{"id":89641,"date":"2026-08-25T15:53:14","date_gmt":"2026-08-25T12:53:14","guid":{"rendered":"https:\/\/twodots.gr\/?p=89641"},"modified":"2026-08-25T15:53:16","modified_gmt":"2026-08-25T12:53:16","slug":"dspark-speculative-decoding-ai-latency","status":"publish","type":"post","link":"https:\/\/twodots.gr\/hr\/dspark-speculative-decoding-ai-latency\/","title":{"rendered":"Speculative decoding \u03bc\u03b5 DSpark: \u03c0\u03ce\u03c2 \u03c4\u03bf AI \u03b1\u03c0\u03b1\u03bd\u03c4\u03ac \u03b3\u03c1\u03b7\u03b3\u03bf\u03c1\u03cc\u03c4\u03b5\u03c1\u03b1 \u03c7\u03c9\u03c1\u03af\u03c2 \u03bd\u03b1 \u03b1\u03bb\u03bb\u03ac\u03b6\u03b5\u03b9 \u03b1\u03c0\u03bf\u03c4\u03ad\u03bb\u03b5\u03c3\u03bc\u03b1"},"content":{"rendered":"<div class=\"td-article-lede\">\n<p><strong>\u03a4\u03bf speculative decoding \u03bc\u03b5 DSpark \u03b5\u03c0\u03b9\u03c4\u03b1\u03c7\u03cd\u03bd\u03b5\u03b9 \u03c4\u03b7\u03bd \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae tokens \u03c7\u03c9\u03c1\u03af\u03c2 \u03bd\u03b1 \u03b1\u03bd\u03c4\u03b9\u03ba\u03b1\u03b8\u03b9\u03c3\u03c4\u03ac \u03c4\u03bf LFM2.5 target model.<\/strong> \u0388\u03bd\u03b1\u03c2 \u03bc\u03b9\u03ba\u03c1\u03cc\u03c2 drafter \u03c0\u03c1\u03bf\u03c4\u03b5\u03af\u03bd\u03b5\u03b9 \u03bf\u03bb\u03cc\u03ba\u03bb\u03b7\u03c1\u03bf block, \u03c4\u03bf target \u03c4\u03bf \u03b5\u03bb\u03ad\u03b3\u03c7\u03b5\u03b9 \u03c3\u03b5 \u03ad\u03bd\u03b1 forward pass \u03ba\u03b1\u03b9 \u03ba\u03c1\u03b1\u03c4\u03ac \u03bc\u03cc\u03bd\u03bf \u03c4\u03b1 tokens \u03c0\u03bf\u03c5 \u03c3\u03c5\u03bc\u03c6\u03c9\u03bd\u03bf\u03cd\u03bd. \u039c\u03b5 greedy decoding \u03ba\u03b1\u03b9 temperature 0, \u03b7 \u03c4\u03b5\u03bb\u03b9\u03ba\u03ae \u03b1\u03ba\u03bf\u03bb\u03bf\u03c5\u03b8\u03af\u03b1 \u03c0\u03b1\u03c1\u03b1\u03bc\u03ad\u03bd\u03b5\u03b9 \u03af\u03b4\u03b9\u03b1 \u03bc\u03b5 \u03c4\u03bf target-only baseline\u00b7 \u03c4\u03bf \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03cc \u03cc\u03c6\u03b5\u03bb\u03bf\u03c2 \u03cc\u03bc\u03c9\u03c2 \u03b5\u03be\u03b1\u03c1\u03c4\u03ac\u03c4\u03b1\u03b9 \u03b1\u03c0\u03cc workload, hardware, backend \u03ba\u03b1\u03b9 acceptance rate.<\/p>\n<\/div>\n<div class=\"td-article-toc\">\n<div class=\"td-toc-title\">\u03a0\u03b5\u03c1\u03b9\u03b5\u03c7\u03cc\u03bc\u03b5\u03bd\u03b1<\/div>\n<ul>\n<li><a href=\"#decoding-simeio-symforisis\">\u0393\u03b9\u03b1\u03c4\u03af \u03c4\u03bf decoding \u03b3\u03af\u03bd\u03b5\u03c4\u03b1\u03b9 \u03c3\u03b7\u03bc\u03b5\u03af\u03bf \u03c3\u03c5\u03bc\u03c6\u03cc\u03c1\u03b7\u03c3\u03b7\u03c2<\/a><\/li>\n<li><a href=\"#pos-leitourgei-dspark\">\u03a0\u03ce\u03c2 \u03bb\u03b5\u03b9\u03c4\u03bf\u03c5\u03c1\u03b3\u03b5\u03af \u03c4\u03bf DSpark<\/a><\/li>\n<li><a href=\"#drafter-architektoniki\">\u03a4\u03b9 \u03c0\u03b5\u03c1\u03b9\u03ad\u03c7\u03b5\u03b9 \u03bf drafter<\/a><\/li>\n<li><a href=\"#ti-metrithike\">\u03a4\u03b9 \u03b1\u03ba\u03c1\u03b9\u03b2\u03ce\u03c2 \u03bc\u03b5\u03c4\u03c1\u03ae\u03b8\u03b7\u03ba\u03b5<\/a><\/li>\n<li><a href=\"#acceptance-rate\">\u0393\u03b9\u03b1\u03c4\u03af \u03bc\u03b5\u03c4\u03c1\u03ac \u03b7 acceptance rate<\/a><\/li>\n<li><a href=\"#apple-silicon-orio\">\u03a4\u03bf \u03cc\u03c1\u03b9\u03bf \u03c3\u03c4\u03bf Apple silicon<\/a><\/li>\n<li><a href=\"#agents-function-calling\">Agents \u03ba\u03b1\u03b9 function calling<\/a><\/li>\n<li><a href=\"#self-hosting-adeia\">Self-hosting, formats \u03ba\u03b1\u03b9 \u03ac\u03b4\u03b5\u03b9\u03b1<\/a><\/li>\n<li><a href=\"#evaluation-plan\">Evaluation plan \u03c0\u03c1\u03b9\u03bd \u03c4\u03b7\u03bd \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae<\/a><\/li>\n<li><a href=\"#pote-axizei\">\u03a0\u03cc\u03c4\u03b5 \u03b1\u03be\u03af\u03b6\u03b5\u03b9 \u03c4\u03bf DSpark<\/a><\/li>\n<li><a href=\"#epicheirimatiki-anagnosi\">\u0397 \u03c3\u03c9\u03c3\u03c4\u03ae \u03b5\u03c0\u03b9\u03c7\u03b5\u03b9\u03c1\u03b7\u03bc\u03b1\u03c4\u03b9\u03ba\u03ae \u03b1\u03bd\u03ac\u03b3\u03bd\u03c9\u03c3\u03b7<\/a><\/li>\n<\/ul>\n<\/div>\n<h2 id=\"decoding-simeio-symforisis\">\u0393\u03b9\u03b1\u03c4\u03af \u03c4\u03bf decoding \u03b3\u03af\u03bd\u03b5\u03c4\u03b1\u03b9 \u03c3\u03b7\u03bc\u03b5\u03af\u03bf \u03c3\u03c5\u03bc\u03c6\u03cc\u03c1\u03b7\u03c3\u03b7\u03c2<\/h2>\n<p>\u03a3\u03c4\u03bf autoregressive decoding, \u03c4\u03bf \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03c0\u03b1\u03c1\u03ac\u03b3\u03b5\u03b9 \u03ad\u03bd\u03b1 token, \u03b5\u03bd\u03b7\u03bc\u03b5\u03c1\u03ce\u03bd\u03b5\u03b9 \u03c4\u03b7\u03bd \u03ba\u03b1\u03c4\u03ac\u03c3\u03c4\u03b1\u03c3\u03ae \u03c4\u03bf\u03c5 \u03ba\u03b1\u03b9 \u03b5\u03c0\u03b1\u03bd\u03b1\u03bb\u03b1\u03bc\u03b2\u03ac\u03bd\u03b5\u03b9 \u03c4\u03b7 \u03b4\u03b9\u03b1\u03b4\u03b9\u03ba\u03b1\u03c3\u03af\u03b1. \u0397 \u03b1\u03ba\u03bf\u03bb\u03bf\u03c5\u03b8\u03af\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03c3\u03b5\u03b9\u03c1\u03b9\u03b1\u03ba\u03ae. \u0391\u03ba\u03cc\u03bc\u03b7 \u03ba\u03b1\u03b9 \u03cc\u03c4\u03b1\u03bd \u03bf \u03b5\u03c0\u03b9\u03c4\u03b1\u03c7\u03c5\u03bd\u03c4\u03ae\u03c2 \u03b4\u03b9\u03b1\u03b8\u03ad\u03c4\u03b5\u03b9 \u03bc\u03b5\u03b3\u03ac\u03bb\u03b7 \u03c5\u03c0\u03bf\u03bb\u03bf\u03b3\u03b9\u03c3\u03c4\u03b9\u03ba\u03ae \u03b9\u03c3\u03c7\u03cd, \u03ba\u03ac\u03b8\u03b5 \u03bd\u03ad\u03bf \u03b2\u03ae\u03bc\u03b1 \u03b1\u03c0\u03b1\u03b9\u03c4\u03b5\u03af \u03bc\u03b5\u03c4\u03b1\u03c6\u03bf\u03c1\u03ac \u03b2\u03b1\u03c1\u03ce\u03bd \u03ba\u03b1\u03b9 \u03c0\u03c1\u03cc\u03c3\u03b2\u03b1\u03c3\u03b7 \u03c3\u03c4\u03b7 \u03bc\u03bd\u03ae\u03bc\u03b7. \u0393\u03b9\u2019 \u03b1\u03c5\u03c4\u03cc \u03b7 Liquid AI \u03c0\u03b5\u03c1\u03b9\u03b3\u03c1\u03ac\u03c6\u03b5\u03b9 \u03c4\u03b7 \u03c6\u03ac\u03c3\u03b7 decoding \u03c9\u03c2 \u03ba\u03c5\u03c1\u03af\u03c9\u03c2 memory-bound \u03ba\u03b1\u03b9 \u03cc\u03c7\u03b9 \u03c9\u03c2 \u03b1\u03c0\u03bb\u03cc \u03c0\u03c1\u03cc\u03b2\u03bb\u03b7\u03bc\u03b1 \u03c0\u03b5\u03c1\u03b9\u03c3\u03c3\u03cc\u03c4\u03b5\u03c1\u03c9\u03bd FLOPS.<\/p>\n<p>\u0397 \u03ba\u03b1\u03b8\u03c5\u03c3\u03c4\u03ad\u03c1\u03b7\u03c3\u03b7 \u03b3\u03af\u03bd\u03b5\u03c4\u03b1\u03b9 \u03ac\u03bc\u03b5\u03c3\u03b1 \u03bf\u03c1\u03b1\u03c4\u03ae \u03c3\u03b5 local assistants, coding copilots \u03ba\u03b1\u03b9 agentic workflows. \u0388\u03bd\u03b1\u03c2 agent \u03c0\u03b1\u03c1\u03ac\u03b3\u03b5\u03b9 \u03c0\u03bb\u03ac\u03bd\u03bf, \u03b5\u03c0\u03b9\u03bb\u03ad\u03b3\u03b5\u03b9 \u03b5\u03c1\u03b3\u03b1\u03bb\u03b5\u03af\u03bf, \u03b4\u03b9\u03b1\u03b2\u03ac\u03b6\u03b5\u03b9 \u03b1\u03c0\u03bf\u03c4\u03ad\u03bb\u03b5\u03c3\u03bc\u03b1 \u03ba\u03b1\u03b9 \u03c3\u03c5\u03bd\u03b5\u03c7\u03af\u03b6\u03b5\u03b9. \u0397 latency \u03b5\u03c0\u03b1\u03bd\u03b1\u03bb\u03b1\u03bc\u03b2\u03ac\u03bd\u03b5\u03c4\u03b1\u03b9 \u03c0\u03c1\u03b9\u03bd \u03ba\u03b1\u03b9 \u03bc\u03b5\u03c4\u03ac \u03b1\u03c0\u03cc \u03ba\u03ac\u03b8\u03b5 tool call. \u0388\u03c4\u03c3\u03b9, \u03bc\u03b9\u03b1 \u03b2\u03b5\u03bb\u03c4\u03af\u03c9\u03c3\u03b7 \u03c3\u03c4\u03bf decode \u03b4\u03b5\u03bd \u03b1\u03c6\u03bf\u03c1\u03ac \u03bc\u03cc\u03bd\u03bf \u00ab\u03b3\u03c1\u03b7\u03b3\u03bf\u03c1\u03cc\u03c4\u03b5\u03c1\u03b7 \u03c0\u03bb\u03b7\u03ba\u03c4\u03c1\u03bf\u03bb\u03cc\u03b3\u03b7\u03c3\u03b7\u00bb, \u03b1\u03bb\u03bb\u03ac \u03c4\u03bf\u03bd \u03c3\u03c5\u03bd\u03bf\u03bb\u03b9\u03ba\u03cc \u03c7\u03c1\u03cc\u03bd\u03bf \u03bc\u03b9\u03b1\u03c2 \u03b5\u03c1\u03b3\u03b1\u03c3\u03af\u03b1\u03c2 \u03c3\u03b5 customer support, e-commerce \u03ae \u03b5\u03c3\u03c9\u03c4\u03b5\u03c1\u03b9\u03ba\u03ae \u03b1\u03c5\u03c4\u03bf\u03bc\u03b1\u03c4\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b7.