03c1\u03bf. \u0395\u03af\u03bd\u03b1\u03b9 \u03cc\u03c4\u03b9 \u03bf\u03b9 \u03c3\u03c5\u03bc\u03b2\u03b1\u03c4\u03ad\u03c2 \u03c5\u03bb\u03bf\u03c0\u03bf\u03b9\u03ae\u03c3\u03b5\u03b9\u03c2 Transformers \u03bc\u03c0\u03bf\u03c1\u03bf\u03cd\u03bd \u03bd\u03b1 \u03b1\u03be\u03b9\u03bf\u03c0\u03bf\u03b9\u03ae\u03c3\u03bf\u03c5\u03bd \u03c4\u03bf serving \u03c4\u03bf\u03c5 vLLM \u03c7\u03c9\u03c1\u03af\u03c2 \u03b4\u03b5\u03cd\u03c4\u03b5\u03c1\u03b7, \u03c0\u03bb\u03ae\u03c1\u03c9\u03c2 \u03be\u03b5\u03c7\u03c9\u03c1\u03b9\u03c3\u03c4\u03ae \u03c5\u03bb\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b7.<\/div>\n<h2 id=\"dyo-ylopoiiseis-idio-montelo\">\u03a4\u03bf \u03c0\u03b1\u03bb\u03b9\u03cc \u03c0\u03c1\u03cc\u03b2\u03bb\u03b7\u03bc\u03b1: \u03b4\u03cd\u03bf \u03c5\u03bb\u03bf\u03c0\u03bf\u03b9\u03ae\u03c3\u03b5\u03b9\u03c2 \u03b3\u03b9\u03b1 \u03c4\u03bf \u03af\u03b4\u03b9\u03bf \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf<\/h2>\n<p>\u0397 \u03c3\u03c5\u03bd\u03b7\u03b8\u03b9\u03c3\u03bc\u03ad\u03bd\u03b7 \u03c0\u03bf\u03c1\u03b5\u03af\u03b1 \u03ae\u03c4\u03b1\u03bd \u03b4\u03b9\u03c0\u03bb\u03ae. \u0388\u03bd\u03b1 \u03bd\u03ad\u03bf \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03c5\u03bb\u03bf\u03c0\u03bf\u03b9\u03bf\u03cd\u03bd\u03c4\u03b1\u03bd \u03c0\u03c1\u03ce\u03c4\u03b1 \u03c3\u03c4\u03b1 Transformers, \u03ce\u03c3\u03c4\u03b5 \u03bd\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03ba\u03b1\u03c4\u03b1\u03bd\u03bf\u03b7\u03c4\u03cc, \u03b5\u03ba\u03c0\u03b1\u03b9\u03b4\u03b5\u03cd\u03c3\u03b9\u03bc\u03bf \u03ba\u03b1\u03b9 \u03b5\u03cd\u03ba\u03bf\u03bb\u03bf \u03bd\u03b1 \u03c7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03b7\u03b8\u03b5\u03af \u03b1\u03c0\u03cc \u03c4\u03b7\u03bd \u03ba\u03bf\u03b9\u03bd\u03cc\u03c4\u03b7\u03c4\u03b1. \u0391\u03bd \u03b7 \u03bf\u03bc\u03ac\u03b4\u03b1 \u03ae\u03b8\u03b5\u03bb\u03b5 \u03c4\u03b7 \u03bc\u03ad\u03b3\u03b9\u03c3\u03c4\u03b7 \u03c4\u03b1\u03c7\u03cd\u03c4\u03b7\u03c4\u03b1 \u03c3\u03b5 production inference, \u03c3\u03c5\u03c7\u03bd\u03ac \u03c7\u03c1\u03b5\u03b9\u03b1\u03b6\u03cc\u03c4\u03b1\u03bd \u03ba\u03b1\u03b9 \u03be\u03b5\u03c7\u03c9\u03c1\u03b9\u03c3\u03c4\u03ae native \u03c5\u03bb\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b7 \u03b3\u03b9\u03b1 vLLM \u03bc\u03b5 \u03b5\u03b9\u03b4\u03b9\u03ba\u03ad\u03c2 \u03b2\u03b5\u03bb\u03c4\u03b9\u03c3\u03c4\u03bf\u03c0\u03bf\u03b9\u03ae\u03c3\u03b5\u03b9\u03c2.<\/p>\n<p>\u0391\u03c5\u03c4\u03cc \u03b4\u03b7\u03bc\u03b9\u03bf\u03c5\u03c1\u03b3\u03bf\u03cd\u03c3\u03b5 \u03ba\u03cc\u03c3\u03c4\u03bf\u03c2 \u03c3\u03c5\u03bd\u03c4\u03ae\u03c1\u03b7\u03c3\u03b7\u03c2. \u039a\u03ac\u03b8\u03b5 \u03b1\u03bb\u03bb\u03b1\u03b3\u03ae \u03c3\u03c4\u03b7\u03bd \u03b1\u03c1\u03c7\u03b9\u03c4\u03b5\u03ba\u03c4\u03bf\u03bd\u03b9\u03ba\u03ae, \u03bd\u03ad\u03b1 \u03c0\u03b1\u03c1\u03b1\u03bb\u03bb\u03b1\u03b3\u03ae \u03ae \u03b5\u03b9\u03b4\u03b9\u03ba\u03ae \u03b2\u03b5\u03bb\u03c4\u03af\u03c9\u03c3\u03b7 \u03ad\u03c0\u03c1\u03b5\u03c0\u03b5 \u03bd\u03b1 \u03b5\u03be\u03b5\u03c4\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03c3\u03b5 \u03b4\u03cd\u03bf \u03b4\u03b9\u03b1\u03b4\u03c1\u03bf\u03bc\u03ad\u03c2 \u03ba\u03ce\u03b4\u03b9\u03ba\u03b1. \u0393\u03b9\u03b1 \u03b5\u03c1\u03b5\u03c5\u03bd\u03b7\u03c4\u03b9\u03ba\u03ad\u03c2 \u03bf\u03bc\u03ac\u03b4\u03b5\u03c2 \u03ba\u03b1\u03b9 startups, \u03c4\u03bf \u03b4\u03b9\u03c0\u03bb\u03cc \u03ad\u03c1\u03b3\u03bf \u03bc\u03c0\u03bf\u03c1\u03bf\u03cd\u03c3\u03b5 \u03bd\u03b1 \u03ba\u03b1\u03b8\u03c5\u03c3\u03c4\u03b5\u03c1\u03ae\u03c3\u03b5\u03b9 \u03ad\u03bd\u03b1 \u03bb\u03b1\u03bd\u03c3\u03ac\u03c1\u03b9\u03c3\u03bc\u03b1. \u0393\u03b9\u03b1 \u03b5\u03c0\u03b9\u03c7\u03b5\u03b9\u03c1\u03ae\u03c3\u03b5\u03b9\u03c2 \u03c0\u03bf\u03c5 \u03b5\u03bd\u03c3\u03c9\u03bc\u03b1\u03c4\u03ce\u03bd\u03bf\u03c5\u03bd AI, \u03b1\u03cd\u03be\u03b1\u03bd\u03b5 \u03c4\u03bf\u03bd \u03c7\u03c1\u03cc\u03bd\u03bf \u03b1\u03c0\u03cc \u03c4\u03bf proof of concept \u03ad\u03c9\u03c2 \u03c4\u03b7 \u03c3\u03c4\u03b1\u03b8\u03b5\u03c1\u03ae \u03c5\u03c0\u03b7\u03c1\u03b5\u03c3\u03af\u03b1.<\/p>\n<p>\u0397 \u03bd\u03ad\u03b1 \u03ba\u03b1\u03c4\u03b5\u03cd\u03b8\u03c5\u03bd\u03c3\u03b7 \u03b5\u03c0\u03b9\u03c4\u03c1\u03ad\u03c0\u03b5\u03b9 \u03c3\u03c4\u03bf vLLM \u03bd\u03b1 \u03c6\u03bf\u03c1\u03c4\u03ce\u03bd\u03b5\u03b9 \u03c4\u03bf model definition \u03b1\u03c0\u03cc \u03c4\u03b1 Transformers \u03ba\u03b1\u03b9 \u03bd\u03b1 \u03b1\u03bd\u03c4\u03b9\u03ba\u03b1\u03b8\u03b9\u03c3\u03c4\u03ac \u03ae \u03bd\u03b1 \u03c3\u03c5\u03b3\u03c7\u03c9\u03bd\u03b5\u03cd\u03b5\u03b9 \u03ba\u03c1\u03af\u03c3\u03b9\u03bc\u03b5\u03c2 \u03bb\u03b5\u03b9\u03c4\u03bf\u03c5\u03c1\u03b3\u03af\u03b5\u03c2 \u03bc\u03b5 \u03c4\u03b9\u03c2 \u03b4\u03b9\u03ba\u03ad\u03c2 \u03c4\u03bf\u03c5 \u03b2\u03b5\u03bb\u03c4\u03b9\u03c3\u03c4\u03bf\u03c0\u03bf\u03b9\u03b7\u03bc\u03ad\u03bd\u03b5\u03c2 \u03b5\u03ba\u03b4\u03bf\u03c7\u03ad\u03c2. \u0388\u03c4\u03c3\u03b9 \u03b7 \u03bf\u03bc\u03ac\u03b4\u03b1 \u03ba\u03c1\u03b1\u03c4\u03ac \u03bc\u03b9\u03b1 \u03c0\u03b9\u03bf \u03b5\u03bd\u03b9\u03b1\u03af\u03b1 \u03b2\u03ac\u03c3\u03b7 \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf\u03c5, \u03c7\u03c9\u03c1\u03af\u03c2 \u03bd\u03b1 \u03c7\u03ac\u03bd\u03b5\u03b9 \u03b1\u03c0\u03b1\u03c1\u03b1\u03af\u03c4\u03b7\u03c4\u03b1 \u03c4\u03b7\u03bd \u03b1\u03c0\u03cc\u03b4\u03bf\u03c3\u03b7 \u03c0\u03bf\u03c5 \u03c0\u03b5\u03c1\u03b9\u03bc\u03ad\u03bd\u03b5\u03b9 \u03b1\u03c0\u03cc \u03ad\u03bd\u03b1 serving engine.<\/p>\n<h2 id=\"dokimes-qwen3\">\u03a4\u03b9 \u03ad\u03b4\u03b5\u03b9\u03be\u03b1\u03bd \u03bf\u03b9 \u03b4\u03bf\u03ba\u03b9\u03bc\u03ad\u03c2 \u03bc\u03b5 Qwen3<\/h2>\n<p>\u0397 Hugging Face \u03c3\u03c5\u03bd\u03ad\u03ba\u03c1\u03b9\u03bd\u03b5 \u03c4\u03bf \u03bd\u03ad\u03bf backend \u03c3\u03b5 \u03c4\u03c1\u03af\u03b1 \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03b5\u03c4\u03b9\u03ba\u03ac \u03c3\u03b5\u03bd\u03ac\u03c1\u03b9\u03b1: Qwen3-4B dense \u03c3\u03b5 \u03bc\u03af\u03b1 GPU, Qwen3-32B dense \u03bc\u03b5 tensor parallelism \u03c3\u03b5 \u03b4\u03cd\u03bf GPUs \u03ba\u03b1\u03b9 Qwen3-235B-A22B FP8 Mixture-of-Experts \u03bc\u03b5 data \u03ba\u03b1\u03b9 expert parallelism \u03c3\u03b5 \u03bf\u03ba\u03c4\u03ce H100 GPUs. \u0397 \u03c3\u03cd\u03b3\u03ba\u03c1\u03b9\u03c3\u03b7 \u03ba\u03ac\u03bb\u03c5\u03c8\u03b5 \u03c4\u03b7 native vLLM \u03c5\u03bb\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b7, \u03c4\u03bf Transformers backend \u03bc\u03b5\u03c4\u03ac \u03c4\u03b7 \u03b2\u03b5\u03bb\u03c4\u03af\u03c9\u03c3\u03b7 \u03ba\u03b1\u03b9 \u03c4\u03b7\u03bd \u03c0\u03c1\u03bf\u03b7\u03b3\u03bf\u03cd\u03bc\u03b5\u03bd\u03b7 \u03b5\u03ba\u03b4\u03bf\u03c7\u03ae \u03c4\u03bf\u03c5 backend.