<\/p>\n<p>\u03a4\u03bf DSpark \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u03bf \u03bc\u03cc\u03bd\u03bf\u03c2 \u03b4\u03c1\u03cc\u03bc\u03bf\u03c2 \u03b3\u03b9\u03b1 \u03ba\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03bf inference. \u03a4\u03b5\u03c7\u03bd\u03b9\u03ba\u03ad\u03c2 \u03cc\u03c0\u03c9\u03c2 optimized kernels, quantization \u03ba\u03b1\u03b9 native runtime integration \u03bc\u03c0\u03bf\u03c1\u03bf\u03cd\u03bd \u03b5\u03c0\u03af\u03c3\u03b7\u03c2 \u03bd\u03b1 \u03bc\u03b5\u03b9\u03ce\u03c3\u03bf\u03c5\u03bd \u03ba\u03b1\u03b8\u03c5\u03c3\u03c4\u03b5\u03c1\u03ae\u03c3\u03b5\u03b9\u03c2, \u03cc\u03c0\u03c9\u03c2 \u03b4\u03b5\u03af\u03c7\u03bd\u03b5\u03b9 \u03b7 \u03bc\u03b5\u03c4\u03ac\u03b2\u03b1\u03c3\u03b7 \u03c3\u03b5 <a href=\"https:\/\/twodots.gr\/vllm-transformers-native-speed-ai-inference\/\">native-speed AI inference \u03bc\u03b5 vLLM \u03ba\u03b1\u03b9 Transformers<\/a>. \u0397 \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03ac \u03b5\u03af\u03bd\u03b1\u03b9 \u03cc\u03c4\u03b9 \u03c4\u03bf speculative decoding \u03c3\u03c4\u03bf\u03c7\u03b5\u03cd\u03b5\u03b9 \u03b5\u03b9\u03b4\u03b9\u03ba\u03ac \u03c4\u03b1 \u03c3\u03b5\u03b9\u03c1\u03b9\u03b1\u03ba\u03ac decode steps, \u03c0\u03c1\u03bf\u03b2\u03bb\u03ad\u03c0\u03bf\u03bd\u03c4\u03b1\u03c2 \u03c0\u03b5\u03c1\u03b9\u03c3\u03c3\u03cc\u03c4\u03b5\u03c1\u03b1 \u03b1\u03c0\u03cc \u03ad\u03bd\u03b1 tokens \u03c0\u03c1\u03b9\u03bd \u03b1\u03c0\u03cc \u03c4\u03b7\u03bd \u03b5\u03c0\u03b1\u03bb\u03ae\u03b8\u03b5\u03c5\u03c3\u03b7.<\/p>\n<h2 id=\"pos-leitourgei-dspark\">\u03a0\u03ce\u03c2 \u03bb\u03b5\u03b9\u03c4\u03bf\u03c5\u03c1\u03b3\u03b5\u03af \u03c4\u03bf speculative decoding \u03c4\u03bf\u03c5 DSpark<\/h2>\n<p>\u03a4\u03bf DSpark \u03c4\u03bf\u03c0\u03bf\u03b8\u03b5\u03c4\u03b5\u03af \u03b4\u03af\u03c0\u03bb\u03b1 \u03c3\u03c4\u03bf target model \u03ad\u03bd\u03b1\u03bd \u03bc\u03b9\u03ba\u03c1\u03cc\u03c4\u03b5\u03c1\u03bf drafter \u03c0\u03b5\u03c1\u03af\u03c0\u03bf\u03c5 300 \u03b5\u03ba\u03b1\u03c4\u03bf\u03bc\u03bc\u03c5\u03c1\u03af\u03c9\u03bd \u03c0\u03b1\u03c1\u03b1\u03bc\u03ad\u03c4\u03c1\u03c9\u03bd. \u039f drafter \u03c0\u03c1\u03bf\u03c4\u03b5\u03af\u03bd\u03b5\u03b9 \u03ad\u03bd\u03b1 block \u03b5\u03bd\u03bd\u03ad\u03b1 \u03c5\u03c0\u03bf\u03c8\u03ae\u03c6\u03b9\u03c9\u03bd tokens. \u03a4\u03bf target model \u03c4\u03b1 \u03b5\u03c0\u03b1\u03bb\u03b7\u03b8\u03b5\u03cd\u03b5\u03b9 \u03bc\u03b1\u03b6\u03af \u03c3\u03b5 \u03ad\u03bd\u03b1 forward pass. \u038c\u03c3\u03b1 \u03c3\u03c5\u03bc\u03c6\u03c9\u03bd\u03bf\u03cd\u03bd \u03bc\u03b5 \u03c4\u03b7 \u03b4\u03b9\u03ba\u03ae \u03c4\u03bf\u03c5 \u03ba\u03b1\u03c4\u03b1\u03bd\u03bf\u03bc\u03ae \u03b3\u03af\u03bd\u03bf\u03bd\u03c4\u03b1\u03b9 \u03b1\u03c0\u03bf\u03b4\u03b5\u03ba\u03c4\u03ac\u00b7 \u03c3\u03c4\u03b7\u03bd \u03c0\u03c1\u03ce\u03c4\u03b7 \u03b1\u03c0\u03cc\u03c1\u03c1\u03b9\u03c8\u03b7, \u03c4\u03bf target \u03b2\u03ac\u03b6\u03b5\u03b9 \u03c4\u03bf \u03b4\u03b9\u03ba\u03cc \u03c4\u03bf\u03c5 token \u03ba\u03b1\u03b9 \u03b7 \u03bc\u03b7 \u03b5\u03c0\u03b1\u03bb\u03b7\u03b8\u03b5\u03c5\u03bc\u03ad\u03bd\u03b7 \u03c3\u03c5\u03bd\u03ad\u03c7\u03b5\u03b9\u03b1 \u03b1\u03c0\u03bf\u03c1\u03c1\u03af\u03c0\u03c4\u03b5\u03c4\u03b1\u03b9.<\/p>\n<p>\u0391\u03c5\u03c4\u03cc\u03c2 \u03bf \u03ad\u03bb\u03b5\u03b3\u03c7\u03bf\u03c2 \u03b5\u03af\u03bd\u03b1\u03b9 \u03bf \u03bb\u03cc\u03b3\u03bf\u03c2 \u03c0\u03bf\u03c5 \u03b7 \u03c4\u03b5\u03c7\u03bd\u03b9\u03ba\u03ae \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 exact. \u03a3\u03c4\u03bf greedy decoding, \u03ad\u03bd\u03b1 draft token \u03b5\u03ba\u03c0\u03ad\u03bc\u03c0\u03b5\u03c4\u03b1\u03b9 \u03bc\u03cc\u03bd\u03bf \u03cc\u03c4\u03b1\u03bd \u03c3\u03c5\u03bc\u03c0\u03af\u03c0\u03c4\u03b5\u03b9 \u03bc\u03b5 \u03c4\u03b7\u03bd \u03b5\u03c0\u03b9\u03bb\u03bf\u03b3\u03ae \u03c4\u03bf\u03c5 target. \u03a4\u03bf \u03bc\u03b9\u03ba\u03c1\u03cc \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03b4\u03b5\u03bd \u03b1\u03bb\u03bb\u03ac\u03b6\u03b5\u03b9 \u03c4\u03bf \u03ba\u03c1\u03b9\u03c4\u03ae\u03c1\u03b9\u03bf \u03ba\u03b1\u03b9 \u03b4\u03b5\u03bd \u03b5\u03c0\u03b9\u03bb\u03ad\u03b3\u03b5\u03b9 \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03b5\u03c4\u03b9\u03ba\u03ae \u03b1\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7. \u03a0\u03c1\u03bf\u03c3\u03c0\u03b1\u03b8\u03b5\u03af \u03bd\u03b1 \u03c0\u03c1\u03bf\u03b2\u03bb\u03ad\u03c8\u03b5\u03b9 \u03b5\u03ba \u03c4\u03c9\u03bd \u03c0\u03c1\u03bf\u03c4\u03ad\u03c1\u03c9\u03bd \u03c4\u03b7\u03bd \u03c0\u03bf\u03c1\u03b5\u03af\u03b1 \u03c0\u03bf\u03c5 \u03b8\u03b1 \u03b1\u03ba\u03bf\u03bb\u03bf\u03c5\u03b8\u03bf\u03cd\u03c3\u03b5 \u03bf\u03cd\u03c4\u03c9\u03c2 \u03ae \u03ac\u03bb\u03bb\u03c9\u03c2 \u03c4\u03bf target, \u03ce\u03c3\u03c4\u03b5 \u03bd\u03b1 \u03bc\u03b5\u03b9\u03c9\u03b8\u03bf\u03cd\u03bd \u03c4\u03b1 \u03be\u03b5\u03c7\u03c9\u03c1\u03b9\u03c3\u03c4\u03ac target forward passes.<\/p>\n<div class=\"td-comparison\">\n<p class=\"td-comparison-title\">Target-only decoding \u03ae DSpark;<\/p>\n<div class=\"td-comparison-cards td-comparison-cards--horizontal\">\n<div class=\"td-comparison-grid\">\n<div class=\"td-platform-card\">\n<p class=\"td-comparison-kicker\">Target-only<\/p>\n<h3>\u0388\u03bd\u03b1 token \u03b1\u03bd\u03ac decode step<\/h3>\n<p>\u03a4\u03bf LFM2.5 \u03b5\u03c0\u03b9\u03bb\u03ad\u03b3\u03b5\u03b9 \u03c4\u03bf \u03b5\u03c0\u03cc\u03bc\u03b5\u03bd\u03bf token, \u03b5\u03bd\u03b7\u03bc\u03b5\u03c1\u03ce\u03bd\u03b5\u03b9 \u03c4\u03bf state \u03ba\u03b1\u03b9 \u03b5\u03c0\u03b1\u03bd\u03b1\u03bb\u03b1\u03bc\u03b2\u03ac\u03bd\u03b5\u03b9. \u0397 \u03b4\u03b9\u03b1\u03b4\u03c1\u03bf\u03bc\u03ae \u03b5\u03af\u03bd\u03b1\u03b9 \u03b1\u03c0\u03bb\u03ae, \u03b1\u03bb\u03bb\u03ac \u03ba\u03ac\u03b8\u03b5 token \u03b1\u03c0\u03b1\u03b9\u03c4\u03b5\u03af \u03be\u03b5\u03c7\u03c9\u03c1\u03b9\u03c3\u03c4\u03cc \u03c3\u03b5\u03b9\u03c1\u03b9\u03b1\u03ba\u03cc \u03b2\u03ae\u03bc\u03b1.<\/p>\n<\/div>\n<div class=\"td-platform-card td-platform-card--navy\">\n<p class=\"td-comparison-kicker\">DSpark<\/p>\n<h3>Block \u03c0\u03c1\u03cc\u03b2\u03bb\u03b5\u03c8\u03b7\u03c2 \u03ba\u03b1\u03b9 \u03bc\u03b1\u03b6\u03b9\u03ba\u03cc\u03c2 \u03ad\u03bb\u03b5\u03b3\u03c7\u03bf\u03c2<\/h3>\n<p>\u039f drafter \u03c0\u03c1\u03bf\u03c4\u03b5\u03af\u03bd\u03b5\u03b9 \u03ad\u03c9\u03c2 \u03b5\u03bd\u03bd\u03ad\u03b1 tokens \u03ba\u03b1\u03b9 \u03c4\u03bf \u03af\u03b4\u03b9\u03bf target \u03c4\u03b1 \u03b5\u03c0\u03b1\u03bb\u03b7\u03b8\u03b5\u03cd\u03b5\u03b9 \u03bc\u03b1\u03b6\u03af. \u03a4\u03bf \u03ba\u03ad\u03c1\u03b4\u03bf\u03c2 \u03b1\u03c5\u03be\u03ac\u03bd\u03b5\u03c4\u03b1\u03b9 \u03cc\u03c4\u03b1\u03bd \u03b1\u03c1\u03ba\u03b5\u03c4\u03ad\u03c2 \u03b4\u03b9\u03b1\u03b4\u03bf\u03c7\u03b9\u03ba\u03ad\u03c2 \u03c0\u03c1\u03bf\u03c4\u03ac\u03c3\u03b5\u03b9\u03c2 \u03b3\u03af\u03bd\u03bf\u03bd\u03c4\u03b1\u03b9 \u03b1\u03c0\u03bf\u03b4\u03b5\u03ba\u03c4\u03ad\u03c2.<\/p>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<div class=\"td-article-note\">\n<p><strong>\u03a4\u03b5\u03c7\u03bd\u03b9\u03ba\u03ae \u03c3\u03c5\u03bd\u03b8\u03ae\u03ba\u03b7:<\/strong> \u03bf \u03b9\u03c3\u03c7\u03c5\u03c1\u03b9\u03c3\u03bc\u03cc\u03c2 \u03c0\u03b5\u03c1\u03af \u03c4\u03b1\u03c5\u03c4\u03cc\u03c3\u03b7\u03bc\u03b7\u03c2 \u03b5\u03be\u03cc\u03b4\u03bf\u03c5 \u03c3\u03c4\u03bf \u03c3\u03c5\u03b3\u03ba\u03b5\u03ba\u03c1\u03b9\u03bc\u03ad\u03bd\u03bf release \u03b1\u03c6\u03bf\u03c1\u03ac greedy decoding \u03bc\u03b5 temperature 0. \u0394\u03b5\u03bd \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03b5\u03c0\u03b5\u03ba\u03c4\u03b5\u03af\u03bd\u03b5\u03c4\u03b1\u03b9 \u03b1\u03c5\u03c4\u03cc\u03bc\u03b1\u03c4\u03b1 \u03c3\u03b5 \u03ba\u03ac\u03b8\u03b5 sampling configuration \u03c7\u03c9\u03c1\u03af\u03c2 \u03be\u03b5\u03c7\u03c9\u03c1\u03b9\u03c3\u03c4\u03cc \u03ad\u03bb\u03b5\u03b3\u03c7\u03bf.<\/p>\n<\/div>\n<h2 id=\"drafter-architektoniki\">\u03a4\u03b9 \u03c0\u03b5\u03c1\u03b9\u03ad\u03c7\u03b5\u03b9 \u03bf drafter \u03c4\u03c9\u03bd LFM2.5<\/h2>\n<p>\u0397 Liquid AI \u03ba\u03c5\u03ba\u03bb\u03bf\u03c6\u03cc\u03c1\u03b7\u03c3\u03b5 drafters \u03b3\u03b9\u03b1 \u03c4\u03b1 LFM2.5-1.2B-Instruct, LFM2.5-2.6B \u03ba\u03b1\u03b9 LFM2.5-8B-A1B. \u039f \u03c0\u03c1\u03ce\u03c4\u03bf\u03c2 \u03ad\u03c7\u03b5\u03b9 295,7 \u03b5\u03ba\u03b1\u03c4\u03bf\u03bc\u03bc\u03cd\u03c1\u03b9\u03b1 \u03c0\u03b1\u03c1\u03b1\u03bc\u03ad\u03c4\u03c1\u03bf\u03c5\u03c2, \u03b5\u03bd\u03ce \u03bf\u03b9 \u03ac\u03bb\u03bb\u03bf\u03b9 \u03b4\u03cd\u03bf 327,7 \u03b5\u03ba\u03b1\u03c4\u03bf\u03bc\u03bc\u03cd\u03c1\u03b9\u03b1. \u0397 \u03ba\u03bf\u03b9\u03bd\u03ae \u03c1\u03b1\u03c7\u03bf\u03ba\u03bf\u03ba\u03b1\u03bb\u03b9\u03ac \u03c0\u03b5\u03c1\u03b9\u03bb\u03b1\u03bc\u03b2\u03ac\u03bd\u03b5\u03b9 \u03c0\u03ad\u03bd\u03c4\u03b5 full-attention layers, hidden size 2.048, intermediate size 6.144 \u03ba\u03b1\u03b9 grouped-query attention \u03bc\u03b5 32 attention heads \u03ba\u03b1\u03b9 8 KV heads. \u03a4\u03bf block size \u03b5\u03af\u03bd\u03b1\u03b9 \u03b5\u03bd\u03bd\u03ad\u03b1.<\/p>\n<p>\u0397 \u03b1\u03c1\u03c7\u03b9\u03c4\u03b5\u03ba\u03c4\u03bf\u03bd\u03b9\u03ba\u03ae \u03c3\u03c5\u03bd\u03b4\u03c5\u03ac\u03b6\u03b5\u03b9 \u03c4\u03c1\u03af\u03b1 \u03c3\u03c4\u03bf\u03b9\u03c7\u03b5\u03af\u03b1. \u0388\u03bd\u03b1 DFlash-style parallel backbone, \u03b5\u03c0\u03b7\u03c1\u03b5\u03b1\u03c3\u03bc\u03ad\u03bd\u03bf \u03b1\u03c0\u03cc context features \u03c4\u03bf\u03c5 target, \u03c0\u03b1\u03c1\u03ac\u03b3\u03b5\u03b9 hidden states \u03b3\u03b9\u03b1 \u03cc\u03bb\u03b5\u03c2 \u03c4\u03b9\u03c2 draft \u03b8\u03ad\u03c3\u03b5\u03b9\u03c2. \u0388\u03bd\u03b1 \u03b5\u03bb\u03b1\u03c6\u03c1\u03cd sequential head, \u03bc\u03bf\u03bd\u03c4\u03b5\u03bb\u03bf\u03c0\u03bf\u03b9\u03b7\u03bc\u03ad\u03bd\u03bf \u03c9\u03c2 Markov chain \u03b1\u03bd\u03ac\u03bc\u03b5\u03c3\u03b1 \u03c3\u03b5 \u03b3\u03b5\u03b9\u03c4\u03bf\u03bd\u03b9\u03ba\u03ac tokens, \u03b5\u03c0\u03b1\u03bd\u03b1\u03c6\u03ad\u03c1\u03b5\u03b9 \u03b5\u03be\u03ac\u03c1\u03c4\u03b7\u03c3\u03b7 \u03bc\u03b5\u03c4\u03b1\u03be\u03cd \u03c4\u03c9\u03bd \u03c0\u03c1\u03bf\u03c4\u03ac\u03c3\u03b5\u03c9\u03bd. \u0388\u03bd\u03b1\u03c2 confidence-scheduled verifier \u03b5\u03ba\u03c4\u03b9\u03bc\u03ac \u03c0\u03bf\u03b9\u03b1 suffixes \u03b1\u03be\u03af\u03b6\u03b5\u03b9 \u03bd\u03b1 \u03b5\u03c0\u03b1\u03bb\u03b7\u03b8\u03b5\u03c5\u03c4\u03bf\u03cd\u03bd \u03ba\u03b1\u03b9 \u03ba\u03cc\u03b2\u03b5\u03b9 \u03b5\u03ba\u03b5\u03af\u03bd\u03b1 \u03bc\u03b5 \u03c7\u03b1\u03bc\u03b7\u03bb\u03ae \u03c0\u03b9\u03b8\u03b1\u03bd\u03cc\u03c4\u03b7\u03c4\u03b1 \u03b5\u03c0\u03b9\u03b2\u03af\u03c9\u03c3\u03b7\u03c2 \u03cc\u03c4\u03b1\u03bd \u03c4\u03bf \u03c0\u03b9\u03b8\u03b1\u03bd\u03cc \u03ba\u03cc\u03c3\u03c4\u03bf\u03c2 \u03be\u03b5\u03c0\u03b5\u03c1\u03bd\u03ac \u03c4\u03bf \u03cc\u03c6\u03b5\u03bb\u03bf\u03c2.<\/p>\n<p>\u039f drafter \u03b4\u03b5\u03bd \u03b1\u03bd\u03c4\u03b9\u03ba\u03b1\u03b8\u03b9\u03c3\u03c4\u03ac \u03c4\u03bf vocabulary \u03c4\u03bf\u03c5 target. \u03a3\u03c5\u03bd\u03b4\u03ad\u03b5\u03c4\u03b1\u03b9 \u03bc\u03b5 \u03c4\u03b1 embeddings \u03ba\u03b1\u03b9 \u03c4\u03bf LM head \u03c4\u03bf\u03c5 \u03b2\u03b1\u03c3\u03b9\u03ba\u03bf\u03cd \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf\u03c5. \u0391\u03c5\u03c4\u03cc \u03ba\u03c1\u03b1\u03c4\u03ac \u03c4\u03bf \u03c0\u03c1\u03cc\u03c3\u03b8\u03b5\u03c4\u03bf \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03c3\u03c7\u03b5\u03c4\u03b9\u03ba\u03ac \u03bc\u03b9\u03ba\u03c1\u03cc, \u03b1\u03bb\u03bb\u03ac \u03cc\u03c7\u03b9 \u03b4\u03c9\u03c1\u03b5\u03ac\u03bd: \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03b5\u03c0\u03b9\u03c0\u03bb\u03ad\u03bf\u03bd \u03bc\u03bd\u03ae\u03bc\u03b7, \u03b4\u03b5\u03cd\u03c4\u03b5\u03c1\u03bf checkpoint, \u03c3\u03c5\u03bc\u03b2\u03b1\u03c4\u03cc runtime \u03ba\u03b1\u03b9 monitoring. \u0397 \u03c4\u03b5\u03c7\u03bd\u03b9\u03ba\u03ae \u03b5\u03b9\u03ba\u03cc\u03bd\u03b1 \u03c3\u03c5\u03bc\u03c0\u03bb\u03b7\u03c1\u03ce\u03bd\u03b5\u03b9 \u03c4\u03b7\u03bd \u03b5\u03c5\u03c1\u03cd\u03c4\u03b5\u03c1\u03b7 \u03b1\u03bd\u03ac\u03bb\u03c5\u03c3\u03b7 \u03c4\u03bf\u03c5 <a href=\"https:\/\/twodots.gr\/lfm25-dspark-taxytero-ai-inference\/\">LFM2.5-DSpark \u03c9\u03c2 \u03b5\u03c0\u03b9\u03bb\u03bf\u03b3\u03ae\u03c2 \u03c4\u03b1\u03c7\u03cd\u03c4\u03b5\u03c1\u03bf\u03c5 AI inference<\/a>, \u03b5\u03b4\u03ce \u03cc\u03bc\u03c9\u03c2 \u03c4\u03bf \u03ba\u03c1\u03af\u03c3\u03b9\u03bc\u03bf \u03b5\u03c1\u03ce\u03c4\u03b7\u03bc\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03b1\u03bd \u03bf drafter \u03c0\u03c1\u03bf\u03b2\u03bb\u03ad\u03c0\u03b5\u03b9 \u03c3\u03c9\u03c3\u03c4\u03ac \u03c4\u03b7 \u03c3\u03c5\u03b3\u03ba\u03b5\u03ba\u03c1\u03b9\u03bc\u03ad\u03bd\u03b7 \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03b9\u03ba\u03ae \u03c1\u03bf\u03ae.<\/p>\n<h2 id=\"ti-metrithike\">\u03a4\u03b9 \u03b1\u03ba\u03c1\u03b9\u03b2\u03ce\u03c2 \u03bc\u03b5\u03c4\u03c1\u03ae\u03b8\u03b7\u03ba\u03b5<\/h2>\n<p>\u039f\u03b9 GPU \u03b4\u03bf\u03ba\u03b9\u03bc\u03ad\u03c2 \u03c4\u03b7\u03c2 Liquid AI \u03ad\u03b3\u03b9\u03bd\u03b1\u03bd \u03c3\u03b5 \u03bc\u03af\u03b1 NVIDIA H100 80 GB, \u03bc\u03b5 SGLang \u03ba\u03b1\u03b9 BF16. \u039f\u03b9 on-device \u03b4\u03bf\u03ba\u03b9\u03bc\u03ad\u03c2 \u03ad\u03b3\u03b9\u03bd\u03b1\u03bd \u03c3\u03b5 MacBook Pro M4 Max, \u03bc\u03b5 llama.cpp, Metal \u03ba\u03b1\u03b9 FP16 GGUF weights. \u039a\u03b1\u03b9 \u03c4\u03b1 \u03b4\u03cd\u03bf setups \u03c7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b1\u03bd block size 9, batch size 1, temperature 0 \u03ba\u03b1\u03b9 \u03ad\u03c9\u03c2 256 output tokens \u03c3\u03c4\u03b1 MATH500, HumanEval, MBPP, GSM8K \u03ba\u03b1\u03b9 MT-Bench.<\/p>\n<div class=\"td-chart td-chart--metrics\">\n<div class=\"td-chart-head\">\n<p class=\"td-chart-title\">\u03a4\u03b1 \u03b4\u03b7\u03bc\u03bf\u03c3\u03b9\u03b5\u03c5\u03bc\u03ad\u03bd\u03b1 DSpark benchmarks \u03c3\u03b5 \u03c4\u03ad\u03c3\u03c3\u03b5\u03c1\u03b9\u03c2 \u03bc\u03b5\u03c4\u03c1\u03b9\u03ba\u03ad\u03c2<\/p>\n<p class=\"td-chart-subtitle\">Vendor-reported \u03b1\u03c0\u03bf\u03c4\u03b5\u03bb\u03ad\u03c3\u03bc\u03b1\u03c4\u03b1 Liquid AI \u03c3\u03c4\u03b1 \u03c3\u03c5\u03b3\u03ba\u03b5\u03ba\u03c1\u03b9\u03bc\u03ad\u03bd\u03b1 \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03b1, datasets \u03ba\u03b1\u03b9 runtimes\u00b7 \u03b4\u03b5\u03bd \u03b1\u03c0\u03bf\u03c4\u03b5\u03bb\u03bf\u03cd\u03bd \u03b3\u03b5\u03bd\u03b9\u03ba\u03ae \u03c0\u03c1\u03cc\u03b2\u03bb\u03b5\u03c8\u03b7 \u03b3\u03b9\u03b1 production latency.<\/p>\n<\/div>\n<div class=\"td-chart-body\">\n<div class=\"td-metric-grid\">\n<div class=\"td-metric-card\"><span class=\"td-metric-value\">3,18\u00d7<\/span><span class=\"td-metric-label\">\u039c\u03ad\u03b3\u03b9\u03c3\u03c4\u03bf \u03c3\u03c4\u03b7\u03bd H100<\/span><span class=\"td-metric-note\">LFM2.5-8B-A1B \u03c3\u03c4\u03bf MATH500, 428 \u2192 1.362 tok\/s<\/span><\/div>\n<div class=\"td-metric-card\"><span class=\"td-metric-value\">2,87\u00d7<\/span><span class=\"td-metric-label\">\u039c\u03ad\u03b3\u03b9\u03c3\u03c4\u03bf \u03c3\u03c4\u03bf M4 Max<\/span><span class=\"td-metric-note\">LFM2.5-1.2B-Instruct \u03c3\u03c4\u03bf HumanEval, 136 \u2192 389 tok\/s<\/span><\/div>\n<div class=\"td-metric-card\"><span class=\"td-metric-value\">57%<\/span><span class=\"td-metric-label\">\u039c\u03ad\u03c3\u03b7 \u03bc\u03b5\u03af\u03c9\u03c3\u03b7 agent latency<\/span><span class=\"td-metric-note\">Vendor test \u03bc\u03b5 LFM2.5-2.6B \u03c3\u03b5 multi-tool scenarios<\/span><\/div>\n<div class=\"td-metric-card\"><span class=\"td-metric-value\">1,18\u00d7<\/span><span class=\"td-metric-label\">\u039c\u03ad\u03c3\u03bf 8B-A1B \u03c3\u03c4\u03bf M4<\/span><span class=\"td-metric-note\">90 \u2192 106 tok\/s, \u03c0\u03b1\u03c1\u03ac \u03c4\u03bf \u03c5\u03c8\u03b7\u03bb\u03cc acceptance rate<\/span><\/div>\n<\/div>\n<\/div>\n<\/div>\n<p>\u0393\u03b9\u03b1 \u03c4\u03bf LFM2.5-2.6B, \u03bf \u03bc\u03ad\u03c3\u03bf\u03c2 \u03c1\u03c5\u03b8\u03bc\u03cc\u03c2 \u03b1\u03bd\u03ad\u03b2\u03b7\u03ba\u03b5 \u03b1\u03c0\u03cc 323 \u03c3\u03b5 864 tokens \u03b1\u03bd\u03ac \u03b4\u03b5\u03c5\u03c4\u03b5\u03c1\u03cc\u03bb\u03b5\u03c0\u03c4\u03bf \u03c3\u03c4\u03b7\u03bd H100 \u03ba\u03b1\u03b9 \u03b1\u03c0\u03cc 61 \u03c3\u03b5 139 \u03c3\u03c4\u03bf M4 Max. \u0393\u03b9\u03b1 \u03c4\u03bf 1.2B-Instruct, \u03bf\u03b9 \u03b1\u03bd\u03c4\u03af\u03c3\u03c4\u03bf\u03b9\u03c7\u03bf\u03b9 \u03bc\u03ad\u03c3\u03bf\u03b9 \u03cc\u03c1\u03bf\u03b9 \u03ae\u03c4\u03b1\u03bd 2,10\u00d7 \u03ba\u03b1\u03b9 2,54\u00d7. \u03a4\u03bf headline 3,18\u00d7 \u03b5\u03af\u03bd\u03b1\u03b9 \u03b7 \u03ba\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03b7 \u03b4\u03b7\u03bc\u03bf\u03c3\u03b9\u03b5\u03c5\u03bc\u03ad\u03bd\u03b7 \u03c0\u03b5\u03c1\u03af\u03c0\u03c4\u03c9\u03c3\u03b7, \u03cc\u03c7\u03b9 \u03bf \u03bc\u03ad\u03c3\u03bf\u03c2 \u03cc\u03c1\u03bf\u03c2 \u03cc\u03bb\u03c9\u03bd \u03c4\u03c9\u03bd workloads.