<\/p>\n<p>\u03a3\u03c4\u03b1 \u03c3\u03c5\u03b3\u03ba\u03b5\u03ba\u03c1\u03b9\u03bc\u03ad\u03bd\u03b1 \u03c3\u03c5\u03bc\u03b2\u03b1\u03c4\u03ac \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03b1 \u03ba\u03b1\u03b9 \u03c3\u03c4\u03b1 workloads \u03c4\u03b7\u03c2 \u03b1\u03bd\u03b1\u03ba\u03bf\u03af\u03bd\u03c9\u03c3\u03b7\u03c2, \u03c4\u03bf \u03bd\u03ad\u03bf backend \u03ad\u03c6\u03c4\u03b1\u03c3\u03b5 \u03ae \u03be\u03b5\u03c0\u03ad\u03c1\u03b1\u03c3\u03b5 \u03c4\u03bf native throughput. \u0391\u03c5\u03c4\u03cc \u03b5\u03af\u03bd\u03b1\u03b9 \u03b9\u03c3\u03c7\u03c5\u03c1\u03ae \u03c4\u03b5\u03c7\u03bd\u03b9\u03ba\u03ae \u03ad\u03bd\u03b4\u03b5\u03b9\u03be\u03b7, \u03cc\u03c7\u03b9 \u03ba\u03b1\u03b8\u03bf\u03bb\u03b9\u03ba\u03ae \u03b5\u03b3\u03b3\u03cd\u03b7\u03c3\u03b7 \u03b3\u03b9\u03b1 \u03ba\u03ac\u03b8\u03b5 checkpoint, GPU, \u03bc\u03ae\u03ba\u03bf\u03c2 context \u03ae \u03bc\u03b5\u03af\u03b3\u03bc\u03b1 \u03b1\u03b9\u03c4\u03b7\u03bc\u03ac\u03c4\u03c9\u03bd. \u0397 \u03af\u03b4\u03b9\u03b1 \u03b7 Hugging Face \u03c0\u03b1\u03c1\u03ad\u03c7\u03b5\u03b9 reproducible runner, \u03ce\u03c3\u03c4\u03b5 \u03bf\u03b9 \u03c4\u03b5\u03c7\u03bd\u03b9\u03ba\u03ad\u03c2 \u03bf\u03bc\u03ac\u03b4\u03b5\u03c2 \u03bd\u03b1 \u03b5\u03be\u03b5\u03c4\u03ac\u03c3\u03bf\u03c5\u03bd \u03c4\u03b7 \u03bc\u03b5\u03b8\u03bf\u03b4\u03bf\u03bb\u03bf\u03b3\u03af\u03b1 \u03b1\u03bd\u03c4\u03af \u03bd\u03b1 \u03b2\u03b1\u03c3\u03b9\u03c3\u03c4\u03bf\u03cd\u03bd \u03bc\u03cc\u03bd\u03bf \u03c3\u03b5 \u03ad\u03bd\u03b1 \u03c3\u03c5\u03bd\u03bf\u03c0\u03c4\u03b9\u03ba\u03cc claim.<\/p>\n<div class=\"td-decision-band\">\n<p class=\"td-decision-label\">\u0397 \u03c3\u03c9\u03c3\u03c4\u03ae \u03b1\u03bd\u03ac\u03b3\u03bd\u03c9\u03c3\u03b7 \u03c4\u03bf\u03c5 benchmark<\/p>\n<p><strong>\u03a7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03ae\u03c3\u03c4\u03b5 \u03c4\u03bf \u03c9\u03c2 \u03bb\u03cc\u03b3\u03bf \u03b3\u03b9\u03b1 \u03bd\u03b1 \u03b4\u03bf\u03ba\u03b9\u03bc\u03ac\u03c3\u03b5\u03c4\u03b5 \u03c4\u03bf backend, \u03cc\u03c7\u03b9 \u03c9\u03c2 \u03c5\u03c0\u03bf\u03ba\u03b1\u03c4\u03ac\u03c3\u03c4\u03b1\u03c4\u03bf \u03c4\u03bf\u03c5 \u03b4\u03b9\u03ba\u03bf\u03cd \u03c3\u03b1\u03c2 load test.<\/strong><\/p>\n<p>\u03a4\u03bf \u03b1\u03c0\u03bf\u03c4\u03ad\u03bb\u03b5\u03c3\u03bc\u03b1 \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae\u03c2 \u03b5\u03be\u03b1\u03c1\u03c4\u03ac\u03c4\u03b1\u03b9 \u03b1\u03c0\u03cc \u03c4\u03bf \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf, \u03c4\u03bf hardware, \u03c4\u03b1 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ac prompts, \u03c4\u03bf concurrency, \u03c4\u03bf \u03bc\u03ae\u03ba\u03bf\u03c2 \u03b5\u03be\u03cc\u03b4\u03bf\u03c5 \u03ba\u03b1\u03b9 \u03c4\u03bf\u03c5\u03c2 \u03c3\u03c4\u03cc\u03c7\u03bf\u03c5\u03c2 latency \u03c4\u03b7\u03c2 \u03b5\u03c6\u03b1\u03c1\u03bc\u03bf\u03b3\u03ae\u03c2.<\/p>\n<\/div>\n<h2 id=\"ena-flag-allazei-diadromi\">\u0388\u03bd\u03b1 flag \u03b1\u03bb\u03bb\u03ac\u03b6\u03b5\u03b9 \u03c4\u03b7 \u03b4\u03b9\u03b1\u03b4\u03c1\u03bf\u03bc\u03ae \u03c4\u03bf\u03c5 \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf\u03c5<\/h2>\n<p>\u0393\u03b9\u03b1 online serving, \u03b7 \u03b5\u03c0\u03b9\u03bb\u03bf\u03b3\u03ae \u03b3\u03af\u03bd\u03b5\u03c4\u03b1\u03b9 \u03bc\u03b5 \u03c4\u03bf <code>--model-impl transformers<\/code>. \u03a3\u03c4\u03bf Python API \u03c7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03b5\u03af\u03c4\u03b1\u03b9 \u03c4\u03bf \u03b1\u03bd\u03c4\u03af\u03c3\u03c4\u03bf\u03b9\u03c7\u03bf <code>model_impl=\"transformers\"<\/code>. \u0397 \u03b5\u03c0\u03b9\u03bb\u03bf\u03b3\u03ae \u03c3\u03c5\u03bd\u03b4\u03c5\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03bc\u03b5 \u03c3\u03c5\u03bd\u03ae\u03b8\u03b5\u03b9\u03c2 \u03c1\u03c5\u03b8\u03bc\u03af\u03c3\u03b5\u03b9\u03c2 parallelism, \u03cc\u03c0\u03c9\u03c2 tensor, data \u03ba\u03b1\u03b9 expert parallelism. \u0391\u03c5\u03c4\u03cc \u03c3\u03b7\u03bc\u03b1\u03af\u03bd\u03b5\u03b9 \u03cc\u03c4\u03b9 \u03bc\u03b9\u03b1 \u03bf\u03bc\u03ac\u03b4\u03b1 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b4\u03bf\u03ba\u03b9\u03bc\u03ac\u03c3\u03b5\u03b9 \u03c4\u03b7 \u03b4\u03b9\u03b1\u03b4\u03c1\u03bf\u03bc\u03ae Transformers \u03bc\u03ad\u03c3\u03b1 \u03c3\u03c4\u03bf \u03c5\u03c0\u03ac\u03c1\u03c7\u03bf\u03bd vLLM serving \u03c0\u03b5\u03c1\u03b9\u03b2\u03ac\u03bb\u03bb\u03bf\u03bd \u03c7\u03c9\u03c1\u03af\u03c2 \u03bd\u03b1 \u03be\u03b1\u03bd\u03b1\u03c3\u03c7\u03b5\u03b4\u03b9\u03ac\u03c3\u03b5\u03b9 \u03cc\u03bb\u03b7 \u03c4\u03b7\u03bd \u03b5\u03c6\u03b1\u03c1\u03bc\u03bf\u03b3\u03ae.<\/p>\n<p>\u0397 \u03c0\u03c1\u03b1\u03ba\u03c4\u03b9\u03ba\u03ae \u03c5\u03c0\u03cc\u03c3\u03c7\u03b5\u03c3\u03b7 \u03b5\u03af\u03bd\u03b1\u03b9 \u03b1\u03c0\u03bb\u03ae: \u03cc\u03c4\u03b1\u03bd \u03b7 \u03b1\u03c1\u03c7\u03b9\u03c4\u03b5\u03ba\u03c4\u03bf\u03bd\u03b9\u03ba\u03ae \u03b5\u03af\u03bd\u03b1\u03b9 \u03c3\u03c5\u03bc\u03b2\u03b1\u03c4\u03ae, \u03ad\u03bd\u03b1 \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03c0\u03bf\u03c5 \u03ad\u03c7\u03b5\u03b9 \u03bf\u03c1\u03b9\u03c3\u03c4\u03b5\u03af \u03c3\u03c9\u03c3\u03c4\u03ac \u03c3\u03c4\u03b1 Transformers \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b1\u03be\u03b9\u03bf\u03c0\u03bf\u03b9\u03ae\u03c3\u03b5\u03b9 \u03c4\u03bf vLLM \u03bc\u03b5 \u03bb\u03b9\u03b3\u03cc\u03c4\u03b5\u03c1\u03bf \u03b5\u03b9\u03b4\u03b9\u03ba\u03cc porting. \u0391\u03c5\u03c4\u03cc \u03bc\u03b5\u03b9\u03ce\u03bd\u03b5\u03b9 friction \u03c3\u03c4\u03b9\u03c2 \u03b1\u03be\u03b9\u03bf\u03bb\u03bf\u03b3\u03ae\u03c3\u03b5\u03b9\u03c2 \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03c9\u03bd \u03ba\u03b1\u03b9 \u03c0\u03b5\u03c1\u03b9\u03bf\u03c1\u03af\u03b6\u03b5\u03b9 \u03c4\u03b1 \u03c3\u03b7\u03bc\u03b5\u03af\u03b1 \u03cc\u03c0\u03bf\u03c5 \u03b4\u03cd\u03bf \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03b5\u03c4\u03b9\u03ba\u03ad\u03c2 \u03c5\u03bb\u03bf\u03c0\u03bf\u03b9\u03ae\u03c3\u03b5\u03b9\u03c2 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b1\u03c0\u03bf\u03ba\u03bb\u03af\u03bd\u03bf\u03c5\u03bd.<\/p>\n<p>\u0397 \u03b1\u03bb\u03bb\u03b1\u03b3\u03ae \u03b5\u03bd\u03cc\u03c2 flag \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9, \u03b2\u03ad\u03b2\u03b1\u03b9\u03b1, rollout plan. \u0397 \u03bf\u03bc\u03ac\u03b4\u03b1 \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03c3\u03b1\u03c6\u03ae baseline, \u03af\u03b4\u03b9\u03b1 \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03b1 \u03b4\u03bf\u03ba\u03b9\u03bc\u03ae\u03c2, \u03af\u03b4\u03b9\u03b1 sampling settings \u03ba\u03b1\u03b9 \u03bc\u03b5\u03c4\u03c1\u03ae\u03c3\u03b5\u03b9\u03c2 \u03c0\u03c1\u03b9\u03bd \u03ba\u03b1\u03b9 \u03bc\u03b5\u03c4\u03ac. \u0394\u03b9\u03b1\u03c6\u03bf\u03c1\u03b5\u03c4\u03b9\u03ba\u03ac, \u03bc\u03b9\u03b1 \u03c6\u03b1\u03b9\u03bd\u03bf\u03bc\u03b5\u03bd\u03b9\u03ba\u03ae \u03b2\u03b5\u03bb\u03c4\u03af\u03c9\u03c3\u03b7 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03bf\u03c6\u03b5\u03af\u03bb\u03b5\u03c4\u03b1\u03b9 \u03c3\u03b5 \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03b5\u03c4\u03b9\u03ba\u03cc workload \u03ae \u03c3\u03b5 \u03c1\u03c5\u03b8\u03bc\u03af\u03c3\u03b5\u03b9\u03c2 \u03c0\u03bf\u03c5 \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u03c3\u03c5\u03b3\u03ba\u03c1\u03af\u03c3\u03b9\u03bc\u03b5\u03c2.