<\/p>\n<div class=\"td-article-note\">\n<p><strong>\u038c\u03c1\u03b9\u03bf \u03b5\u03c1\u03bc\u03b7\u03bd\u03b5\u03af\u03b1\u03c2:<\/strong> \u03bf\u03b9 \u03bc\u03b5\u03c4\u03c1\u03ae\u03c3\u03b5\u03b9\u03c2 \u03c0\u03c1\u03bf\u03ad\u03c1\u03c7\u03bf\u03bd\u03c4\u03b1\u03b9 \u03b1\u03c0\u03cc \u03c4\u03bf\u03bd \u03c0\u03c1\u03bf\u03bc\u03b7\u03b8\u03b5\u03c5\u03c4\u03ae, \u03bc\u03b5 batch size 1 \u03ba\u03b1\u03b9 \u03b5\u03bb\u03b5\u03b3\u03c7\u03cc\u03bc\u03b5\u03bd\u03b1 benchmarks. \u0394\u03b5\u03bd \u03c4\u03b5\u03ba\u03bc\u03b7\u03c1\u03b9\u03ce\u03bd\u03bf\u03c5\u03bd \u03af\u03c3\u03b7 \u03b2\u03b5\u03bb\u03c4\u03af\u03c9\u03c3\u03b7 \u03c3\u03b5 high concurrency, \u03ac\u03bb\u03bb\u03bf quantization, \u03bc\u03b5\u03b3\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03bf context \u03ae \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03b5\u03c4\u03b9\u03ba\u03cc prompt mix.<\/p>\n<\/div>\n<div class=\"td-decision-band\">\n<p class=\"td-decision-band-kicker\">\u0391\u03c0\u03cc benchmark \u03c3\u03b5 pilot<\/p>\n<p><strong>\u03a4\u03bf 3,18\u00d7 \u03b4\u03b9\u03ba\u03b1\u03b9\u03bf\u03bb\u03bf\u03b3\u03b5\u03af \u03b4\u03bf\u03ba\u03b9\u03bc\u03ae, \u03cc\u03c7\u03b9 \u03c5\u03c0\u03cc\u03c3\u03c7\u03b5\u03c3\u03b7 \u03c0\u03c1\u03bf\u03c2 \u03c7\u03c1\u03ae\u03c3\u03c4\u03b5\u03c2.<\/strong> \u0397 \u03b1\u03c0\u03cc\u03c6\u03b1\u03c3\u03b7 \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03af\u03b4\u03b9\u03b1 prompts, \u03af\u03b4\u03b9\u03bf target, \u03af\u03b4\u03b9\u03bf backend \u03ba\u03b1\u03b9 \u03bc\u03ad\u03c4\u03c1\u03b7\u03c3\u03b7 end-to-end latency, throughput, \u03bc\u03bd\u03ae\u03bc\u03b7\u03c2, \u03bf\u03c5\u03c1\u03ac\u03c2 \u03ba\u03b1\u03b9 fallback \u03c3\u03c4\u03bf \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03cc \u03c0\u03b5\u03c1\u03b9\u03b2\u03ac\u03bb\u03bb\u03bf\u03bd.<\/p>\n<\/div>\n<h2 id=\"acceptance-rate\">\u0397 acceptance rate \u03b5\u03be\u03b7\u03b3\u03b5\u03af \u03c4\u03b9\u03c2 \u03bc\u03b5\u03b3\u03ac\u03bb\u03b5\u03c2 \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03ad\u03c2<\/h2>\n<p>\u03a4\u03bf speculative decoding \u03b1\u03c0\u03bf\u03b4\u03af\u03b4\u03b5\u03b9 \u03cc\u03c4\u03b1\u03bd \u03bf drafter \u03c0\u03c1\u03bf\u03b2\u03bb\u03ad\u03c0\u03b5\u03b9 \u03c3\u03c9\u03c3\u03c4\u03ac \u03b1\u03c1\u03ba\u03b5\u03c4\u03ac \u03b4\u03b9\u03b1\u03b4\u03bf\u03c7\u03b9\u03ba\u03ac tokens. \u03a3\u03c4\u03bf MATH500, \u03c4\u03bf 8B-A1B \u03b4\u03ad\u03c7\u03c4\u03b7\u03ba\u03b5 8,27 \u03b1\u03c0\u03cc \u03c4\u03b1 10 tokens \u03b1\u03bd\u03ac \u03b2\u03ae\u03bc\u03b1 \u03ba\u03b1\u03b9 \u03ad\u03c6\u03c4\u03b1\u03c3\u03b5 3,18\u00d7 \u03c3\u03c4\u03b7\u03bd H100. \u03a3\u03c4\u03bf GSM8K \u03b4\u03ad\u03c7\u03c4\u03b7\u03ba\u03b5 4,02 \u03ba\u03b1\u03b9 \u03c0\u03b5\u03c1\u03b9\u03bf\u03c1\u03af\u03c3\u03c4\u03b7\u03ba\u03b5 \u03c3\u03b5 1,29\u00d7 \u03c3\u03c4\u03b7\u03bd \u03af\u03b4\u03b9\u03b1 GPU. \u0393\u03b9\u03b1 \u03c4\u03bf 1.2B-Instruct, \u03b7 acceptance \u03c3\u03c4\u03bf MT-Bench \u03ae\u03c4\u03b1\u03bd 3,90 \u03ba\u03b1\u03b9 \u03c4\u03bf speedup \u03c3\u03c4\u03b7\u03bd H100 1,66\u00d7.<\/p>\n<p>\u03a4\u03bf pattern \u03b4\u03b5\u03af\u03c7\u03bd\u03b5\u03b9 \u03cc\u03c4\u03b9 \u03c4\u03bf workload \u03b5\u03af\u03bd\u03b1\u03b9 \u03bc\u03ad\u03c1\u03bf\u03c2 \u03c4\u03b7\u03c2 \u03c4\u03b5\u03c7\u03bd\u03bf\u03bb\u03bf\u03b3\u03b9\u03ba\u03ae\u03c2 \u03b1\u03c0\u03cc\u03c6\u03b1\u03c3\u03b7\u03c2. \u0394\u03bf\u03bc\u03b7\u03bc\u03ad\u03bd\u03b7 \u03ad\u03be\u03bf\u03b4\u03bf\u03c2, code completion \u03ae \u03b5\u03c0\u03b1\u03bd\u03b1\u03bb\u03b1\u03bc\u03b2\u03b1\u03bd\u03cc\u03bc\u03b5\u03bd\u03b1 function-call arguments \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03b5\u03c5\u03ba\u03bf\u03bb\u03cc\u03c4\u03b5\u03c1\u03b1 \u03b3\u03b9\u03b1 \u03c4\u03bf\u03bd drafter \u03b1\u03c0\u03cc \u03ad\u03bd\u03b1\u03bd \u03b1\u03bd\u03bf\u03b9\u03c7\u03c4\u03cc \u03b4\u03b9\u03ac\u03bb\u03bf\u03b3\u03bf \u03bc\u03b5 \u03b1\u03c0\u03c1\u03cc\u03b2\u03bb\u03b5\u03c0\u03c4\u03b7 \u03c3\u03c5\u03bd\u03ad\u03c7\u03b5\u03b9\u03b1. \u0391\u03c5\u03c4\u03ae \u03b5\u03af\u03bd\u03b1\u03b9 \u03bc\u03b7\u03c7\u03b1\u03bd\u03b9\u03c3\u03c4\u03b9\u03ba\u03ae \u03b5\u03c1\u03bc\u03b7\u03bd\u03b5\u03af\u03b1 \u03c4\u03c9\u03bd \u03bc\u03b5\u03c4\u03c1\u03ae\u03c3\u03b5\u03c9\u03bd, \u03cc\u03c7\u03b9 \u03bd\u03ad\u03bf benchmark \u03bf\u03cd\u03c4\u03b5 \u03c5\u03c0\u03cc\u03c3\u03c7\u03b5\u03c3\u03b7 \u03cc\u03c4\u03b9 \u03ba\u03ac\u03b8\u03b5 structured task \u03b8\u03b1 \u03ad\u03c7\u03b5\u03b9 \u03c5\u03c8\u03b7\u03bb\u03ae \u03b1\u03c0\u03bf\u03b4\u03bf\u03c7\u03ae.<\/p>\n<p>\u0397 \u03b1\u03c0\u03bf\u03b4\u03bf\u03c7\u03ae \u03ad\u03c7\u03b5\u03b9 \u03b5\u03c0\u03af\u03c3\u03b7\u03c2 \u03cc\u03c1\u03b9\u03b1 \u03c9\u03c2 KPI. \u0388\u03bd\u03b1 \u03c3\u03cd\u03c3\u03c4\u03b7\u03bc\u03b1 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b4\u03ad\u03c7\u03b5\u03c4\u03b1\u03b9 \u03c0\u03bf\u03bb\u03bb\u03ac draft tokens, \u03b1\u03bb\u03bb\u03ac \u03bd\u03b1 \u03c7\u03ac\u03bd\u03b5\u03b9 \u03c4\u03bf \u03cc\u03c6\u03b5\u03bb\u03bf\u03c2 \u03c3\u03b5 backend overhead, \u03bc\u03b5\u03c4\u03b1\u03c6\u03bf\u03c1\u03ac \u03b2\u03b1\u03c1\u03ce\u03bd \u03ae queueing. \u038c\u03c0\u03c9\u03c2 \u03ba\u03b1\u03b9 \u03c3\u03c4\u03bf <a href=\"https:\/\/twodots.gr\/trie-automata-constrained-decoding-ai-systimata\/\">constrained decoding \u03bc\u03b5 \u03c7\u03b9\u03bb\u03b9\u03ac\u03b4\u03b5\u03c2 \u03b5\u03c0\u03b9\u03bb\u03bf\u03b3\u03ad\u03c2<\/a>, \u03b7 \u03b5\u03c0\u03af\u03b4\u03bf\u03c3\u03b7 \u03b4\u03b5\u03bd \u03ba\u03c1\u03af\u03bd\u03b5\u03c4\u03b1\u03b9 \u03bc\u03cc\u03bd\u03bf \u03b1\u03c0\u03cc \u03c4\u03bf\u03bd \u03b1\u03bb\u03b3\u03cc\u03c1\u03b9\u03b8\u03bc\u03bf\u00b7 \u03b5\u03be\u03b1\u03c1\u03c4\u03ac\u03c4\u03b1\u03b9 \u03b1\u03c0\u03cc \u03c4\u03bf \u03c0\u03ce\u03c2 \u03bf runtime \u03c5\u03bb\u03bf\u03c0\u03bf\u03b9\u03b5\u03af \u03c4\u03bf\u03bd \u03ad\u03bb\u03b5\u03b3\u03c7\u03bf \u03bc\u03ad\u03c3\u03b1 \u03c3\u03c4\u03bf \u03c0\u03bb\u03ae\u03c1\u03b5\u03c2 request path.<\/p>\n<h2 id=\"apple-silicon-orio\">\u0393\u03b9\u03b1\u03c4\u03af \u03c4\u03bf Apple silicon \u03b4\u03b5\u03af\u03c7\u03bd\u03b5\u03b9 \u03c4\u03bf \u03b2\u03b1\u03c3\u03b9\u03ba\u03cc \u03cc\u03c1\u03b9\u03bf<\/h2>\n<p>\u0397 \u03ba\u03b1\u03b8\u03b1\u03c1\u03cc\u03c4\u03b5\u03c1\u03b7 \u03c0\u03c1\u03bf\u03b5\u03b9\u03b4\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b7 \u03b5\u03bc\u03c6\u03b1\u03bd\u03af\u03b6\u03b5\u03c4\u03b1\u03b9 \u03c3\u03c4\u03bf LFM2.5-8B-A1B, \u03ad\u03bd\u03b1 Mixture-of-Experts \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf. \u03a3\u03c4\u03bf M4 Max \u03c0\u03ad\u03c4\u03c5\u03c7\u03b5 \u03bc\u03ad\u03c3\u03b7 \u03b5\u03c0\u03b9\u03c4\u03ac\u03c7\u03c5\u03bd\u03c3\u03b7 \u03bc\u03cc\u03bb\u03b9\u03c2 1,18\u00d7. \u0397 Liquid AI \u03b1\u03c0\u03bf\u03b4\u03af\u03b4\u03b5\u03b9 \u03c4\u03bf \u03b1\u03c0\u03bf\u03c4\u03ad\u03bb\u03b5\u03c3\u03bc\u03b1 \u03c3\u03c4\u03b7\u03bd \u03c4\u03c1\u03ad\u03c7\u03bf\u03c5\u03c3\u03b1 \u03c5\u03bb\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b7 MoE \u03c4\u03bf\u03c5 Metal backend \u03c3\u03c4\u03bf llama.cpp \u03ba\u03b1\u03b9 \u03c3\u03c4\u03bf \u03cc\u03c4\u03b9 \u03b7 \u03b5\u03c0\u03b1\u03bb\u03ae\u03b8\u03b5\u03c5\u03c3\u03b7 \u03c0\u03bf\u03bb\u03bb\u03ce\u03bd tokens \u03b5\u03bd\u03b5\u03c1\u03b3\u03bf\u03c0\u03bf\u03b9\u03b5\u03af \u03c0\u03b5\u03c1\u03b9\u03c3\u03c3\u03cc\u03c4\u03b5\u03c1\u03bf\u03c5\u03c2 experts, \u03b1\u03c5\u03be\u03ac\u03bd\u03bf\u03bd\u03c4\u03b1\u03c2 \u03c4\u03b7\u03bd \u03ba\u03af\u03bd\u03b7\u03c3\u03b7 \u03b2\u03b1\u03c1\u03ce\u03bd \u03c3\u03b5 \u03c3\u03c7\u03ad\u03c3\u03b7 \u03bc\u03b5 \u03ad\u03bd\u03b1 \u03ba\u03b1\u03bd\u03bf\u03bd\u03b9\u03ba\u03cc decode step.<\/p>\n<p>\u03a4\u03bf \u03b5\u03cd\u03c1\u03b7\u03bc\u03b1 \u03b4\u03b5\u03bd \u03b1\u03ba\u03c5\u03c1\u03ce\u03bd\u03b5\u03b9 \u03c4\u03bf on-device \u03c3\u03b5\u03bd\u03ac\u03c1\u03b9\u03bf. \u0394\u03b5\u03af\u03c7\u03bd\u03b5\u03b9 \u03cc\u03c4\u03b9 \u03b1\u03c1\u03c7\u03b9\u03c4\u03b5\u03ba\u03c4\u03bf\u03bd\u03b9\u03ba\u03ae target, kernels \u03ba\u03b1\u03b9 backend \u03c9\u03c1\u03b9\u03bc\u03cc\u03c4\u03b7\u03c4\u03b1 \u03bc\u03c0\u03bf\u03c1\u03bf\u03cd\u03bd \u03bd\u03b1 \u03c0\u03b5\u03c1\u03b9\u03bf\u03c1\u03af\u03c3\u03bf\u03c5\u03bd \u03c4\u03bf \u03b8\u03b5\u03c9\u03c1\u03b7\u03c4\u03b9\u03ba\u03cc \u03cc\u03c6\u03b5\u03bb\u03bf\u03c2. \u039c\u03b9\u03b1 \u03b5\u03c0\u03b9\u03c7\u03b5\u03af\u03c1\u03b7\u03c3\u03b7 \u03c0\u03bf\u03c5 \u03c3\u03c7\u03b5\u03b4\u03b9\u03ac\u03b6\u03b5\u03b9 offline copilot \u03c3\u03b5 laptop \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03bc\u03b5\u03c4\u03c1\u03ae\u03c3\u03b5\u03b9 \u03c3\u03c4\u03b7\u03bd \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ae \u03c3\u03c5\u03c3\u03ba\u03b5\u03c5\u03ae, \u03bc\u03b5 \u03af\u03b4\u03b9\u03bf quantization, context length \u03ba\u03b1\u03b9 thermal profile. \u0397 H100 \u03ba\u03b1\u03b9 \u03c4\u03bf M4 Max \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u03b5\u03bd\u03b1\u03bb\u03bb\u03ac\u03be\u03b9\u03bc\u03b5\u03c2 \u03c0\u03bb\u03b1\u03c4\u03c6\u03cc\u03c1\u03bc\u03b5\u03c2.<\/p>\n<p>\u0397 \u03b5\u03c0\u03b9\u03bb\u03bf\u03b3\u03ae \u03c3\u03c5\u03c3\u03ba\u03b5\u03c5\u03ae\u03c2 \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03c0\u03b5\u03c1\u03b9\u03bb\u03b1\u03bc\u03b2\u03ac\u03bd\u03b5\u03b9 \u03bc\u03bd\u03ae\u03bc\u03b7, bandwidth, \u03ba\u03b1\u03c4\u03b1\u03bd\u03ac\u03bb\u03c9\u03c3\u03b7, \u03c7\u03c1\u03cc\u03bd\u03bf \u03b5\u03ba\u03ba\u03af\u03bd\u03b7\u03c3\u03b7\u03c2 \u03ba\u03b1\u03b9 \u03c5\u03c0\u03bf\u03c3\u03c4\u03ae\u03c1\u03b9\u03be\u03b7 runtime. \u038c\u03c4\u03b1\u03bd \u03c4\u03bf deployment \u03b1\u03c0\u03b1\u03b9\u03c4\u03b5\u03af \u03b5\u03be\u03b5\u03b9\u03b4\u03b9\u03ba\u03b5\u03c5\u03bc\u03ad\u03bd\u03bf workstation \u03ae server, \u03b7 \u03b1\u03be\u03b9\u03bf\u03bb\u03cc\u03b3\u03b7\u03c3\u03b7 \u03c3\u03c5\u03bd\u03b4\u03ad\u03b5\u03c4\u03b1\u03b9 \u03ba\u03b1\u03b9 \u03bc\u03b5 \u03c4\u03bf \u03ba\u03b1\u03c4\u03ac\u03bb\u03bb\u03b7\u03bb\u03bf <a href=\"https:\/\/twodots.gr\/epaggelmatiko-hardware\/\">\u03b5\u03c0\u03b1\u03b3\u03b3\u03b5\u03bb\u03bc\u03b1\u03c4\u03b9\u03ba\u03cc hardware<\/a>, \u03cc\u03c7\u03b9 \u03bc\u03cc\u03bd\u03bf \u03bc\u03b5 \u03c4\u03bf \u03b8\u03b5\u03c9\u03c1\u03b7\u03c4\u03b9\u03ba\u03cc \u03bc\u03ad\u03b3\u03b5\u03b8\u03bf\u03c2 \u03c4\u03bf\u03c5 \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf\u03c5.<\/p>\n<h2 id=\"agents-function-calling\">Agents \u03ba\u03b1\u03b9 function calling: \u03c0\u03bf\u03cd \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03c6\u03b1\u03bd\u03b5\u03af \u03c0\u03b5\u03c1\u03b9\u03c3\u03c3\u03cc\u03c4\u03b5\u03c1\u03bf<\/h2>\n<p>\u0397 Liquid AI \u03b1\u03bd\u03b1\u03c6\u03ad\u03c1\u03b5\u03b9 \u03bc\u03ad\u03c3\u03b7 \u03bc\u03b5\u03af\u03c9\u03c3\u03b7 57% \u03c3\u03c4\u03b7 latency \u03c4\u03bf\u03c5 LFM2.5-2.6B \u03c3\u03b5 \u03b4\u03b9\u03ac\u03c6\u03bf\u03c1\u03b1 multi-tool scenarios. \u039f \u03b1\u03c1\u03b9\u03b8\u03bc\u03cc\u03c2 \u03b5\u03af\u03bd\u03b1\u03b9 vendor-reported \u03ba\u03b1\u03b9 \u03b4\u03b5\u03bd \u03c3\u03c5\u03bd\u03bf\u03b4\u03b5\u03cd\u03b5\u03c4\u03b1\u03b9 \u03b1\u03c0\u03cc \u03c0\u03bb\u03ae\u03c1\u03b7 \u03b1\u03bd\u03ac\u03bb\u03c5\u03c3\u03b7 \u03ba\u03ac\u03b8\u03b5 production workflow. \u03a0\u03b1\u03c1\u2019 \u03cc\u03bb\u03b1 \u03b1\u03c5\u03c4\u03ac, \u03b7 \u03ba\u03b1\u03c4\u03b5\u03cd\u03b8\u03c5\u03bd\u03c3\u03b7 \u03b5\u03af\u03bd\u03b1\u03b9 \u03bf\u03c5\u03c3\u03b9\u03b1\u03c3\u03c4\u03b9\u03ba\u03ae: \u03ad\u03bd\u03b1\u03c2 agent \u03c0\u03bb\u03b7\u03c1\u03ce\u03bd\u03b5\u03b9 decode cost \u03c0\u03c1\u03b9\u03bd \u03b1\u03c0\u03cc \u03c4\u03b7\u03bd \u03b5\u03c0\u03b9\u03bb\u03bf\u03b3\u03ae \u03b5\u03c1\u03b3\u03b1\u03bb\u03b5\u03af\u03bf\u03c5, \u03ba\u03b1\u03c4\u03ac \u03c4\u03b7 \u03b4\u03b7\u03bc\u03b9\u03bf\u03c5\u03c1\u03b3\u03af\u03b1 arguments \u03ba\u03b1\u03b9 \u03bc\u03b5\u03c4\u03ac \u03c4\u03b7\u03bd \u03b5\u03c0\u03b9\u03c3\u03c4\u03c1\u03bf\u03c6\u03ae \u03c4\u03bf\u03c5 \u03b1\u03c0\u03bf\u03c4\u03b5\u03bb\u03ad\u03c3\u03bc\u03b1\u03c4\u03bf\u03c2.<\/p>\n<p>\u03a3\u03b5 customer support, \u03c4\u03bf \u03ba\u03b1\u03c4\u03ac\u03bb\u03bb\u03b7\u03bb\u03bf test \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u03bc\u03cc\u03bd\u03bf tokens \u03b1\u03bd\u03ac \u03b4\u03b5\u03c5\u03c4\u03b5\u03c1\u03cc\u03bb\u03b5\u03c0\u03c4\u03bf. \u0395\u03af\u03bd\u03b1\u03b9 \u03bf \u03c7\u03c1\u03cc\u03bd\u03bf\u03c2 \u03b1\u03c0\u03cc \u03c4\u03bf \u03b1\u03af\u03c4\u03b7\u03bc\u03b1 \u03ad\u03c9\u03c2 \u03c4\u03b7\u03bd \u03b1\u03bd\u03ac\u03ba\u03c4\u03b7\u03c3\u03b7 \u03c0\u03b1\u03c1\u03b1\u03b3\u03b3\u03b5\u03bb\u03af\u03b1\u03c2, \u03c4\u03bf\u03bd \u03ad\u03bb\u03b5\u03b3\u03c7\u03bf \u03c0\u03bf\u03bb\u03b9\u03c4\u03b9\u03ba\u03ae\u03c2 \u03b5\u03c0\u03b9\u03c3\u03c4\u03c1\u03bf\u03c6\u03ce\u03bd \u03ba\u03b1\u03b9 \u03c4\u03b7\u03bd \u03c4\u03b5\u03bb\u03b9\u03ba\u03ae \u03b1\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7, \u03bc\u03b5 \u03c3\u03c9\u03c3\u03c4\u03ac permissions \u03ba\u03b1\u03b9 human handoff. \u0397 \u03b5\u03c0\u03b9\u03bb\u03bf\u03b3\u03ae \u03b1\u03bd\u03ac\u03bc\u03b5\u03c3\u03b1 \u03c3\u03b5 <a href=\"https:\/\/twodots.gr\/6-ai-agents-customer-support-gia-epicheiriseis\/\">AI agents \u03b3\u03b9\u03b1 customer support<\/a> \u03c0\u03b1\u03c1\u03b1\u03bc\u03ad\u03bd\u03b5\u03b9 \u03b1\u03c0\u03cc\u03c6\u03b1\u03c3\u03b7 workflow, data access \u03ba\u03b1\u03b9 \u03b1\u03be\u03b9\u03bf\u03c0\u03b9\u03c3\u03c4\u03af\u03b1\u03c2\u00b7 \u03c4\u03bf DSpark \u03b2\u03b5\u03bb\u03c4\u03b9\u03c3\u03c4\u03bf\u03c0\u03bf\u03b9\u03b5\u03af \u03ad\u03bd\u03b1 \u03bc\u03ad\u03c1\u03bf\u03c2 \u03c4\u03b7\u03c2 \u03b4\u03b9\u03b1\u03b4\u03c1\u03bf\u03bc\u03ae\u03c2.<\/p>\n<p>\u03a4\u03bf pilot \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03ba\u03b1\u03c4\u03b1\u03b3\u03c1\u03ac\u03c6\u03b5\u03b9 \u03bb\u03ac\u03b8\u03bf\u03c2 tool calls, retries, timeouts \u03ba\u03b1\u03b9 \u03b5\u03b3\u03ba\u03c1\u03af\u03c3\u03b5\u03b9\u03c2. \u0397 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ae \u03bb\u03b5\u03b9\u03c4\u03bf\u03c5\u03c1\u03b3\u03af\u03b1 \u03c4\u03c9\u03bd <a href=\"https:\/\/twodots.gr\/ai-agents-paragogi-leitourgikes-astochies\/\">AI agents \u03c3\u03c4\u03b7\u03bd \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae<\/a> \u03c0\u03b5\u03c1\u03b9\u03bb\u03b1\u03bc\u03b2\u03ac\u03bd\u03b5\u03b9 \u03c0\u03b5\u03c1\u03b9\u03c3\u03c3\u03cc\u03c4\u03b5\u03c1\u03b1 \u03b1\u03c0\u03cc decoding. \u0393\u03c1\u03b7\u03b3\u03bf\u03c1\u03cc\u03c4\u03b5\u03c1\u03bf token stream \u03b4\u03b5\u03bd \u03b4\u03b9\u03bf\u03c1\u03b8\u03ce\u03bd\u03b5\u03b9 \u03bb\u03b1\u03bd\u03b8\u03b1\u03c3\u03bc\u03ad\u03bd\u03b7 \u03b1\u03bd\u03ac\u03ba\u03c4\u03b7\u03c3\u03b7 \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03c9\u03bd \u03bf\u03cd\u03c4\u03b5 \u03bc\u03b7 \u03b1\u03c3\u03c6\u03b1\u03bb\u03ae \u03b5\u03bd\u03ad\u03c1\u03b3\u03b5\u03b9\u03b1.