<\/p>\n<h2 id=\"pos-petychainetai-tachytita\">\u03a0\u03ce\u03c2 \u03c0\u03b5\u03c4\u03c5\u03c7\u03b1\u03af\u03bd\u03b5\u03c4\u03b1\u03b9 \u03b7 \u03c4\u03b1\u03c7\u03cd\u03c4\u03b7\u03c4\u03b1 \u03c7\u03c9\u03c1\u03af\u03c2 custom vLLM port<\/h2>\n<p>\u03a4\u03bf backend \u03c7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03b5\u03af <code>torch.fx<\/code> \u03b3\u03b9\u03b1 \u03c3\u03c4\u03b1\u03c4\u03b9\u03ba\u03ae \u03b1\u03bd\u03ac\u03bb\u03c5\u03c3\u03b7 \u03c4\u03bf\u03c5 graph \u03c4\u03bf\u03c5 \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf\u03c5 \u03ba\u03b1\u03b9 \u03b1\u03bd\u03b1\u03b6\u03b7\u03c4\u03ac \u03b3\u03bd\u03c9\u03c3\u03c4\u03ac \u03bc\u03bf\u03c4\u03af\u03b2\u03b1 \u03c0\u03bf\u03c5 \u03bc\u03c0\u03bf\u03c1\u03bf\u03cd\u03bd \u03bd\u03b1 \u03b2\u03b5\u03bb\u03c4\u03b9\u03c3\u03c4\u03bf\u03c0\u03bf\u03b9\u03b7\u03b8\u03bf\u03cd\u03bd. \u038c\u03c4\u03b1\u03bd \u03b5\u03bd\u03c4\u03bf\u03c0\u03b9\u03c3\u03c4\u03bf\u03cd\u03bd, \u03b1\u03be\u03b9\u03bf\u03c0\u03bf\u03b9\u03b5\u03af AST, \u03b4\u03b7\u03bb\u03b1\u03b4\u03ae abstract syntax tree, \u03b3\u03b9\u03b1 \u03bd\u03b1 \u03be\u03b1\u03bd\u03b1\u03b3\u03c1\u03ac\u03c8\u03b5\u03b9 \u03b5\u03c0\u03b9\u03bb\u03b5\u03b3\u03bc\u03ad\u03bd\u03b5\u03c2 \u03bb\u03b5\u03b9\u03c4\u03bf\u03c5\u03c1\u03b3\u03af\u03b5\u03c2 \u03c3\u03c4\u03bf\u03bd \u03c0\u03b7\u03b3\u03b1\u03af\u03bf \u03ba\u03ce\u03b4\u03b9\u03ba\u03b1 \u03ba\u03b1\u03c4\u03ac \u03c4\u03bf runtime.<\/p>\n<p>\u0397 \u03b4\u03b9\u03b1\u03b4\u03b9\u03ba\u03b1\u03c3\u03af\u03b1 \u03b5\u03c6\u03b1\u03c1\u03bc\u03cc\u03b6\u03b5\u03b9 inference-specific layer fusions \u03ba\u03b1\u03b9 \u03b1\u03bd\u03c4\u03b9\u03c3\u03c4\u03bf\u03b9\u03c7\u03af\u03b6\u03b5\u03b9 \u03bb\u03b5\u03b9\u03c4\u03bf\u03c5\u03c1\u03b3\u03af\u03b5\u03c2 \u03c3\u03b5 \u03b2\u03b5\u03bb\u03c4\u03b9\u03c3\u03c4\u03bf\u03c0\u03bf\u03b9\u03b7\u03bc\u03ad\u03bd\u03bf\u03c5\u03c2 kernels \u03c4\u03bf\u03c5 vLLM. \u03a3\u03c4\u03b1 \u03c0\u03b1\u03c1\u03b1\u03b4\u03b5\u03af\u03b3\u03bc\u03b1\u03c4\u03b1 \u03c4\u03b7\u03c2 \u03b1\u03bd\u03b1\u03ba\u03bf\u03af\u03bd\u03c9\u03c3\u03b7\u03c2 \u03c0\u03b5\u03c1\u03b9\u03bb\u03b1\u03bc\u03b2\u03ac\u03bd\u03bf\u03bd\u03c4\u03b1\u03b9 fused operations \u03b3\u03b9\u03b1 expert parallelization \u03c3\u03b5 Mixture-of-Experts \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03b1, \u03ba\u03b1\u03b8\u03ce\u03c2 \u03ba\u03b1\u03b9 blocks \u03cc\u03c0\u03c9\u03c2 <code>MergedColumnParallelLinear<\/code> and <code>QKVParallelLinear<\/code> \u03c0\u03bf\u03c5 \u03b2\u03bf\u03b7\u03b8\u03bf\u03cd\u03bd \u03c3\u03c4\u03b7\u03bd \u03b5\u03be\u03b1\u03b3\u03c9\u03b3\u03ae tensor-parallel plans.<\/p>\n<p>\u038c\u03c4\u03b1\u03bd \u03b7 \u03bb\u03af\u03c3\u03c4\u03b1 \u03c4\u03c9\u03bd decoder blocks \u03b1\u03bd\u03b1\u03b3\u03bd\u03c9\u03c1\u03af\u03b6\u03b5\u03c4\u03b1\u03b9 \u03b5\u03cd\u03ba\u03bf\u03bb\u03b1, \u03bc\u03c0\u03bf\u03c1\u03bf\u03cd\u03bd \u03bd\u03b1 \u03c3\u03c5\u03bd\u03b1\u03c7\u03b8\u03bf\u03cd\u03bd \u03ba\u03b1\u03b9 pipeline-parallel plans. \u03a4\u03b1 \u03bc\u03b5\u03c4\u03b1\u03c3\u03c7\u03b7\u03bc\u03b1\u03c4\u03b9\u03c3\u03bc\u03ad\u03bd\u03b1 \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03b1 \u03c0\u03b1\u03c1\u03b1\u03bc\u03ad\u03bd\u03bf\u03c5\u03bd \u03c3\u03c5\u03bc\u03b2\u03b1\u03c4\u03ac \u03bc\u03b5 <code>torch.compile<\/code> \u03ba\u03b1\u03b9 CUDA Graphs. \u03a4\u03bf \u03ba\u03c1\u03af\u03c3\u03b9\u03bc\u03bf \u03c3\u03b7\u03bc\u03b5\u03af\u03bf \u03b5\u03af\u03bd\u03b1\u03b9 \u03cc\u03c4\u03b9 \u03b7 \u03c4\u03b1\u03c7\u03cd\u03c4\u03b7\u03c4\u03b1 \u03b4\u03b5\u03bd \u03c0\u03c1\u03bf\u03ba\u03cd\u03c0\u03c4\u03b5\u03b9 \u03b1\u03c0\u03cc \u03ad\u03bd\u03b1 \u03b1\u03c0\u03bb\u03cc wrapper, \u03b1\u03bb\u03bb\u03ac \u03b1\u03c0\u03cc \u03b4\u03c5\u03bd\u03b1\u03bc\u03b9\u03ba\u03ae \u03c0\u03c1\u03bf\u03c3\u03b1\u03c1\u03bc\u03bf\u03b3\u03ae \u03c4\u03b7\u03c2 \u03c5\u03bb\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b7\u03c2 \u03c3\u03c4\u03b9\u03c2 \u03b2\u03b5\u03bb\u03c4\u03b9\u03c3\u03c4\u03bf\u03c0\u03bf\u03b9\u03ae\u03c3\u03b5\u03b9\u03c2 \u03c4\u03bf\u03c5 inference engine.<\/p>\n<h2 id=\"idio-model-code\">\u0393\u03b9\u03b1\u03c4\u03af \u03c4\u03bf \u03af\u03b4\u03b9\u03bf model code \u03b5\u03af\u03bd\u03b1\u03b9 \u03b5\u03c0\u03b9\u03c7\u03b5\u03b9\u03c1\u03b7\u03bc\u03b1\u03c4\u03b9\u03ba\u03cc \u03c0\u03bb\u03b5\u03bf\u03bd\u03ad\u03ba\u03c4\u03b7\u03bc\u03b1<\/h2>\n<p>\u039f\u03b9 \u03c5\u03bb\u03bf\u03c0\u03bf\u03b9\u03ae\u03c3\u03b5\u03b9\u03c2 Transformers \u03bc\u03c0\u03bf\u03c1\u03bf\u03cd\u03bd \u03bd\u03b1 \u03c7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03b7\u03b8\u03bf\u03cd\u03bd \u03c3\u03b5 training, evaluations \u03ba\u03b1\u03b9 reinforcement-learning rollouts, \u03b5\u03bd\u03ce \u03bf\u03b9 \u03ba\u03b1\u03b8\u03b1\u03c1\u03ad\u03c2 native vLLM \u03c5\u03bb\u03bf\u03c0\u03bf\u03b9\u03ae\u03c3\u03b5\u03b9\u03c2 \u03c3\u03c4\u03bf\u03c7\u03b5\u03cd\u03bf\u03c5\u03bd \u03ba\u03c5\u03c1\u03af\u03c9\u03c2 \u03c3\u03c4\u03bf inference. \u038c\u03c4\u03b1\u03bd \u03b7 \u03af\u03b4\u03b9\u03b1 \u03b2\u03b1\u03c3\u03b9\u03ba\u03ae \u03c5\u03bb\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b7 \u03ba\u03b1\u03bb\u03cd\u03c0\u03c4\u03b5\u03b9 \u03c0\u03b5\u03c1\u03b9\u03c3\u03c3\u03cc\u03c4\u03b5\u03c1\u03b1 \u03c3\u03c4\u03ac\u03b4\u03b9\u03b1 \u03c4\u03bf\u03c5 \u03ba\u03cd\u03ba\u03bb\u03bf\u03c5 \u03b6\u03c9\u03ae\u03c2, \u03b7 \u03bf\u03bc\u03ac\u03b4\u03b1 \u03bc\u03b5\u03b9\u03ce\u03bd\u03b5\u03b9 \u03c4\u03b9\u03c2 \u03b1\u03c0\u03bf\u03ba\u03bb\u03af\u03c3\u03b5\u03b9\u03c2 \u03b1\u03bd\u03ac\u03bc\u03b5\u03c3\u03b1 \u03c3\u03b5 \u03ad\u03c1\u03b5\u03c5\u03bd\u03b1, \u03b1\u03be\u03b9\u03bf\u03bb\u03cc\u03b3\u03b7\u03c3\u03b7 \u03ba\u03b1\u03b9 \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae.<\/p>\n<p>\u0393\u03b9\u03b1 \u03ad\u03bd\u03b1\u03bd \u03bf\u03c1\u03b3\u03b1\u03bd\u03b9\u03c3\u03bc\u03cc \u03c0\u03bf\u03c5 \u03c7\u03c4\u03af\u03b6\u03b5\u03b9 \u03b9\u03b4\u03b9\u03cc\u03ba\u03c4\u03b7\u03c4\u03b1 AI workflows, \u03b1\u03c5\u03c4\u03cc \u03c3\u03b7\u03bc\u03b1\u03af\u03bd\u03b5\u03b9 \u03bb\u03b9\u03b3\u03cc\u03c4\u03b5\u03c1\u03b1 \u03c3\u03b7\u03bc\u03b5\u03af\u03b1 \u03cc\u03c0\u03bf\u03c5 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b5\u03bc\u03c6\u03b1\u03bd\u03b9\u03c3\u03c4\u03b5\u03af \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03b5\u03c4\u03b9\u03ba\u03ae \u03c3\u03c5\u03bc\u03c0\u03b5\u03c1\u03b9\u03c6\u03bf\u03c1\u03ac \u03bb\u03cc\u03b3\u03c9 \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03b5\u03c4\u03b9\u03ba\u03bf\u03cd \u03ba\u03ce\u03b4\u03b9\u03ba\u03b1. \u039c\u03b9\u03b1 \u03bf\u03bc\u03ac\u03b4\u03b1 \u03c0\u03bf\u03c5 \u03c0\u03c1\u03bf\u03c3\u03b1\u03c1\u03bc\u03cc\u03b6\u03b5\u03b9 \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03b3\u03b9\u03b1 \u03b1\u03c0\u03b1\u03bd\u03c4\u03ae\u03c3\u03b5\u03b9\u03c2 \u03c0\u03b5\u03bb\u03b1\u03c4\u03ce\u03bd \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03ad\u03c7\u03b5\u03b9 \u03ba\u03b1\u03b8\u03b1\u03c1\u03cc\u03c4\u03b5\u03c1\u03b7 \u03b4\u03b9\u03b1\u03b4\u03c1\u03bf\u03bc\u03ae \u03b1\u03c0\u03cc \u03c4\u03bf evaluation \u03ad\u03c9\u03c2 \u03c4\u03bf serving, \u03bc\u03b5 \u03b5\u03c5\u03ba\u03bf\u03bb\u03cc\u03c4\u03b5\u03c1\u03b7 \u03c4\u03b5\u03ba\u03bc\u03b7\u03c1\u03af\u03c9\u03c3\u03b7 \u03ba\u03b1\u03b9 rollback.