<\/p>\n<h2 id=\"self-hosting-adeia\">Self-hosting, formats \u03ba\u03b1\u03b9 \u03ac\u03b4\u03b5\u03b9\u03b1 \u03c7\u03c1\u03ae\u03c3\u03b7\u03c2<\/h2>\n<p>\u03a4\u03b1 DSpark checkpoints \u03b4\u03b9\u03b1\u03c4\u03af\u03b8\u03b5\u03bd\u03c4\u03b1\u03b9 \u03c9\u03c2 Safetensors \u03ba\u03b1\u03b9 GGUF. \u0397 Liquid AI \u03c4\u03b5\u03ba\u03bc\u03b7\u03c1\u03b9\u03ce\u03bd\u03b5\u03b9 \u03c7\u03c1\u03ae\u03c3\u03b7 \u03bc\u03ad\u03c3\u03c9 SGLang \u03b3\u03b9\u03b1 GPU serving \u03ba\u03b1\u03b9 \u03bc\u03ad\u03c3\u03c9 llama.cpp\/Metal \u03b3\u03b9\u03b1 on-device deployment. \u03a4\u03b1 \u03c3\u03c5\u03b3\u03ba\u03b5\u03ba\u03c1\u03b9\u03bc\u03ad\u03bd\u03b1 model cards \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u03b1\u03bd\u03b1\u03c0\u03c4\u03c5\u03b3\u03bc\u03ad\u03bd\u03b1 \u03c3\u03b5 hosted Hugging Face Inference Provider, \u03ac\u03c1\u03b1 \u03b7 \u03bf\u03bc\u03ac\u03b4\u03b1 \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03bf\u03c1\u03b3\u03b1\u03bd\u03ce\u03c3\u03b5\u03b9 self-hosting \u03ba\u03b1\u03b9 \u03bd\u03b1 \u03c7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03ae\u03c3\u03b5\u03b9 build \u03bc\u03b5 \u03c3\u03c5\u03bc\u03b2\u03b1\u03c4\u03ae \u03c5\u03c0\u03bf\u03c3\u03c4\u03ae\u03c1\u03b9\u03be\u03b7 DSpark \u03b3\u03b9\u03b1 LFM2 targets.<\/p>\n<p>\u0397 \u03bb\u03b5\u03b9\u03c4\u03bf\u03c5\u03c1\u03b3\u03af\u03b1 \u03b4\u03b5\u03cd\u03c4\u03b5\u03c1\u03bf\u03c5 \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf\u03c5 \u03b1\u03c5\u03be\u03ac\u03bd\u03b5\u03b9 \u03c4\u03b7\u03bd operational \u03b5\u03c0\u03b9\u03c6\u03ac\u03bd\u03b5\u03b9\u03b1: checkpoints, \u03b5\u03ba\u03b4\u03cc\u03c3\u03b5\u03b9\u03c2, startup, \u03bc\u03bd\u03ae\u03bc\u03b7, telemetry \u03ba\u03b1\u03b9 fallback. \u03a4\u03bf \u03ba\u03cc\u03c3\u03c4\u03bf\u03c2 \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03b5\u03be\u03b5\u03c4\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03bc\u03b1\u03b6\u03af \u03bc\u03b5 \u03cc\u03c3\u03b1 \u03b9\u03c3\u03c7\u03cd\u03bf\u03c5\u03bd \u03b3\u03b9\u03b1 <a href=\"https:\/\/twodots.gr\/ai-agent-harnesses-elegchos-kostos-self-hosting\/\">agent harnesses, \u03ad\u03bb\u03b5\u03b3\u03c7\u03bf \u03ba\u03b1\u03b9 self-hosting<\/a>. \u0391\u03bd \u03bf drafter \u03b4\u03b5\u03bd \u03c6\u03bf\u03c1\u03c4\u03ce\u03bd\u03b5\u03c4\u03b1\u03b9 \u03ae \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u03b1\u03c0\u03bf\u03b4\u03bf\u03c4\u03b9\u03ba\u03cc\u03c2 \u03b3\u03b9\u03b1 \u03ad\u03bd\u03b1 workload, \u03c4\u03bf \u03c0\u03c1\u03bf\u03ca\u03cc\u03bd \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03c3\u03c5\u03bd\u03b5\u03c7\u03af\u03b6\u03b5\u03b9 \u03bc\u03b5 target-only decoding \u03c7\u03c9\u03c1\u03af\u03c2 \u03b4\u03b9\u03b1\u03ba\u03bf\u03c0\u03ae \u03b5\u03bc\u03c0\u03b5\u03b9\u03c1\u03af\u03b1\u03c2.<\/p>\n<p>\u03a5\u03c0\u03ac\u03c1\u03c7\u03b5\u03b9 \u03ba\u03b1\u03b9 \u03b1\u03b4\u03b5\u03b9\u03bf\u03b4\u03bf\u03c4\u03b9\u03ba\u03cc \u03cc\u03c1\u03b9\u03bf. \u0397 LFM Open License v1.0 \u03bf\u03c1\u03af\u03b6\u03b5\u03b9 threshold \u03b5\u03c4\u03ae\u03c3\u03b9\u03c9\u03bd \u03b5\u03c3\u03cc\u03b4\u03c9\u03bd 10 \u03b5\u03ba\u03b1\u03c4\u03bf\u03bc\u03bc\u03c5\u03c1\u03af\u03c9\u03bd \u03b4\u03bf\u03bb\u03b1\u03c1\u03af\u03c9\u03bd \u03ae \u03c0\u03b5\u03c1\u03b9\u03c3\u03c3\u03cc\u03c4\u03b5\u03c1\u03bf \u03b3\u03b9\u03b1 \u03b5\u03bc\u03c0\u03bf\u03c1\u03b9\u03ba\u03ae \u03c7\u03c1\u03ae\u03c3\u03b7 \u03b1\u03c0\u03cc legal entity. \u03a0\u03ac\u03bd\u03c9 \u03b1\u03c0\u03cc \u03b1\u03c5\u03c4\u03cc \u03c4\u03bf \u03cc\u03c1\u03b9\u03bf, \u03b7 \u03b5\u03bc\u03c0\u03bf\u03c1\u03b9\u03ba\u03ae \u03c7\u03c1\u03ae\u03c3\u03b7 \u03b4\u03b5\u03bd \u03b1\u03b4\u03b5\u03b9\u03bf\u03b4\u03bf\u03c4\u03b5\u03af\u03c4\u03b1\u03b9 \u03b1\u03c0\u03cc \u03c4\u03b7 \u03c3\u03c5\u03b3\u03ba\u03b5\u03ba\u03c1\u03b9\u03bc\u03ad\u03bd\u03b7 \u03c3\u03c5\u03bc\u03c6\u03c9\u03bd\u03af\u03b1. \u0397 \u03bd\u03bf\u03bc\u03b9\u03ba\u03ae \u03bf\u03bc\u03ac\u03b4\u03b1 \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03b4\u03b9\u03b1\u03b2\u03ac\u03c3\u03b5\u03b9 \u03c4\u03bf \u03b9\u03c3\u03c7\u03cd\u03bf\u03bd \u03ba\u03b5\u03af\u03bc\u03b5\u03bd\u03bf \u03c4\u03b7\u03c2 \u03ac\u03b4\u03b5\u03b9\u03b1\u03c2 \u03ba\u03b1\u03b9 \u03bd\u03b1 \u03b5\u03c0\u03b9\u03b2\u03b5\u03b2\u03b1\u03b9\u03ce\u03c3\u03b5\u03b9 \u03c4\u03b7\u03bd \u03b5\u03c4\u03b1\u03b9\u03c1\u03b9\u03ba\u03ae \u03b4\u03bf\u03bc\u03ae \u03c0\u03c1\u03b9\u03bd \u03b1\u03c0\u03cc \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03b9\u03ba\u03ae \u03c7\u03c1\u03ae\u03c3\u03b7.<\/p>\n<h2 id=\"evaluation-plan\">\u0388\u03bd\u03b1 \u03c3\u03bf\u03b2\u03b1\u03c1\u03cc evaluation plan \u03c0\u03c1\u03b9\u03bd \u03b1\u03c0\u03cc \u03c4\u03b7\u03bd \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae<\/h2>\n<p>\u03a4\u03bf baseline \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03c4\u03bf \u03af\u03b4\u03b9\u03bf target model \u03c7\u03c9\u03c1\u03af\u03c2 drafter, \u03c3\u03c4\u03b7\u03bd \u03af\u03b4\u03b9\u03b1 \u03c3\u03c5\u03c3\u03ba\u03b5\u03c5\u03ae \u03ba\u03b1\u03b9 \u03bc\u03b5 \u03c4\u03b9\u03c2 \u03af\u03b4\u03b9\u03b5\u03c2 \u03c1\u03c5\u03b8\u03bc\u03af\u03c3\u03b5\u03b9\u03c2. \u039c\u03b5\u03c4\u03c1\u03ae\u03c3\u03c4\u03b5 time-to-first-token, inter-token latency, tokens \u03b1\u03bd\u03ac \u03b4\u03b5\u03c5\u03c4\u03b5\u03c1\u03cc\u03bb\u03b5\u03c0\u03c4\u03bf, end-to-end latency, peak \u03bc\u03bd\u03ae\u03bc\u03b7 \u03ba\u03b1\u03b9 \u03b5\u03bd\u03ad\u03c1\u03b3\u03b5\u03b9\u03b1 \u03cc\u03c0\u03bf\u03c5 \u03ad\u03c7\u03b5\u03b9 \u03bd\u03cc\u03b7\u03bc\u03b1. \u039c\u03b5\u03c4\u03ac \u03b5\u03bd\u03b5\u03c1\u03b3\u03bf\u03c0\u03bf\u03b9\u03ae\u03c3\u03c4\u03b5 DSpark \u03c7\u03c9\u03c1\u03af\u03c2 \u03bd\u03b1 \u03b1\u03bb\u03bb\u03ac\u03be\u03b5\u03c4\u03b5 \u03c4\u03b1\u03c5\u03c4\u03cc\u03c7\u03c1\u03bf\u03bd\u03b1 quantization, context \u03ae backend.<\/p>\n<p>\u03a7\u03c9\u03c1\u03af\u03c3\u03c4\u03b5 \u03c4\u03b1 traces \u03b1\u03bd\u03ac \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ae \u03b5\u03c1\u03b3\u03b1\u03c3\u03af\u03b1. Code completion, function calling, \u03b1\u03bd\u03bf\u03b9\u03c7\u03c4\u03cc\u03c2 \u03b4\u03b9\u03ac\u03bb\u03bf\u03b3\u03bf\u03c2 \u03ba\u03b1\u03b9 \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae \u03b5\u03bb\u03bb\u03b7\u03bd\u03b9\u03ba\u03bf\u03cd \u03c0\u03b5\u03c1\u03b9\u03b5\u03c7\u03bf\u03bc\u03ad\u03bd\u03bf\u03c5 \u03bc\u03c0\u03bf\u03c1\u03bf\u03cd\u03bd \u03bd\u03b1 \u03ad\u03c7\u03bf\u03c5\u03bd \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03b5\u03c4\u03b9\u03ba\u03ae acceptance rate. \u0395\u03be\u03b5\u03c4\u03ac\u03c3\u03c4\u03b5 p50, p95 \u03ba\u03b1\u03b9 p99, \u03cc\u03c7\u03b9 \u03bc\u03cc\u03bd\u03bf \u03bc\u03ad\u03c3\u03bf \u03cc\u03c1\u03bf. \u03a4\u03b1 \u03b4\u03b7\u03bc\u03bf\u03c3\u03b9\u03b5\u03c5\u03bc\u03ad\u03bd\u03b1 benchmarks \u03b1\u03c6\u03bf\u03c1\u03bf\u03cd\u03bd batch size 1, \u03b5\u03c0\u03bf\u03bc\u03ad\u03bd\u03c9\u03c2 \u03b7 \u03bf\u03c5\u03c1\u03ac \u03ba\u03b1\u03b9 \u03c4\u03bf concurrency \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03bf\u03bd\u03c4\u03b1\u03b9 \u03b4\u03b9\u03ba\u03ae \u03c4\u03bf\u03c5\u03c2 \u03b4\u03bf\u03ba\u03b9\u03bc\u03ae.