<\/p>\n<p>\u0393\u03b9\u03b1 business owners \u03ba\u03b1\u03b9 marketers, \u03b7 \u03c7\u03c1\u03ae\u03c3\u03b9\u03bc\u03b7 \u03b5\u03c1\u03ce\u03c4\u03b7\u03c3\u03b7 \u03c0\u03c1\u03bf\u03c2 \u03c4\u03bf\u03bd \u03c4\u03b5\u03c7\u03bd\u03b9\u03ba\u03cc \u03c3\u03c5\u03bd\u03b5\u03c1\u03b3\u03ac\u03c4\u03b7 \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u03bc\u03cc\u03bd\u03bf \u00ab\u03c0\u03bf\u03b9\u03bf \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03b8\u03b1 \u03c7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03ae\u03c3\u03bf\u03c5\u03bc\u03b5;\u00bb. \u0395\u03af\u03bd\u03b1\u03b9 \u00ab\u03c0\u03cc\u03c3\u03bf \u03b5\u03cd\u03ba\u03bf\u03bb\u03b1 \u03bc\u03c0\u03bf\u03c1\u03bf\u03cd\u03bc\u03b5 \u03bd\u03b1 \u03c4\u03bf \u03b1\u03be\u03b9\u03bf\u03bb\u03bf\u03b3\u03ae\u03c3\u03bf\u03c5\u03bc\u03b5, \u03bd\u03b1 \u03c4\u03bf \u03b1\u03bb\u03bb\u03ac\u03be\u03bf\u03c5\u03bc\u03b5 \u03ba\u03b1\u03b9 \u03bd\u03b1 \u03c4\u03bf \u03bb\u03b5\u03b9\u03c4\u03bf\u03c5\u03c1\u03b3\u03ae\u03c3\u03bf\u03c5\u03bc\u03b5 \u03c3\u03b5 \u03ba\u03bb\u03af\u03bc\u03b1\u03ba\u03b1 \u03c7\u03c9\u03c1\u03af\u03c2 \u03bd\u03b1 \u03c3\u03c5\u03bd\u03c4\u03b7\u03c1\u03bf\u03cd\u03bc\u03b5 \u03c0\u03b1\u03c1\u03ac\u03bb\u03bb\u03b7\u03bb\u03b5\u03c2 \u03c5\u03bb\u03bf\u03c0\u03bf\u03b9\u03ae\u03c3\u03b5\u03b9\u03c2;\u00bb.<\/p>\n<h2 id=\"ai-proionta-pelati\">\u03a4\u03b9 \u03c3\u03b7\u03bc\u03b1\u03af\u03bd\u03b5\u03b9 \u03b3\u03b9\u03b1 AI \u03c0\u03c1\u03bf\u03ca\u03cc\u03bd\u03c4\u03b1 \u03c0\u03bf\u03c5 \u03b1\u03b3\u03b3\u03af\u03b6\u03bf\u03c5\u03bd \u03c4\u03bf\u03bd \u03c0\u03b5\u03bb\u03ac\u03c4\u03b7<\/h2>\n<p>\u03a3\u03c4\u03b1 customer-facing AI \u03c0\u03c1\u03bf\u03ca\u03cc\u03bd\u03c4\u03b1, \u03b7 \u03ba\u03b1\u03b8\u03c5\u03c3\u03c4\u03ad\u03c1\u03b7\u03c3\u03b7 \u03b5\u03af\u03bd\u03b1\u03b9 \u03bc\u03ad\u03c1\u03bf\u03c2 \u03c4\u03b7\u03c2 \u03b5\u03bc\u03c0\u03b5\u03b9\u03c1\u03af\u03b1\u03c2. \u0388\u03bd\u03b1\u03c2 assistant \u03c0\u03bf\u03c5 \u03b1\u03c0\u03b1\u03bd\u03c4\u03ac \u03b1\u03c1\u03b3\u03ac \u03bc\u03b5\u03b9\u03ce\u03bd\u03b5\u03b9 \u03c4\u03b7\u03bd \u03b5\u03bc\u03c0\u03b9\u03c3\u03c4\u03bf\u03c3\u03cd\u03bd\u03b7, \u03b5\u03b9\u03b4\u03b9\u03ba\u03ac \u03c3\u03b5 e-commerce \u03c0\u03b5\u03c1\u03b9\u03b2\u03ac\u03bb\u03bb\u03bf\u03bd \u03cc\u03c0\u03bf\u03c5 \u03bf \u03c7\u03c1\u03ae\u03c3\u03c4\u03b7\u03c2 \u03c3\u03c5\u03b3\u03ba\u03c1\u03af\u03bd\u03b5\u03b9 \u03c0\u03c1\u03bf\u03ca\u03cc\u03bd\u03c4\u03b1 \u03ae \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03ac\u03bc\u03b5\u03c3\u03b7 \u03ba\u03b1\u03b8\u03bf\u03b4\u03ae\u03b3\u03b7\u03c3\u03b7. \u0388\u03bd\u03b1 recommendation \u03ae search flow \u03c0\u03bf\u03c5 \u03b1\u03c1\u03b3\u03b5\u03af \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03c0\u03c1\u03bf\u03c3\u03b8\u03ad\u03c3\u03b5\u03b9 \u03c4\u03c1\u03b9\u03b2\u03ae, \u03b1\u03ba\u03cc\u03bc\u03b7 \u03ba\u03b9 \u03b1\u03bd \u03b7 \u03c0\u03bf\u03b9\u03cc\u03c4\u03b7\u03c4\u03b1 \u03c4\u03b7\u03c2 \u03b1\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7\u03c2 \u03b5\u03af\u03bd\u03b1\u03b9 \u03ba\u03b1\u03bb\u03ae.<\/p>\n<p>\u0397 \u03b2\u03b5\u03bb\u03c4\u03af\u03c9\u03c3\u03b7 \u03c4\u03bf\u03c5 inference backend \u03b4\u03b5\u03bd \u03b5\u03b3\u03b3\u03c5\u03ac\u03c4\u03b1\u03b9 \u03b1\u03c0\u03cc \u03bc\u03cc\u03bd\u03b7 \u03c4\u03b7\u03c2 \u03ba\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03bf business \u03b1\u03c0\u03bf\u03c4\u03ad\u03bb\u03b5\u03c3\u03bc\u03b1. \u03a7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03c3\u03c9\u03c3\u03c4\u03cc retrieval, \u03b1\u03be\u03b9\u03bf\u03bb\u03cc\u03b3\u03b7\u03c3\u03b7 \u03c0\u03bf\u03b9\u03cc\u03c4\u03b7\u03c4\u03b1\u03c2, \u03c0\u03c1\u03bf\u03c3\u03c4\u03b1\u03c3\u03af\u03b1 \u03c0\u03c1\u03bf\u03c3\u03c9\u03c0\u03b9\u03ba\u03ce\u03bd \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03c9\u03bd, monitoring \u03ba\u03b1\u03b9 \u03be\u03b5\u03ba\u03ac\u03b8\u03b1\u03c1\u03b7 \u03bc\u03ad\u03c4\u03c1\u03b7\u03c3\u03b7 \u03ba\u03cc\u03c3\u03c4\u03bf\u03c5\u03c2. \u0388\u03bd\u03b1 \u03bb\u03b9\u03b3\u03cc\u03c4\u03b5\u03c1\u03bf \u03c0\u03b5\u03c1\u03af\u03c0\u03bb\u03bf\u03ba\u03bf serving layer, \u03cc\u03bc\u03c9\u03c2, \u03b1\u03c6\u03ae\u03bd\u03b5\u03b9 \u03c0\u03b5\u03c1\u03b9\u03c3\u03c3\u03cc\u03c4\u03b5\u03c1\u03bf \u03c7\u03c1\u03cc\u03bd\u03bf \u03b3\u03b9\u03b1 \u03b1\u03c5\u03c4\u03ac \u03c4\u03b1 \u03bf\u03c5\u03c3\u03b9\u03b1\u03c3\u03c4\u03b9\u03ba\u03ac \u03c3\u03b7\u03bc\u03b5\u03af\u03b1.<\/p>\n<p>\u0397 \u03b5\u03c5\u03ba\u03b1\u03b9\u03c1\u03af\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03c0\u03b9\u03bf \u03b3\u03c1\u03ae\u03b3\u03bf\u03c1\u03b7 \u03ba\u03b1\u03b9 \u03c3\u03c5\u03c3\u03c4\u03b7\u03bc\u03b1\u03c4\u03b9\u03ba\u03ae \u03b1\u03be\u03b9\u03bf\u03bb\u03cc\u03b3\u03b7\u03c3\u03b7. \u0391\u03bd \u03bc\u03b9\u03b1 \u03bf\u03bc\u03ac\u03b4\u03b1 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b4\u03bf\u03ba\u03b9\u03bc\u03ac\u03c3\u03b5\u03b9 Qwen, Llama \u03ae \u03ac\u03bb\u03bb\u03b7 \u03c3\u03c5\u03bc\u03b2\u03b1\u03c4\u03ae \u03b1\u03c1\u03c7\u03b9\u03c4\u03b5\u03ba\u03c4\u03bf\u03bd\u03b9\u03ba\u03ae \u03c7\u03c9\u03c1\u03af\u03c2 \u03bc\u03b5\u03b3\u03ac\u03bb\u03bf porting \u03ba\u03cc\u03c3\u03c4\u03bf\u03c2, \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b1\u03bd\u03b1\u03b6\u03b7\u03c4\u03ae\u03c3\u03b5\u03b9 \u03bd\u03c9\u03c1\u03af\u03c4\u03b5\u03c1\u03b1 \u03c4\u03b7\u03bd \u03b9\u03c3\u03bf\u03c1\u03c1\u03bf\u03c0\u03af\u03b1 \u03b1\u03bd\u03ac\u03bc\u03b5\u03c3\u03b1 \u03c3\u03b5 \u03c0\u03bf\u03b9\u03cc\u03c4\u03b7\u03c4\u03b1, latency \u03ba\u03b1\u03b9 \u03b4\u03b1\u03c0\u03ac\u03bd\u03b7. \u0391\u03c5\u03c4\u03cc \u03b5\u03af\u03bd\u03b1\u03b9 \u03b9\u03b4\u03b9\u03b1\u03af\u03c4\u03b5\u03c1\u03b1 \u03c7\u03c1\u03ae\u03c3\u03b9\u03bc\u03bf \u03cc\u03c4\u03b1\u03bd \u03b7 \u03b5\u03bb\u03bb\u03b7\u03bd\u03b9\u03ba\u03ae \u03b3\u03bb\u03ce\u03c3\u03c3\u03b1, \u03c4\u03bf domain vocabulary \u03ae \u03bf \u03ba\u03b1\u03c4\u03ac\u03bb\u03bf\u03b3\u03bf\u03c2 \u03c0\u03c1\u03bf\u03ca\u03cc\u03bd\u03c4\u03c9\u03bd \u03b1\u03c0\u03b1\u03b9\u03c4\u03bf\u03cd\u03bd \u03c0\u03c1\u03bf\u03c3\u03b1\u03c1\u03bc\u03bf\u03c3\u03bc\u03ad\u03bd\u03b5\u03c2 \u03b4\u03bf\u03ba\u03b9\u03bc\u03ad\u03c2.<\/p>\n<p>\u0393\u03b9\u03b1 \u03bd\u03b1 \u03bf\u03c1\u03b3\u03b1\u03bd\u03c9\u03b8\u03b5\u03af \u03c3\u03c9\u03c3\u03c4\u03ac \u03b7 \u03bc\u03b5\u03c4\u03ac\u03b2\u03b1\u03c3\u03b7, \u03bf\u03b9 <a href=\"https:\/\/twodots.gr\/aftomatismoi-epicheiriseon-ai\/\">Business Automation &amp; AI<\/a> \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03be\u03b5\u03ba\u03b9\u03bd\u03bf\u03cd\u03bd \u03b1\u03c0\u03cc \u03c4\u03b7 \u03b4\u03b9\u03b1\u03b4\u03b9\u03ba\u03b1\u03c3\u03af\u03b1 \u03ba\u03b1\u03b9 \u03c4\u03b1 \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03b1, \u03cc\u03c7\u03b9 \u03b1\u03c0\u03cc \u03c4\u03b7\u03bd \u03b5\u03c0\u03b9\u03bb\u03bf\u03b3\u03ae framework. \u03a4\u03bf serving \u03b5\u03af\u03bd\u03b1\u03b9 \u03ad\u03bd\u03b1 \u03bc\u03ad\u03c1\u03bf\u03c2 \u03c4\u03bf\u03c5 \u03c3\u03c5\u03c3\u03c4\u03ae\u03bc\u03b1\u03c4\u03bf\u03c2\u00b7 \u03c4\u03b1 approval points, \u03c4\u03b1 fallbacks \u03ba\u03b1\u03b9 \u03b7 \u03bc\u03ad\u03c4\u03c1\u03b7\u03c3\u03b7 \u03c4\u03b7\u03c2 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ae\u03c2 \u03b1\u03be\u03af\u03b1\u03c2 \u03c0\u03b1\u03c1\u03b1\u03bc\u03ad\u03bd\u03bf\u03c5\u03bd \u03b5\u03be\u03af\u03c3\u03bf\u03c5 \u03c3\u03b7\u03bc\u03b1\u03bd\u03c4\u03b9\u03ba\u03ac.<\/p>\n<h2 id=\"benchmark-prin-paragogi\">\u03a4\u03b9 \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03bc\u03b5\u03c4\u03c1\u03ae\u03c3\u03b5\u03b9 \u03b7 \u03bf\u03bc\u03ac\u03b4\u03b1 \u03c0\u03c1\u03b9\u03bd \u03b1\u03c0\u03cc \u03c4\u03b7\u03bd \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae<\/h2>\n<div class=\"td-step-list\">\n<p class=\"td-step-list-title\">Benchmark \u03c4\u03bf\u03c5 Transformers backend \u03c3\u03b5 6 \u03b2\u03ae\u03bc\u03b1\u03c4\u03b1<\/p>\n<ol>\n<li><span class=\"td-step-kicker\">Step 1<\/span><strong>\u039f\u03c1\u03af\u03c3\u03c4\u03b5 \u03ad\u03bd\u03b1 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03cc workload.<\/strong>\n<p>\u03a7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03ae\u03c3\u03c4\u03b5 \u03b1\u03bd\u03c4\u03b9\u03c0\u03c1\u03bf\u03c3\u03c9\u03c0\u03b5\u03c5\u03c4\u03b9\u03ba\u03ac prompts, \u03bc\u03ae\u03ba\u03b7 context \u03ba\u03b1\u03b9 \u03b1\u03bd\u03b1\u03bc\u03b5\u03bd\u03cc\u03bc\u03b5\u03bd\u03b1 outputs \u03b1\u03c0\u03cc \u03c4\u03bf search, \u03c4\u03bf support \u03ae \u03c4\u03bf content workflow \u03c0\u03bf\u03c5 \u03b8\u03b1 \u03bb\u03b5\u03b9\u03c4\u03bf\u03c5\u03c1\u03b3\u03ae\u03c3\u03b5\u03b9 \u03c3\u03c4\u03b7\u03bd \u03c0\u03c1\u03ac\u03be\u03b7.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">Step 2<\/span><strong>\u039a\u03c1\u03b1\u03c4\u03ae\u03c3\u03c4\u03b5 \u03c3\u03c4\u03b1\u03b8\u03b5\u03c1\u03cc \u03c4\u03bf \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03ba\u03b1\u03b9 \u03c4\u03b9\u03c2 \u03c1\u03c5\u03b8\u03bc\u03af\u03c3\u03b5\u03b9\u03c2.<\/strong>\n<p>\u03a3\u03c5\u03b3\u03ba\u03c1\u03af\u03bd\u03b5\u03c4\u03b5 native \u03ba\u03b1\u03b9 Transformers \u03b4\u03b9\u03b1\u03b4\u03c1\u03bf\u03bc\u03ae \u03bc\u03b5 \u03af\u03b4\u03b9\u03bf checkpoint, quantization, sampling configuration \u03ba\u03b1\u03b9 hardware.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">Step 3<\/span><strong>\u039c\u03b5\u03c4\u03c1\u03ae\u03c3\u03c4\u03b5 latency \u03ba\u03b1\u03b9 throughput \u03bc\u03b1\u03b6\u03af.<\/strong>\n<p>\u039a\u03b1\u03c4\u03b1\u03b3\u03c1\u03ac\u03c8\u03c4\u03b5 time to first token, \u03c7\u03c1\u03cc\u03bd\u03bf \u03bf\u03bb\u03bf\u03ba\u03bb\u03ae\u03c1\u03c9\u03c3\u03b7\u03c2, tokens \u03b1\u03bd\u03ac \u03b4\u03b5\u03c5\u03c4\u03b5\u03c1\u03cc\u03bb\u03b5\u03c0\u03c4\u03bf \u03ba\u03b1\u03b9 \u03c3\u03c5\u03bc\u03c0\u03b5\u03c1\u03b9\u03c6\u03bf\u03c1\u03ac \u03c3\u03b5 \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03b5\u03c4\u03b9\u03ba\u03ac \u03b5\u03c0\u03af\u03c0\u03b5\u03b4\u03b1 concurrency.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">Step 4<\/span><strong>\u03a0\u03b1\u03c1\u03b1\u03ba\u03bf\u03bb\u03bf\u03c5\u03b8\u03ae\u03c3\u03c4\u03b5 GPU \u03ba\u03b1\u03b9 \u03bc\u03bd\u03ae\u03bc\u03b7.<\/strong>\n<p>\u0395\u03bb\u03ad\u03b3\u03be\u03c4\u03b5 utilization, KV cache pressure, \u03b1\u03c0\u03bf\u03c4\u03c5\u03c7\u03af\u03b5\u03c2 \u03bb\u03cc\u03b3\u03c9 \u03bc\u03bd\u03ae\u03bc\u03b7\u03c2 \u03ba\u03b1\u03b9 \u03c3\u03c4\u03b1\u03b8\u03b5\u03c1\u03cc\u03c4\u03b7\u03c4\u03b1 \u03c3\u03b5 \u03c0\u03b1\u03c1\u03b1\u03c4\u03b5\u03c4\u03b1\u03bc\u03ad\u03bd\u03bf load.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">Step 5<\/span><strong>\u0395\u03c0\u03b9\u03b2\u03b5\u03b2\u03b1\u03b9\u03ce\u03c3\u03c4\u03b5 \u03c4\u03b7\u03bd \u03c0\u03bf\u03b9\u03cc\u03c4\u03b7\u03c4\u03b1 \u03c4\u03c9\u03bd \u03b1\u03c0\u03b1\u03bd\u03c4\u03ae\u03c3\u03b5\u03c9\u03bd.<\/strong>\n<p>\u0397 \u03c4\u03b1\u03c7\u03cd\u03c4\u03b7\u03c4\u03b1 \u03b4\u03b5\u03bd \u03ad\u03c7\u03b5\u03b9 \u03b1\u03be\u03af\u03b1 \u03b1\u03bd \u03b1\u03bb\u03bb\u03ac\u03b6\u03b5\u03b9 \u03b7 \u03c3\u03c5\u03bc\u03c0\u03b5\u03c1\u03b9\u03c6\u03bf\u03c1\u03ac \u03c4\u03bf\u03c5 \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf\u03c5, \u03bc\u03b5\u03b9\u03ce\u03bd\u03b5\u03c4\u03b1\u03b9 \u03b7 \u03b1\u03ba\u03c1\u03af\u03b2\u03b5\u03b9\u03b1 \u03ae \u03b1\u03c0\u03bf\u03c4\u03c5\u03b3\u03c7\u03ac\u03bd\u03bf\u03c5\u03bd \u03c4\u03b1 guardrails \u03c4\u03bf\u03c5 workflow.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">Step 6<\/span><strong>\u03a5\u03c0\u03bf\u03bb\u03bf\u03b3\u03af\u03c3\u03c4\u03b5 \u03ba\u03cc\u03c3\u03c4\u03bf\u03c2 \u03b1\u03bd\u03ac \u03c7\u03c1\u03ae\u03c3\u03b9\u03bc\u03b7 \u03b5\u03c1\u03b3\u03b1\u03c3\u03af\u03b1.<\/strong>\n<p>\u03a3\u03c5\u03bd\u03b4\u03ad\u03c3\u03c4\u03b5 \u03c4\u03b7 \u03b4\u03b1\u03c0\u03ac\u03bd\u03b7 \u03c5\u03c0\u03bf\u03b4\u03bf\u03bc\u03ae\u03c2 \u03bc\u03b5 \u03bf\u03bb\u03bf\u03ba\u03bb\u03b7\u03c1\u03c9\u03bc\u03ad\u03bd\u03b1, \u03c0\u03bf\u03b9\u03bf\u03c4\u03b9\u03ba\u03ac \u03b1\u03b9\u03c4\u03ae\u03bc\u03b1\u03c4\u03b1 \u03ba\u03b1\u03b9 \u03cc\u03c7\u03b9 \u03bc\u03cc\u03bd\u03bf \u03bc\u03b5 \u03b1\u03ba\u03b1\u03c4\u03ad\u03c1\u03b3\u03b1\u03c3\u03c4\u03b1 tokens \u03ae \u03bc\u03ad\u03b3\u03b9\u03c3\u03c4\u03bf throughput.<\/p>\n<\/li>\n<\/ol>\n<\/div>\n<p>\u03a4\u03bf \u03b1\u03c0\u03bf\u03c4\u03ad\u03bb\u03b5\u03c3\u03bc\u03b1 \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03bf\u03b4\u03b7\u03b3\u03b5\u03af \u03c3\u03b5 \u03b1\u03c0\u03cc\u03c6\u03b1\u03c3\u03b7 \u03bc\u03b5 \u03c3\u03b1\u03c6\u03ad\u03c2 \u03cc\u03c1\u03b9\u03bf: \u03c0\u03bf\u03b9\u03bf configuration \u03ba\u03b1\u03bb\u03cd\u03c0\u03c4\u03b5\u03b9 \u03c4\u03bf SLA, \u03c0\u03bf\u03b9\u03bf \u03b5\u03af\u03bd\u03b1\u03b9 \u03c4\u03bf \u03ba\u03cc\u03c3\u03c4\u03bf\u03c2 \u03b1\u03bd\u03ac \u03b1\u03af\u03c4\u03b7\u03bc\u03b1 \u03ba\u03b1\u03b9 \u03c0\u03cc\u03c4\u03b5 \u03b3\u03af\u03bd\u03b5\u03c4\u03b1\u03b9 fallback \u03c3\u03b5 \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03b5\u03c4\u03b9\u03ba\u03cc \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03ae \u03bc\u03b9\u03ba\u03c1\u03cc\u03c4\u03b5\u03c1\u03bf context. \u0388\u03c4\u03c3\u03b9 \u03c4\u03bf benchmark \u03b3\u03af\u03bd\u03b5\u03c4\u03b1\u03b9 \u03b5\u03c1\u03b3\u03b1\u03bb\u03b5\u03af\u03bf \u03bb\u03b5\u03b9\u03c4\u03bf\u03c5\u03c1\u03b3\u03af\u03b1\u03c2 \u03ba\u03b1\u03b9 \u03cc\u03c7\u03b9 \u03c0\u03b1\u03c1\u03bf\u03c5\u03c3\u03af\u03b1\u03c3\u03b7 \u03b5\u03bd\u03cc\u03c2 \u03b5\u03bd\u03c4\u03c5\u03c0\u03c9\u03c3\u03b9\u03b1\u03ba\u03bf\u03cd \u03b1\u03c1\u03b9\u03b8\u03bc\u03bf\u03cd.