<\/p>\n<div class=\"td-step-list\">\n<p class=\"td-step-list-title\">\u0395\u03c0\u03c4\u03ac \u03b2\u03ae\u03bc\u03b1\u03c4\u03b1 \u03b3\u03b9\u03b1 \u03b1\u03c3\u03c6\u03b1\u03bb\u03ad\u03c2 DSpark pilot<\/p>\n<ol>\n<li><span class=\"td-step-kicker\">\u0392\u03ae\u03bc\u03b1 1<\/span><strong>\u039a\u03bb\u03b5\u03b9\u03b4\u03ce\u03c3\u03c4\u03b5 \u03c4\u03bf target-only baseline<\/strong>\n<p>\u03a7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03ae\u03c3\u03c4\u03b5 \u03c4\u03bf \u03af\u03b4\u03b9\u03bf LFM2.5 checkpoint, prompt set, context, sampling \u03ba\u03b1\u03b9 runtime \u03c0\u03bf\u03c5 \u03b8\u03b1 \u03c7\u03c1\u03b7\u03c3\u03b9\u03bc\u03bf\u03c0\u03bf\u03b9\u03ae\u03c3\u03b5\u03b9 \u03c4\u03bf \u03c0\u03c1\u03bf\u03ca\u03cc\u03bd.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">\u0392\u03ae\u03bc\u03b1 2<\/span><strong>\u039f\u03c1\u03af\u03c3\u03c4\u03b5 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ac workloads<\/strong>\n<p>\u03a3\u03c5\u03bb\u03bb\u03ad\u03be\u03c4\u03b5 \u03b1\u03bd\u03c4\u03b9\u03c0\u03c1\u03bf\u03c3\u03c9\u03c0\u03b5\u03c5\u03c4\u03b9\u03ba\u03ac traces \u03b3\u03b9\u03b1 function calling, code, \u03b4\u03b9\u03ac\u03bb\u03bf\u03b3\u03bf \u03ba\u03b1\u03b9 \u03c4\u03b9\u03c2 \u03ba\u03c1\u03af\u03c3\u03b9\u03bc\u03b5\u03c2 \u03b5\u03bb\u03bb\u03b7\u03bd\u03b9\u03ba\u03ad\u03c2 \u03c1\u03bf\u03ad\u03c2 \u03c4\u03b7\u03c2 \u03b5\u03c0\u03b9\u03c7\u03b5\u03af\u03c1\u03b7\u03c3\u03b7\u03c2.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">\u0392\u03ae\u03bc\u03b1 3<\/span><strong>\u039c\u03b5\u03c4\u03c1\u03ae\u03c3\u03c4\u03b5 acceptance \u03b1\u03bd\u03ac \u03b5\u03c1\u03b3\u03b1\u03c3\u03af\u03b1<\/strong>\n<p>\u039c\u03b7\u03bd \u03ba\u03c1\u03cd\u03b2\u03b5\u03c4\u03b5 \u03c4\u03b9\u03c2 \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03ad\u03c2 \u03c3\u03b5 \u03ad\u03bd\u03b1\u03bd \u03b3\u03b5\u03bd\u03b9\u03ba\u03cc \u03bc\u03ad\u03c3\u03bf \u03cc\u03c1\u03bf\u00b7 \u03c3\u03c5\u03bd\u03b4\u03ad\u03c3\u03c4\u03b5 accepted tokens \u03bc\u03b5 latency \u03ba\u03b1\u03b9 business journey.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">\u0392\u03ae\u03bc\u03b1 4<\/span><strong>\u0395\u03bb\u03ad\u03b3\u03be\u03c4\u03b5 \u03c4\u03b7\u03bd exact \u03c3\u03c5\u03bd\u03b8\u03ae\u03ba\u03b7<\/strong>\n<p>\u039c\u03b5 temperature 0, \u03c3\u03c5\u03b3\u03ba\u03c1\u03af\u03bd\u03b5\u03c4\u03b5 \u03ba\u03ac\u03b8\u03b5 \u03ad\u03be\u03bf\u03b4\u03bf \u03bc\u03b5 \u03c4\u03bf target-only baseline \u03ba\u03b1\u03b9 \u03ba\u03c1\u03b1\u03c4\u03ae\u03c3\u03c4\u03b5 \u03be\u03b5\u03c7\u03c9\u03c1\u03b9\u03c3\u03c4\u03ae \u03b4\u03b9\u03b1\u03b4\u03b9\u03ba\u03b1\u03c3\u03af\u03b1 \u03b3\u03b9\u03b1 sampling modes.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">\u0392\u03ae\u03bc\u03b1 5<\/span><strong>\u0394\u03bf\u03ba\u03b9\u03bc\u03ac\u03c3\u03c4\u03b5 hardware \u03ba\u03b1\u03b9 concurrency<\/strong>\n<p>\u0395\u03c0\u03b1\u03bd\u03b1\u03bb\u03ac\u03b2\u03b5\u03c4\u03b5 H100, edge \u03ae laptop tests \u03bc\u03b5 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03cc batch, \u03bf\u03c5\u03c1\u03ac, quantization, context length \u03ba\u03b1\u03b9 \u03b8\u03b5\u03c1\u03bc\u03b9\u03ba\u03ae \u03c3\u03c5\u03bc\u03c0\u03b5\u03c1\u03b9\u03c6\u03bf\u03c1\u03ac.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">\u0392\u03ae\u03bc\u03b1 6<\/span><strong>\u039a\u03b1\u03c4\u03b1\u03b3\u03c1\u03ac\u03c8\u03c4\u03b5 operational \u03ba\u03cc\u03c3\u03c4\u03bf\u03c2<\/strong>\n<p>\u039c\u03b5\u03c4\u03c1\u03ae\u03c3\u03c4\u03b5 \u03c0\u03c1\u03cc\u03c3\u03b8\u03b5\u03c4\u03b7 \u03bc\u03bd\u03ae\u03bc\u03b7, startup, \u03c3\u03c5\u03bc\u03b2\u03b1\u03c4\u03cc\u03c4\u03b7\u03c4\u03b1 builds, telemetry, updates \u03ba\u03b1\u03b9 \u03c7\u03c1\u03cc\u03bd\u03bf \u03b1\u03c0\u03bf\u03ba\u03b1\u03c4\u03ac\u03c3\u03c4\u03b1\u03c3\u03b7\u03c2.<\/p>\n<\/li>\n<li><span class=\"td-step-kicker\">\u0392\u03ae\u03bc\u03b1 7<\/span><strong>\u0395\u03bd\u03b5\u03c1\u03b3\u03bf\u03c0\u03bf\u03b9\u03ae\u03c3\u03c4\u03b5 \u03b1\u03c3\u03c6\u03b1\u03bb\u03ad\u03c2 fallback<\/strong>\n<p>\u0391\u03bd \u03bf drafter \u03b1\u03c0\u03bf\u03c4\u03cd\u03c7\u03b5\u03b9 \u03ae \u03b4\u03b5\u03bd \u03c0\u03c1\u03bf\u03c3\u03c6\u03ad\u03c1\u03b5\u03b9 \u03ba\u03ad\u03c1\u03b4\u03bf\u03c2, \u03b5\u03c0\u03b9\u03c3\u03c4\u03c1\u03ad\u03c8\u03c4\u03b5 \u03b1\u03c5\u03c4\u03cc\u03bc\u03b1\u03c4\u03b1 \u03c3\u03b5 target-only decoding \u03ba\u03b1\u03b9 \u03b5\u03c0\u03b9\u03b2\u03b5\u03b2\u03b1\u03b9\u03ce\u03c3\u03c4\u03b5 \u03c4\u03b7\u03bd \u03b5\u03bc\u03c0\u03b5\u03b9\u03c1\u03af\u03b1.<\/p>\n<\/li>\n<\/ol>\n<\/div>\n<p>\u0397 \u03af\u03b4\u03b9\u03b1 \u03c0\u03b5\u03b9\u03b8\u03b1\u03c1\u03c7\u03af\u03b1 \u03b9\u03c3\u03c7\u03cd\u03b5\u03b9 \u03cc\u03c4\u03b1\u03bd \u03ad\u03bd\u03b1 AI demo \u03c0\u03b5\u03c1\u03bd\u03ac \u03c3\u03c4\u03b7\u03bd \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae. \u03a7\u03c9\u03c1\u03af\u03c2 observability, version pinning, permission boundaries \u03ba\u03b1\u03b9 recovery path, \u03b7 \u03c4\u03b1\u03c7\u03cd\u03c4\u03b5\u03c1\u03b7 \u03b1\u03c0\u03cc\u03ba\u03c1\u03b9\u03c3\u03b7 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03ba\u03c1\u03cd\u03c8\u03b5\u03b9 \u03bc\u03b5\u03b3\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03bf \u03bb\u03b5\u03b9\u03c4\u03bf\u03c5\u03c1\u03b3\u03b9\u03ba\u03cc \u03c1\u03af\u03c3\u03ba\u03bf. \u03a4\u03b1 <a href=\"https:\/\/twodots.gr\/ai-agent-demo-paragogi-pente-teixi-epicheirisis\/\">\u03c0\u03ad\u03bd\u03c4\u03b5 \u03b5\u03bc\u03c0\u03cc\u03b4\u03b9\u03b1 \u03b1\u03c0\u03cc \u03c4\u03bf AI agent demo \u03c3\u03c4\u03b7\u03bd \u03c0\u03b1\u03c1\u03b1\u03b3\u03c9\u03b3\u03ae<\/a> \u03c0\u03b1\u03c1\u03b1\u03bc\u03ad\u03bd\u03bf\u03c5\u03bd \u03c3\u03c7\u03b5\u03c4\u03b9\u03ba\u03ac, \u03b1\u03ba\u03cc\u03bc\u03b7 \u03ba\u03b9 \u03cc\u03c4\u03b1\u03bd \u03c4\u03bf \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03b1\u03c0\u03bf\u03ba\u03c1\u03af\u03bd\u03b5\u03c4\u03b1\u03b9 \u03c0\u03b9\u03bf \u03b3\u03c1\u03ae\u03b3\u03bf\u03c1\u03b1.<\/p>\n<h2 id=\"pote-axizei\">\u03a0\u03cc\u03c4\u03b5 \u03b1\u03be\u03af\u03b6\u03b5\u03b9 \u03c4\u03bf DSpark \u03ba\u03b1\u03b9 \u03c0\u03cc\u03c4\u03b5 \u03cc\u03c7\u03b9<\/h2>\n<p>\u03a4\u03bf DSpark \u03b1\u03be\u03af\u03b6\u03b5\u03b9 \u03cc\u03c4\u03b1\u03bd \u03c4\u03bf decoding \u03b5\u03af\u03bd\u03b1\u03b9 \u03bc\u03b5\u03c4\u03c1\u03b7\u03bc\u03ad\u03bd\u03bf bottleneck, \u03c4\u03b1 workloads \u03b5\u03af\u03bd\u03b1\u03b9 \u03b1\u03c1\u03ba\u03b5\u03c4\u03ac \u03c3\u03c4\u03b1\u03b8\u03b5\u03c1\u03ac, \u03c5\u03c0\u03ac\u03c1\u03c7\u03b5\u03b9 \u03bc\u03bd\u03ae\u03bc\u03b7 \u03b3\u03b9\u03b1 \u03c4\u03bf\u03bd drafter \u03ba\u03b1\u03b9 \u03c4\u03bf runtime \u03c5\u03c0\u03bf\u03c3\u03c4\u03b7\u03c1\u03af\u03b6\u03b5\u03c4\u03b1\u03b9 \u03b1\u03be\u03b9\u03cc\u03c0\u03b9\u03c3\u03c4\u03b1. \u0395\u03af\u03bd\u03b1\u03b9 \u03b9\u03b4\u03b9\u03b1\u03af\u03c4\u03b5\u03c1\u03b1 \u03b5\u03bd\u03b4\u03b9\u03b1\u03c6\u03ad\u03c1\u03bf\u03bd \u03cc\u03c4\u03b1\u03bd \u03c0\u03bf\u03bb\u03bb\u03ad\u03c2 \u03bc\u03b9\u03ba\u03c1\u03ad\u03c2 \u03ba\u03b1\u03b8\u03c5\u03c3\u03c4\u03b5\u03c1\u03ae\u03c3\u03b5\u03b9\u03c2 \u03b1\u03b8\u03c1\u03bf\u03af\u03b6\u03bf\u03bd\u03c4\u03b1\u03b9 \u03c3\u03b5 agentic journey \u03ae \u03cc\u03c4\u03b1\u03bd \u03c4\u03bf on-device \u03c0\u03c1\u03bf\u03ca\u03cc\u03bd \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03c0\u03b9\u03bf \u03ac\u03bc\u03b5\u03c3\u03b7 \u03b1\u03af\u03c3\u03b8\u03b7\u03c3\u03b7 \u03c7\u03c9\u03c1\u03af\u03c2 \u03b1\u03bd\u03c4\u03b9\u03ba\u03b1\u03c4\u03ac\u03c3\u03c4\u03b1\u03c3\u03b7 \u03c4\u03bf\u03c5 target.