<\/p>\n<h2 id=\"oria-kai-prosochi\">\u03a0\u03bf\u03cd \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03c0\u03c1\u03bf\u03c3\u03bf\u03c7\u03ae \u03c0\u03c1\u03b9\u03bd \u03b1\u03c0\u03cc \u03c4\u03b7\u03bd \u03c5\u03b9\u03bf\u03b8\u03ad\u03c4\u03b7\u03c3\u03b7<\/h2>\n<p>\u0397 \u03b1\u03bd\u03b1\u03ba\u03bf\u03af\u03bd\u03c9\u03c3\u03b7 \u03b4\u03b5\u03bd \u03c3\u03b7\u03bc\u03b1\u03af\u03bd\u03b5\u03b9 \u03cc\u03c4\u03b9 \u03ba\u03ac\u03b8\u03b5 AI stack \u03b3\u03af\u03bd\u03b5\u03c4\u03b1\u03b9 \u03b1\u03c5\u03c4\u03cc\u03bc\u03b1\u03c4\u03b1 \u03c6\u03b8\u03b7\u03bd\u03cc \u03ba\u03b1\u03b9 \u03b3\u03c1\u03ae\u03b3\u03bf\u03c1\u03bf. \u03a0\u03c1\u03ce\u03c4\u03bf\u03bd, \u03b7 \u03c3\u03c5\u03bc\u03b2\u03b1\u03c4\u03cc\u03c4\u03b7\u03c4\u03b1 \u03c4\u03bf\u03c5 \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf\u03c5 \u03ad\u03c7\u03b5\u03b9 \u03c3\u03b7\u03bc\u03b1\u03c3\u03af\u03b1. \u0397 Hugging Face \u03c3\u03b7\u03bc\u03b5\u03b9\u03ce\u03bd\u03b5\u03b9 \u03cc\u03c4\u03b9 \u03bf\u03b9 \u03b1\u03c1\u03c7\u03b9\u03c4\u03b5\u03ba\u03c4\u03bf\u03bd\u03b9\u03ba\u03ad\u03c2 \u03bc\u03b5 linear attention \u03b4\u03b5\u03bd \u03c5\u03c0\u03bf\u03c3\u03c4\u03b7\u03c1\u03af\u03b6\u03bf\u03bd\u03c4\u03b1\u03b9 \u03b1\u03ba\u03cc\u03bc\u03b7 \u03b1\u03c0\u03cc \u03b1\u03c5\u03c4\u03ae \u03c4\u03b7 \u03b4\u03b9\u03b1\u03b4\u03c1\u03bf\u03bc\u03ae, \u03b5\u03bd\u03ce custom models \u03c4\u03c9\u03bd \u03bf\u03c0\u03bf\u03af\u03c9\u03bd \u03bf \u03ba\u03ce\u03b4\u03b9\u03ba\u03b1\u03c2 \u03b6\u03b5\u03b9 \u03c3\u03b5 Hub repository \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03bc\u03b7\u03bd \u03ad\u03c7\u03bf\u03c5\u03bd \u03b3\u03c1\u03b1\u03c6\u03c4\u03b5\u03af \u03bc\u03b5 \u03c4\u03bf\u03bd \u03b1\u03c0\u03b1\u03b9\u03c4\u03bf\u03cd\u03bc\u03b5\u03bd\u03bf \u03c3\u03c5\u03bc\u03b2\u03b1\u03c4\u03cc \u03c4\u03c1\u03cc\u03c0\u03bf.<\/p>\n<p>\u0394\u03b5\u03cd\u03c4\u03b5\u03c1\u03bf\u03bd, \u03c4\u03bf hardware \u03b5\u03be\u03b1\u03ba\u03bf\u03bb\u03bf\u03c5\u03b8\u03b5\u03af \u03bd\u03b1 \u03ba\u03b1\u03b8\u03bf\u03c1\u03af\u03b6\u03b5\u03b9 \u03c4\u03bf \u03c0\u03bb\u03b1\u03af\u03c3\u03b9\u03bf. \u0388\u03bd\u03b1 4B dense \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03c3\u03b5 \u03bc\u03af\u03b1 GPU \u03ba\u03b1\u03b9 \u03ad\u03bd\u03b1 235B MoE \u03c3\u03b5 \u03ba\u03cc\u03bc\u03b2\u03bf \u03bc\u03b5 \u03bf\u03ba\u03c4\u03ce H100 \u03b4\u03b5\u03bd \u03ad\u03c7\u03bf\u03c5\u03bd \u03c4\u03bf \u03af\u03b4\u03b9\u03bf operational \u03c0\u03c1\u03bf\u03c6\u03af\u03bb. \u03a4\u03c1\u03af\u03c4\u03bf\u03bd, \u03ad\u03bd\u03b1 flag \u03b4\u03b5\u03bd \u03b1\u03bd\u03c4\u03b9\u03ba\u03b1\u03b8\u03b9\u03c3\u03c4\u03ac capacity planning, observability, version pinning, rollback \u03ba\u03b1\u03b9 \u03b4\u03bf\u03ba\u03b9\u03bc\u03ad\u03c2 \u03b1\u03bd\u03c4\u03bf\u03c7\u03ae\u03c2.<\/p>\n<p>\u039f\u03b9 \u03bf\u03bc\u03ac\u03b4\u03b5\u03c2 \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03b5\u03c0\u03af\u03c3\u03b7\u03c2 \u03bd\u03b1 \u03be\u03b5\u03c7\u03c9\u03c1\u03af\u03b6\u03bf\u03c5\u03bd \u03c4\u03b1 \u03b5\u03c0\u03b1\u03bb\u03b7\u03b8\u03b5\u03c5\u03bc\u03ad\u03bd\u03b1 \u03b1\u03c0\u03bf\u03c4\u03b5\u03bb\u03ad\u03c3\u03bc\u03b1\u03c4\u03b1 \u03b1\u03c0\u03cc \u03c4\u03b9\u03c2 \u03b3\u03b5\u03bd\u03b9\u03ba\u03b5\u03cd\u03c3\u03b5\u03b9\u03c2. \u0397 \u03b4\u03b7\u03bc\u03bf\u03c3\u03af\u03b5\u03c5\u03c3\u03b7 \u03b4\u03af\u03bd\u03b5\u03b9 \u03c4\u03b5\u03c7\u03bd\u03b9\u03ba\u03cc \u03c0\u03bb\u03b1\u03af\u03c3\u03b9\u03bf \u03ba\u03b1\u03b9 reproducible runner, \u03b1\u03bb\u03bb\u03ac \u03b4\u03b5\u03bd \u03b4\u03b9\u03ba\u03b1\u03b9\u03bf\u03bb\u03bf\u03b3\u03b5\u03af \u03ad\u03bd\u03b1 \u03ba\u03b1\u03b8\u03bf\u03bb\u03b9\u03ba\u03cc \u03c0\u03bf\u03c3\u03bf\u03c3\u03c4\u03cc \u03b2\u03b5\u03bb\u03c4\u03af\u03c9\u03c3\u03b7\u03c2 \u03b3\u03b9\u03b1 \u03ba\u03ac\u03b8\u03b5 \u03b5\u03c0\u03b9\u03c7\u03b5\u03af\u03c1\u03b7\u03c3\u03b7. \u0397 \u03b1\u03c3\u03c6\u03b1\u03bb\u03ae\u03c2 \u03b1\u03c0\u03cc\u03c6\u03b1\u03c3\u03b7 \u03b2\u03b1\u03c3\u03af\u03b6\u03b5\u03c4\u03b1\u03b9 \u03c3\u03b5 \u03b5\u03c3\u03c9\u03c4\u03b5\u03c1\u03b9\u03ba\u03cc benchmark \u03c0\u03ac\u03bd\u03c9 \u03c3\u03c4\u03b1 \u03b4\u03b9\u03ba\u03ac \u03c4\u03b7\u03c2 \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03b1 \u03ba\u03b1\u03b9 \u03c3\u03c4\u03bf\u03c5\u03c2 \u03b4\u03b9\u03ba\u03bf\u03cd\u03c2 \u03c4\u03b7\u03c2 \u03c3\u03c4\u03cc\u03c7\u03bf\u03c5\u03c2.<\/p>\n<h2 id=\"symperasma-elliniki-agora\">\u03a4\u03bf \u03c3\u03c5\u03bc\u03c0\u03ad\u03c1\u03b1\u03c3\u03bc\u03b1 \u03b3\u03b9\u03b1 \u03c4\u03b7\u03bd \u03b5\u03bb\u03bb\u03b7\u03bd\u03b9\u03ba\u03ae \u03b1\u03b3\u03bf\u03c1\u03ac<\/h2>\n<p>\u0393\u03b9\u03b1 \u03c4\u03b9\u03c2 \u03b5\u03bb\u03bb\u03b7\u03bd\u03b9\u03ba\u03ad\u03c2 \u03b5\u03c0\u03b9\u03c7\u03b5\u03b9\u03c1\u03ae\u03c3\u03b5\u03b9\u03c2 \u03c0\u03bf\u03c5 \u03c0\u03b5\u03c1\u03bd\u03bf\u03cd\u03bd \u03b1\u03c0\u03cc AI \u03b4\u03bf\u03ba\u03b9\u03bc\u03ad\u03c2 \u03c3\u03b5 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ad\u03c2 \u03c5\u03c0\u03b7\u03c1\u03b5\u03c3\u03af\u03b5\u03c2, \u03b7 \u03b5\u03be\u03ad\u03bb\u03b9\u03be\u03b7 vLLM \u03ba\u03b1\u03b9 Transformers \u03b5\u03af\u03bd\u03b1\u03b9 \u03c3\u03b7\u03bc\u03ac\u03b4\u03b9 \u03c9\u03c1\u03af\u03bc\u03b1\u03bd\u03c3\u03b7\u03c2 \u03c4\u03bf\u03c5 \u03bf\u03b9\u03ba\u03bf\u03c3\u03c5\u03c3\u03c4\u03ae\u03bc\u03b1\u03c4\u03bf\u03c2. \u03a4\u03b1 frameworks \u03b4\u03b5\u03bd \u03bb\u03cd\u03bd\u03bf\u03c5\u03bd \u03bc\u03cc\u03bd\u03b1 \u03c4\u03bf\u03c5\u03c2 \u03c4\u03b7 \u03c3\u03c4\u03c1\u03b1\u03c4\u03b7\u03b3\u03b9\u03ba\u03ae, \u03b1\u03bb\u03bb\u03ac \u03bc\u03c0\u03bf\u03c1\u03bf\u03cd\u03bd \u03bd\u03b1 \u03bc\u03b5\u03b9\u03ce\u03c3\u03bf\u03c5\u03bd \u03c4\u03b7\u03bd \u03c4\u03b5\u03c7\u03bd\u03b9\u03ba\u03ae \u03c4\u03c1\u03b9\u03b2\u03ae \u03b1\u03bd\u03ac\u03bc\u03b5\u03c3\u03b1 \u03c3\u03c4\u03b7\u03bd \u03b5\u03c0\u03b9\u03bb\u03bf\u03b3\u03ae \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf\u03c5 \u03ba\u03b1\u03b9 \u03c3\u03c4\u03b7\u03bd \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03b9\u03ba\u03ae \u03c7\u03c1\u03ae\u03c3\u03b7 \u03c4\u03bf\u03c5.<\/p>\n<p>\u0397 \u03c3\u03c9\u03c3\u03c4\u03ae \u03b5\u03c1\u03ce\u03c4\u03b7\u03c3\u03b7 \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u00ab\u03bd\u03b1 \u03b2\u03ac\u03bb\u03bf\u03c5\u03bc\u03b5 AI \u03b5\u03c0\u03b5\u03b9\u03b4\u03ae \u03ad\u03b3\u03b9\u03bd\u03b5 \u03c0\u03b9\u03bf \u03b3\u03c1\u03ae\u03b3\u03bf\u03c1\u03bf;\u00bb. \u0395\u03af\u03bd\u03b1\u03b9 \u00ab\u03c3\u03b5 \u03c0\u03bf\u03b9\u03bf \u03c3\u03b7\u03bc\u03b5\u03af\u03bf \u03c4\u03b7\u03c2 \u03b5\u03bc\u03c0\u03b5\u03b9\u03c1\u03af\u03b1\u03c2 \u03c0\u03b5\u03bb\u03ac\u03c4\u03b7 \u03ae \u03c4\u03b7\u03c2 \u03b5\u03c3\u03c9\u03c4\u03b5\u03c1\u03b9\u03ba\u03ae\u03c2 \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03b9\u03ba\u03cc\u03c4\u03b7\u03c4\u03b1\u03c2 \u03b1\u03be\u03af\u03b6\u03b5\u03b9 \u03bd\u03b1 \u03b5\u03c0\u03b5\u03bd\u03b4\u03cd\u03c3\u03bf\u03c5\u03bc\u03b5, \u03c4\u03ce\u03c1\u03b1 \u03c0\u03bf\u03c5 \u03b7 \u03b1\u03be\u03b9\u03bf\u03bb\u03cc\u03b3\u03b7\u03c3\u03b7 \u03ba\u03b1\u03b9 \u03c4\u03bf serving \u03b3\u03af\u03bd\u03bf\u03bd\u03c4\u03b1\u03b9 \u03c0\u03b9\u03bf \u03b5\u03c5\u03ad\u03bb\u03b9\u03ba\u03c4\u03b1;\u00bb. \u0393\u03b9\u03b1 \u03ad\u03bd\u03b1 brand \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03ba\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03b7 \u03b1\u03bd\u03b1\u03b6\u03ae\u03c4\u03b7\u03c3\u03b7, \u03b3\u03b9\u03b1 \u03ad\u03bd\u03b1 e-shop \u03c0\u03b9\u03bf \u03c7\u03c1\u03ae\u03c3\u03b9\u03bc\u03b7 \u03ba\u03b1\u03b8\u03bf\u03b4\u03ae\u03b3\u03b7\u03c3\u03b7 \u03b1\u03b3\u03bf\u03c1\u03ac\u03c2 \u03ba\u03b1\u03b9 \u03b3\u03b9\u03b1 \u03bc\u03b9\u03b1 \u03bf\u03bc\u03ac\u03b4\u03b1 marketing \u03c0\u03b9\u03bf \u03c3\u03c4\u03b1\u03b8\u03b5\u03c1\u03cc content workflow \u03bc\u03b5 \u03b1\u03bd\u03b8\u03c1\u03ce\u03c0\u03b9\u03bd\u03bf \u03ad\u03bb\u03b5\u03b3\u03c7\u03bf.<\/p>\n<p>\u0397 \u03c4\u03b5\u03c7\u03bd\u03b9\u03ba\u03ae \u03c0\u03c1\u03cc\u03bf\u03b4\u03bf\u03c2 \u03b1\u03c0\u03bf\u03ba\u03c4\u03ac \u03b5\u03c0\u03b9\u03c7\u03b5\u03b9\u03c1\u03b7\u03bc\u03b1\u03c4\u03b9\u03ba\u03ae \u03b1\u03be\u03af\u03b1 \u03cc\u03c4\u03b1\u03bd \u03c3\u03c5\u03bd\u03b4\u03ad\u03b5\u03c4\u03b1\u03b9 \u03bc\u03b5 \u03ba\u03b1\u03b8\u03b1\u03c1\u03cc use case, \u03bc\u03b5\u03c4\u03c1\u03ae\u03c3\u03b9\u03bc\u03b1 KPIs \u03ba\u03b1\u03b9 \u03b5\u03bc\u03c0\u03b5\u03b9\u03c1\u03af\u03b1 \u03c7\u03c1\u03ae\u03c3\u03c4\u03b7 \u03c0\u03bf\u03c5 \u03cc\u03bd\u03c4\u03c9\u03c2 \u03b2\u03b5\u03bb\u03c4\u03b9\u03ce\u03bd\u03b5\u03c4\u03b1\u03b9. \u0397 native-speed \u03b4\u03b9\u03b1\u03b4\u03c1\u03bf\u03bc\u03ae \u03b1\u03be\u03af\u03b6\u03b5\u03b9 \u03b4\u03bf\u03ba\u03b9\u03bc\u03ae \u03b1\u03ba\u03c1\u03b9\u03b2\u03ce\u03c2 \u03b5\u03c0\u03b5\u03b9\u03b4\u03ae \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b1\u03c0\u03b5\u03bb\u03b5\u03c5\u03b8\u03b5\u03c1\u03ce\u03c3\u03b5\u03b9 \u03c7\u03c1\u03cc\u03bd\u03bf \u03b3\u03b9\u03b1 \u03b1\u03c5\u03c4\u03ae \u03c4\u03b7 \u03b4\u03bf\u03c5\u03bb\u03b5\u03b9\u03ac.<\/p>\n<section class=\"td-service-cta\">\n<div class=\"td-service-cta-content\">\n<p class=\"td-service-cta-eyebrow\">\u0391\u03c0\u03cc \u03c4\u03bf benchmark \u03c3\u03b5 \u03b5\u03bb\u03b5\u03b3\u03c7\u03cc\u03bc\u03b5\u03bd\u03b7 \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae<\/p>\n<h2 id=\"ai-workflows-me-metrisi\">AI workflows \u03bc\u03b5 \u03bc\u03ad\u03c4\u03c1\u03b7\u03c3\u03b7 \u03b1\u03c0\u03cc \u03c4\u03bf pilot \u03c3\u03c4\u03b7\u03bd \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae<\/h2>\n<p>\u0397 TWO DOTS \u03c7\u03b1\u03c1\u03c4\u03bf\u03b3\u03c1\u03b1\u03c6\u03b5\u03af \u03c4\u03bf use case, \u03c4\u03b1 \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03b1, \u03c4\u03b9\u03c2 \u03c3\u03c5\u03bd\u03b4\u03ad\u03c3\u03b5\u03b9\u03c2, \u03c4\u03b1 approval points \u03ba\u03b1\u03b9 \u03c4\u03b1 KPIs \u03b5\u03bd\u03cc\u03c2 AI workflow \u03c0\u03c1\u03b9\u03bd \u03c0\u03b5\u03c1\u03ac\u03c3\u03b5\u03b9 \u03c3\u03b5 live \u03bb\u03b5\u03b9\u03c4\u03bf\u03c5\u03c1\u03b3\u03af\u03b1. \u0388\u03c4\u03c3\u03b9 \u03b7 \u03b5\u03c0\u03b9\u03bb\u03bf\u03b3\u03ae \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf\u03c5 \u03ba\u03b1\u03b9 \u03c5\u03c0\u03bf\u03b4\u03bf\u03bc\u03ae\u03c2 \u03c3\u03c5\u03bd\u03b4\u03ad\u03b5\u03c4\u03b1\u03b9 \u03bc\u03b5 \u03c7\u03c1\u03cc\u03bd\u03bf \u03b1\u03c0\u03cc\u03ba\u03c1\u03b9\u03c3\u03b7\u03c2, \u03c0\u03bf\u03b9\u03cc\u03c4\u03b7\u03c4\u03b1, \u03ba\u03cc\u03c3\u03c4\u03bf\u03c2 \u03ba\u03b1\u03b9 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ae \u03b1\u03be\u03af\u03b1 \u03b3\u03b9\u03b1 \u03c4\u03b7\u03bd \u03bf\u03bc\u03ac\u03b4\u03b1 \u03ae \u03c4\u03bf\u03bd \u03c0\u03b5\u03bb\u03ac\u03c4\u03b7.<\/p>\n<div class=\"td-service-cta-actions\"><a class=\"td-service-cta-button\" href=\"https:\/\/twodots.gr\/aftomatismoi-epicheiriseon-ai\/\">\u0394\u03b5\u03af\u03c4\u03b5 \u03c4\u03bf\u03c5\u03c2 \u0391\u03c5\u03c4\u03bf\u03bc\u03b1\u03c4\u03b9\u03c3\u03bc\u03bf\u03cd\u03c2 &amp; AI<\/a><\/div>\n<\/div>\n<\/section>\n<section id=\"sychnes-erotiseis\" class=\"td-faq-section\">\n<div class=\"td-faq\">\n<p class=\"td-faq-heading\">Frequently Asked Questions (FAQs)<\/p>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u03a4\u03b9 \u03b5\u03af\u03bd\u03b1\u03b9 \u03c4\u03bf vLLM;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u03a4\u03bf vLLM \u03b5\u03af\u03bd\u03b1\u03b9 inference \u03ba\u03b1\u03b9 serving engine \u03b3\u03b9\u03b1 \u03bc\u03b5\u03b3\u03ac\u03bb\u03b1 \u03b3\u03bb\u03c9\u03c3\u03c3\u03b9\u03ba\u03ac \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03b1. \u03a7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03b5\u03af \u03c4\u03b5\u03c7\u03bd\u03b9\u03ba\u03ad\u03c2 \u03cc\u03c0\u03c9\u03c2 continuous batching \u03ba\u03b1\u03b9 PagedAttention \u03b3\u03b9\u03b1 \u03c5\u03c8\u03b7\u03bb\u03cc throughput \u03ba\u03b1\u03b9 \u03ba\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03b7 \u03b1\u03be\u03b9\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b7 \u03c4\u03b7\u03c2 GPU.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u03a4\u03b9 \u03b1\u03bb\u03bb\u03ac\u03b6\u03b5\u03b9 \u03bc\u03b5 \u03c4\u03bf Transformers modeling backend;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u0395\u03c0\u03b9\u03c4\u03c1\u03ad\u03c0\u03b5\u03b9 \u03c3\u03b5 \u03c3\u03c5\u03bc\u03b2\u03b1\u03c4\u03ad\u03c2 \u03c5\u03bb\u03bf\u03c0\u03bf\u03b9\u03ae\u03c3\u03b5\u03b9\u03c2 \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03c9\u03bd \u03c4\u03c9\u03bd Transformers \u03bd\u03b1 \u03c4\u03c1\u03ad\u03c7\u03bf\u03c5\u03bd \u03bc\u03ad\u03c3\u03b1 \u03c3\u03c4\u03bf vLLM \u03ba\u03b1\u03b9 \u03bd\u03b1 \u03b1\u03be\u03b9\u03bf\u03c0\u03bf\u03b9\u03bf\u03cd\u03bd runtime \u03b2\u03b5\u03bb\u03c4\u03b9\u03c3\u03c4\u03bf\u03c0\u03bf\u03b9\u03ae\u03c3\u03b5\u03b9\u03c2, \u03c7\u03c9\u03c1\u03af\u03c2 \u03bd\u03b1 \u03b1\u03c0\u03b1\u03b9\u03c4\u03b5\u03af\u03c4\u03b1\u03b9 \u03be\u03b5\u03c7\u03c9\u03c1\u03b9\u03c3\u03c4\u03cc custom vLLM port \u03b3\u03b9\u03b1 \u03ba\u03ac\u03b8\u03b5 \u03b1\u03c1\u03c7\u03b9\u03c4\u03b5\u03ba\u03c4\u03bf\u03bd\u03b9\u03ba\u03ae.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u03a0\u03ce\u03c2 \u03b5\u03bd\u03b5\u03c1\u03b3\u03bf\u03c0\u03bf\u03b9\u03b5\u03af\u03c4\u03b1\u03b9 \u03c4\u03bf backend;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u03a3\u03c4\u03bf online serving \u03c7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03b5\u03af\u03c4\u03b1\u03b9 \u03c4\u03bf <code>--model-impl transformers<\/code>. \u03a3\u03c4\u03bf Python API \u03bf\u03c1\u03af\u03b6\u03b5\u03c4\u03b1\u03b9 <code>model_impl=\"transformers\"<\/code>, \u03bc\u03b1\u03b6\u03af \u03bc\u03b5 \u03c4\u03b9\u03c2 \u03ba\u03b1\u03c4\u03ac\u03bb\u03bb\u03b7\u03bb\u03b5\u03c2 \u03c1\u03c5\u03b8\u03bc\u03af\u03c3\u03b5\u03b9\u03c2 parallelism \u03ba\u03b1\u03b9 serving.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u03a0\u03bf\u03b9\u03b1 Qwen3 \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03b1 \u03b4\u03bf\u03ba\u03b9\u03bc\u03ac\u03c3\u03c4\u03b7\u03ba\u03b1\u03bd;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u0397 Hugging Face \u03c0\u03b1\u03c1\u03bf\u03c5\u03c3\u03af\u03b1\u03c3\u03b5 Qwen3-4B \u03c3\u03b5 \u03bc\u03af\u03b1 GPU, Qwen3-32B \u03bc\u03b5 tensor parallelism \u03c3\u03b5 \u03b4\u03cd\u03bf GPUs \u03ba\u03b1\u03b9 Qwen3-235B-A22B FP8 MoE \u03bc\u03b5 data \u03ba\u03b1\u03b9 expert parallelism \u03c3\u03b5 \u03bf\u03ba\u03c4\u03ce H100 GPUs.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u03a5\u03c0\u03bf\u03c3\u03c4\u03b7\u03c1\u03af\u03b6\u03bf\u03bd\u03c4\u03b1\u03b9 \u03cc\u03bb\u03b1 \u03c4\u03b1 Hugging Face \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03b1;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u038c\u03c7\u03b9. \u0397 \u03c3\u03c5\u03bc\u03b2\u03b1\u03c4\u03cc\u03c4\u03b7\u03c4\u03b1 \u03b5\u03be\u03b1\u03c1\u03c4\u03ac\u03c4\u03b1\u03b9 \u03b1\u03c0\u03cc \u03c4\u03b7\u03bd \u03b1\u03c1\u03c7\u03b9\u03c4\u03b5\u03ba\u03c4\u03bf\u03bd\u03b9\u03ba\u03ae \u03ba\u03b1\u03b9 \u03c4\u03bf\u03bd \u03c4\u03c1\u03cc\u03c0\u03bf \u03c5\u03bb\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b7\u03c2. \u0397 \u03b1\u03bd\u03b1\u03ba\u03bf\u03af\u03bd\u03c9\u03c3\u03b7 \u03b1\u03bd\u03b1\u03c6\u03ad\u03c1\u03b5\u03b9 \u03cc\u03c4\u03b9 linear-attention \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03b1 \u03b4\u03b5\u03bd \u03c5\u03c0\u03bf\u03c3\u03c4\u03b7\u03c1\u03af\u03b6\u03bf\u03bd\u03c4\u03b1\u03b9 \u03b1\u03ba\u03cc\u03bc\u03b7 \u03ba\u03b1\u03b9 \u03cc\u03c4\u03b9 \u03bf\u03c1\u03b9\u03c3\u03bc\u03ad\u03bd\u03b1 custom Hub models \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03bc\u03b7\u03bd \u03bb\u03b5\u03b9\u03c4\u03bf\u03c5\u03c1\u03b3\u03bf\u03cd\u03bd.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u039c\u03b5\u03b9\u03ce\u03bd\u03b5\u03c4\u03b1\u03b9 \u03b1\u03c5\u03c4\u03cc\u03bc\u03b1\u03c4\u03b1 \u03c4\u03bf \u03ba\u03cc\u03c3\u03c4\u03bf\u03c2 AI;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u038c\u03c7\u03b9. \u0397 \u03ba\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03b7 \u03b1\u03be\u03b9\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b7 \u03c5\u03c0\u03bf\u03b4\u03bf\u03bc\u03ae\u03c2 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b2\u03bf\u03b7\u03b8\u03ae\u03c3\u03b5\u03b9, \u03b1\u03bb\u03bb\u03ac \u03c4\u03bf \u03ba\u03cc\u03c3\u03c4\u03bf\u03c2 \u03b5\u03be\u03b1\u03c1\u03c4\u03ac\u03c4\u03b1\u03b9 \u03b1\u03c0\u03cc checkpoint, quantization, traffic, \u03bc\u03ae\u03ba\u03bf\u03c2 context, concurrency, hardware \u03ba\u03b1\u03b9 \u03b1\u03c0\u03b1\u03b9\u03c4\u03ae\u03c3\u03b5\u03b9\u03c2 \u03c0\u03bf\u03b9\u03cc\u03c4\u03b7\u03c4\u03b1\u03c2.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">Why does it matter for an e-shop?;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u0388\u03bd\u03b1 e-shop \u03c0\u03bf\u03c5 \u03c7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03b5\u03af AI \u03c3\u03b5 \u03b1\u03bd\u03b1\u03b6\u03ae\u03c4\u03b7\u03c3\u03b7, \u03c0\u03c1\u03bf\u03c4\u03ac\u03c3\u03b5\u03b9\u03c2 \u03ae \u03c5\u03c0\u03bf\u03c3\u03c4\u03ae\u03c1\u03b9\u03be\u03b7 \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03b3\u03c1\u03ae\u03b3\u03bf\u03c1\u03b5\u03c2 \u03ba\u03b1\u03b9 \u03c3\u03c4\u03b1\u03b8\u03b5\u03c1\u03ad\u03c2 \u03b1\u03c0\u03b1\u03bd\u03c4\u03ae\u03c3\u03b5\u03b9\u03c2. \u0395\u03c5\u03ba\u03bf\u03bb\u03cc\u03c4\u03b5\u03c1\u03bf serving \u03b5\u03c0\u03b9\u03c4\u03c1\u03ad\u03c0\u03b5\u03b9 \u03c4\u03b1\u03c7\u03cd\u03c4\u03b5\u03c1\u03b7 \u03b1\u03be\u03b9\u03bf\u03bb\u03cc\u03b3\u03b7\u03c3\u03b7 \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03c9\u03bd, \u03b1\u03bb\u03bb\u03ac \u03b1\u03c0\u03b1\u03b9\u03c4\u03b5\u03af benchmark \u03bc\u03b5 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ac \u03b1\u03b9\u03c4\u03ae\u03bc\u03b1\u03c4\u03b1 \u03c0\u03b5\u03bb\u03b1\u03c4\u03ce\u03bd.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u03a0\u03bf\u03b9\u03bf \u03b5\u03af\u03bd\u03b1\u03b9 \u03c4\u03bf \u03c3\u03c9\u03c3\u03c4\u03cc \u03c0\u03c1\u03ce\u03c4\u03bf \u03b2\u03ae\u03bc\u03b1 \u03b3\u03b9\u03b1 \u03bc\u03b9\u03b1 \u03b5\u03c0\u03b9\u03c7\u03b5\u03af\u03c1\u03b7\u03c3\u03b7;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u039d\u03b1 \u03b5\u03c0\u03b9\u03bb\u03ad\u03be\u03b5\u03b9 \u03ad\u03bd\u03b1 \u03c3\u03c5\u03b3\u03ba\u03b5\u03ba\u03c1\u03b9\u03bc\u03ad\u03bd\u03bf workflow, \u03bd\u03b1 \u03bf\u03c1\u03af\u03c3\u03b5\u03b9 baseline \u03b3\u03b9\u03b1 \u03c0\u03bf\u03b9\u03cc\u03c4\u03b7\u03c4\u03b1, latency \u03ba\u03b1\u03b9 \u03ba\u03cc\u03c3\u03c4\u03bf\u03c2 \u03ba\u03b1\u03b9 \u03bd\u03b1 \u03c3\u03c5\u03b3\u03ba\u03c1\u03af\u03bd\u03b5\u03b9 \u03c4\u03b9\u03c2 \u03b4\u03cd\u03bf \u03b4\u03b9\u03b1\u03b4\u03c1\u03bf\u03bc\u03ad\u03c2 \u03bc\u03b5 \u03af\u03b4\u03b9\u03bf \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf, hardware \u03ba\u03b1\u03b9 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03cc \u03c6\u03bf\u03c1\u03c4\u03af\u03bf \u03c0\u03c1\u03b9\u03bd \u03b1\u03c0\u03cc \u03bf\u03c0\u03bf\u03b9\u03bf\u03b4\u03ae\u03c0\u03bf\u03c4\u03b5 rollout.<\/p>\n<\/div>\n<\/details>\n<\/div>\n<\/section>\n<div class=\"td-source-list\">\n<p id=\"piges\" class=\"td-source-list-title\">Sources<\/p>\n<ul>\n<li><a href=\"https:\/\/huggingface.co\/blog\/native-speed-vllm-transformers-backend\" target=\"_blank\" rel=\"noopener\">Native-speed vLLM Transformers modeling backend \u2014 Hugging Face<\/a><\/li>\n<li><a href=\"https:\/\/huggingface.co\/docs\/transformers\/community_integrations\/vllm\" target=\"_blank\" rel=\"noopener\">vLLM integration \u2014 Hugging Face Transformers documentation<\/a><\/li>\n<li><a href=\"https:\/\/docs.vllm.ai\/en\/latest\/models\/supported_models\/\" target=\"_blank\" rel=\"noopener\">Supported Models and Transformers backend \u2014 vLLM documentation<\/a><\/li>\n<\/ul>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>\u03a4\u03bf \u03bd\u03ad\u03bf Transformers backend \u03c4\u03bf\u03c5 vLLM \u03bc\u03b5\u03b9\u03ce\u03bd\u03b5\u03b9 \u03c4\u03bf custom porting \u03ba\u03b1\u03b9 \u03b2\u03bf\u03b7\u03b8\u03ac \u03c4\u03b9\u03c2 \u03bf\u03bc\u03ac\u03b4\u03b5\u03c2 \u03bd\u03b1 \u03b4\u03bf\u03ba\u03b9\u03bc\u03ac\u03b6\u03bf\u03c5\u03bd \u03b3\u03c1\u03b7\u03b3\u03bf\u03c1\u03cc\u03c4\u03b5\u03c1\u03bf, \u03c0\u03b9\u03bf \u03bc\u03b5\u03c4\u03c1\u03ae\u03c3\u03b9\u03bc\u03bf AI inference.<\/p>","protected":false},"author":1,"featured_media":85362,"comment_status":"open","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_gspb_post_css":"","footnotes":""},"categories":[40],"tags":[],"class_list":["post-84684","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-arthra"],"blocksy_meta":[],"_links":{"self":[{"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/posts\/84684","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/comments?post=84684"}],"version-history":[{"count":0,"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/posts\/84684\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/media\/85362"}],"wp:attachment":[{"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/media?parent=84684"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/categories?post=84684"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/twodots.gr\/en\/wp-json\/wp\/v2\/tags?post=84684"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}