<\/p>\n<p>\u0394\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u03c0\u03c1\u03bf\u03c4\u03b5\u03c1\u03b1\u03b9\u03cc\u03c4\u03b7\u03c4\u03b1 \u03cc\u03c4\u03b1\u03bd \u03bf \u03c7\u03c1\u03cc\u03bd\u03bf\u03c2 \u03c7\u03ac\u03bd\u03b5\u03c4\u03b1\u03b9 \u03ba\u03c5\u03c1\u03af\u03c9\u03c2 \u03c3\u03b5 database queries, \u03b4\u03af\u03ba\u03c4\u03c5\u03bf, tool execution \u03ae \u03b1\u03bd\u03b8\u03c1\u03ce\u03c0\u03b9\u03bd\u03b7 \u03ad\u03b3\u03ba\u03c1\u03b9\u03c3\u03b7. \u0395\u03c0\u03af\u03c3\u03b7\u03c2 \u03b4\u03b5\u03bd \u03b1\u03c1\u03ba\u03b5\u03af \u03cc\u03c4\u03b1\u03bd \u03b7 \u03b1\u03c0\u03bf\u03c4\u03c5\u03c7\u03af\u03b1 \u03c4\u03bf\u03c5 agent \u03c0\u03c1\u03bf\u03ad\u03c1\u03c7\u03b5\u03c4\u03b1\u03b9 \u03b1\u03c0\u03cc \u03bb\u03ac\u03b8\u03bf\u03c2 \u03c3\u03c7\u03ad\u03b4\u03b9\u03bf \u03b5\u03c1\u03b3\u03b1\u03bb\u03b5\u03af\u03c9\u03bd, \u03b1\u03b4\u03cd\u03bd\u03b1\u03bc\u03bf retrieval \u03ae \u03b1\u03bd\u03b1\u03be\u03b9\u03cc\u03c0\u03b9\u03c3\u03c4\u03b7 \u03ad\u03be\u03bf\u03b4\u03bf. \u03a3\u03b5 \u03b1\u03c5\u03c4\u03ad\u03c2 \u03c4\u03b9\u03c2 \u03c0\u03b5\u03c1\u03b9\u03c0\u03c4\u03ce\u03c3\u03b5\u03b9\u03c2, \u03c4\u03bf optimization \u03c4\u03bf\u03c5 decode \u03b2\u03b5\u03bb\u03c4\u03b9\u03ce\u03bd\u03b5\u03b9 \u03c4\u03b7 \u03bb\u03ac\u03b8\u03bf\u03c2 \u03b4\u03b9\u03b1\u03b4\u03c1\u03bf\u03bc\u03ae.<\/p>\n<p>\u0397 \u03b1\u03c0\u03cc\u03c6\u03b1\u03c3\u03b7 \u03b5\u03af\u03bd\u03b1\u03b9 \u03bf\u03b9\u03ba\u03bf\u03bd\u03bf\u03bc\u03b9\u03ba\u03ae \u03ba\u03b1\u03b9 \u03c4\u03b5\u03c7\u03bd\u03b9\u03ba\u03ae \u03bc\u03b1\u03b6\u03af. \u03a3\u03c5\u03b3\u03ba\u03c1\u03af\u03bd\u03b5\u03c4\u03b5 \u03c4\u03b7\u03bd \u03b1\u03be\u03af\u03b1 \u03c4\u03b7\u03c2 \u03bc\u03b5\u03b9\u03c9\u03bc\u03ad\u03bd\u03b7\u03c2 \u03b1\u03bd\u03b1\u03bc\u03bf\u03bd\u03ae\u03c2 \u03bc\u03b5 \u03c0\u03c1\u03cc\u03c3\u03b8\u03b5\u03c4\u03b7 \u03bc\u03bd\u03ae\u03bc\u03b7, engineering effort, \u03c5\u03c0\u03bf\u03c3\u03c4\u03ae\u03c1\u03b9\u03be\u03b7 custom builds \u03ba\u03b1\u03b9 \u03b1\u03b4\u03b5\u03b9\u03bf\u03b4\u03bf\u03c4\u03b9\u03ba\u03ae \u03c3\u03c5\u03bc\u03bc\u03cc\u03c1\u03c6\u03c9\u03c3\u03b7. \u0391\u03bd \u03c4\u03bf \u03ba\u03ad\u03c1\u03b4\u03bf\u03c2 \u03bc\u03ad\u03bd\u03b5\u03b9 \u03bf\u03c5\u03c3\u03b9\u03b1\u03c3\u03c4\u03b9\u03ba\u03cc \u03c3\u03c4\u03b1 \u03ba\u03c1\u03af\u03c3\u03b9\u03bc\u03b1 journeys \u03ba\u03b1\u03b9 \u03c3\u03c4\u03bf p95, \u03c4\u03cc\u03c4\u03b5 \u03bc\u03c0\u03bf\u03c1\u03b5\u03af \u03bd\u03b1 \u03b4\u03b9\u03ba\u03b1\u03b9\u03bf\u03bb\u03bf\u03b3\u03b5\u03af rollout. \u0391\u03bd \u03b5\u03bc\u03c6\u03b1\u03bd\u03af\u03b6\u03b5\u03c4\u03b1\u03b9 \u03bc\u03cc\u03bd\u03bf \u03c3\u03c4\u03bf \u03ba\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03bf benchmark, \u03bc\u03ad\u03bd\u03b5\u03b9 \u03b5\u03bd\u03b4\u03b9\u03b1\u03c6\u03ad\u03c1\u03bf\u03bd \u03c0\u03b5\u03af\u03c1\u03b1\u03bc\u03b1.<\/p>\n<h2 id=\"epicheirimatiki-anagnosi\">\u0397 \u03c3\u03c9\u03c3\u03c4\u03ae \u03b5\u03c0\u03b9\u03c7\u03b5\u03b9\u03c1\u03b7\u03bc\u03b1\u03c4\u03b9\u03ba\u03ae \u03b1\u03bd\u03ac\u03b3\u03bd\u03c9\u03c3\u03b7 \u03c4\u03bf\u03c5 \u00ab\u03ad\u03c9\u03c2 3,18\u00d7\u00bb<\/h2>\n<p>\u03a4\u03bf DSpark \u03b5\u03af\u03bd\u03b1\u03b9 \u03c3\u03b7\u03bc\u03b1\u03bd\u03c4\u03b9\u03ba\u03cc \u03b5\u03c0\u03b5\u03b9\u03b4\u03ae \u03b5\u03c0\u03b9\u03c7\u03b5\u03b9\u03c1\u03b5\u03af \u03bd\u03b1 \u03bc\u03b5\u03b9\u03ce\u03c3\u03b5\u03b9 \u03c4\u03b7 latency \u03c7\u03c9\u03c1\u03af\u03c2 \u03bd\u03b1 \u03b1\u03bb\u03bb\u03ac\u03be\u03b5\u03b9 \u03c4\u03b7 greedy \u03ad\u03be\u03bf\u03b4\u03bf \u03c4\u03bf\u03c5 target. \u0394\u03b5\u03bd \u03b1\u03c0\u03b1\u03b9\u03c4\u03b5\u03af \u03b1\u03bd\u03c4\u03b9\u03ba\u03b1\u03c4\u03ac\u03c3\u03c4\u03b1\u03c3\u03b7 \u03bc\u03b5 \u03bc\u03b9\u03ba\u03c1\u03cc\u03c4\u03b5\u03c1\u03bf \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf \u03bf\u03cd\u03c4\u03b5 \u03b1\u03c0\u03bf\u03b4\u03bf\u03c7\u03ae \u03b4\u03b9\u03b1\u03c6\u03bf\u03c1\u03b5\u03c4\u03b9\u03ba\u03bf\u03cd quality profile \u03c3\u03c4\u03b7\u03bd \u03b5\u03c0\u03b1\u03bb\u03b7\u03b8\u03b5\u03c5\u03bc\u03ad\u03bd\u03b7 \u03b4\u03b9\u03b1\u03b4\u03c1\u03bf\u03bc\u03ae. \u03a4\u03bf \u03c4\u03af\u03bc\u03b7\u03bc\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03c0\u03c1\u03cc\u03c3\u03b8\u03b5\u03c4\u03b7 \u03bc\u03bd\u03ae\u03bc\u03b7, \u03b4\u03b5\u03cd\u03c4\u03b5\u03c1\u03bf checkpoint, \u03c3\u03c5\u03bc\u03b2\u03b1\u03c4\u03cc backend \u03ba\u03b1\u03b9 \u03b1\u03c0\u03cc\u03b4\u03bf\u03c3\u03b7 \u03c0\u03bf\u03c5 \u03b5\u03be\u03b1\u03c1\u03c4\u03ac\u03c4\u03b1\u03b9 \u03ad\u03bd\u03c4\u03bf\u03bd\u03b1 \u03b1\u03c0\u03cc \u03c4\u03b7\u03bd \u03c0\u03c1\u03bf\u03b2\u03bb\u03b5\u03c8\u03b9\u03bc\u03cc\u03c4\u03b7\u03c4\u03b1 \u03c4\u03bf\u03c5 workload.<\/p>\n<p>\u0393\u03b9\u03b1 \u03bc\u03b9\u03b1 \u03b5\u03c0\u03b9\u03c7\u03b5\u03af\u03c1\u03b7\u03c3\u03b7, \u03c4\u03bf \u03c3\u03c9\u03c3\u03c4\u03cc \u03c3\u03c5\u03bc\u03c0\u03ad\u03c1\u03b1\u03c3\u03bc\u03b1 \u03b4\u03b5\u03bd \u03b5\u03af\u03bd\u03b1\u03b9 \u00ab\u03c4\u03bf AI \u03bc\u03b1\u03c2 \u03b8\u03b1 \u03b3\u03af\u03bd\u03b5\u03b9 3,18 \u03c6\u03bf\u03c1\u03ad\u03c2 \u03b3\u03c1\u03b7\u03b3\u03bf\u03c1\u03cc\u03c4\u03b5\u03c1\u03bf\u00bb. \u0395\u03af\u03bd\u03b1\u03b9 \u00ab\u03c5\u03c0\u03ac\u03c1\u03c7\u03b5\u03b9 \u03bc\u03b9\u03b1 \u03c4\u03b5\u03c7\u03bd\u03b9\u03ba\u03ae \u03c0\u03bf\u03c5 \u03b1\u03be\u03af\u03b6\u03b5\u03b9 \u03bd\u03b1 \u03bc\u03b5\u03c4\u03c1\u03b7\u03b8\u03b5\u03af \u03c3\u03c4\u03b1 \u03b4\u03b9\u03ba\u03ac \u03bc\u03b1\u03c2 traces\u00bb. \u0391\u03bd \u03bc\u03b5\u03b9\u03ce\u03bd\u03b5\u03b9 \u03c3\u03c4\u03b1\u03b8\u03b5\u03c1\u03ac \u03c4\u03b7\u03bd end-to-end latency \u03c7\u03c9\u03c1\u03af\u03c2 \u03b1\u03bb\u03bb\u03b1\u03b3\u03ae \u03b5\u03be\u03cc\u03b4\u03bf\u03c5, \u03c7\u03c9\u03c1\u03af\u03c2 \u03bd\u03ad\u03bf operational \u03c1\u03af\u03c3\u03ba\u03bf \u03ba\u03b1\u03b9 \u03bc\u03b5 \u03b2\u03b9\u03ce\u03c3\u03b9\u03bc\u03bf \u03ba\u03cc\u03c3\u03c4\u03bf\u03c2, \u03c4\u03cc\u03c4\u03b5 \u03c4\u03bf speculative decoding \u03c0\u03b5\u03c1\u03bd\u03ac \u03b1\u03c0\u03cc \u03b5\u03bd\u03c4\u03c5\u03c0\u03c9\u03c3\u03b9\u03b1\u03ba\u03cc benchmark \u03c3\u03b5 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03cc \u03c0\u03bb\u03b5\u03bf\u03bd\u03ad\u03ba\u03c4\u03b7\u03bc\u03b1 \u03b5\u03bc\u03c0\u03b5\u03b9\u03c1\u03af\u03b1\u03c2.<\/p>\n<section class=\"td-service-cta\">\n<div class=\"td-service-cta-content\">\n<p class=\"td-service-cta-kicker\">\u0391\u03c5\u03c4\u03bf\u03bc\u03b1\u03c4\u03b9\u03c3\u03bc\u03bf\u03af \u0395\u03c0\u03b9\u03c7\u03b5\u03b9\u03c1\u03ae\u03c3\u03b5\u03c9\u03bd &amp; AI<\/p>\n<h3>\u039c\u03b5\u03c4\u03c1\u03ae\u03c3\u03c4\u03b5 \u03c4\u03bf AI workflow \u03c0\u03c1\u03b9\u03bd \u03b2\u03b5\u03bb\u03c4\u03b9\u03c3\u03c4\u03bf\u03c0\u03bf\u03b9\u03ae\u03c3\u03b5\u03c4\u03b5 \u03c4\u03bf \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf<\/h3>\n<p>\u0397 TWO DOTS \u03c3\u03c7\u03b5\u03b4\u03b9\u03ac\u03b6\u03b5\u03b9 \u03b1\u03c3\u03c6\u03b1\u03bb\u03b5\u03af\u03c2 \u03b1\u03c5\u03c4\u03bf\u03bc\u03b1\u03c4\u03b9\u03c3\u03bc\u03bf\u03cd\u03c2 \u03ba\u03b1\u03b9 AI \u03c1\u03bf\u03ad\u03c2 \u03bc\u03b5 \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ac business journeys, permissions, monitoring \u03ba\u03b1\u03b9 fallback, \u03ce\u03c3\u03c4\u03b5 \u03b7 \u03c4\u03b1\u03c7\u03cd\u03c4\u03b7\u03c4\u03b1 \u03bd\u03b1 \u03bc\u03b5\u03c4\u03b1\u03c4\u03c1\u03ad\u03c0\u03b5\u03c4\u03b1\u03b9 \u03c3\u03b5 \u03b1\u03be\u03b9\u03cc\u03c0\u03b9\u03c3\u03c4\u03b7 \u03b5\u03bc\u03c0\u03b5\u03b9\u03c1\u03af\u03b1.<\/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 \u0391\u03c5\u03c4\u03bf\u03bc\u03b1\u03c4\u03b9\u03c3\u03bc\u03bf\u03cd\u03c2 \u0395\u03c0\u03b9\u03c7\u03b5\u03b9\u03c1\u03ae\u03c3\u03b5\u03c9\u03bd &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\">\u03a3\u03c5\u03c7\u03bd\u03ad\u03c2 \u03b5\u03c1\u03c9\u03c4\u03ae\u03c3\u03b5\u03b9\u03c2<\/p>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u03a4\u03b9 \u03b5\u03af\u03bd\u03b1\u03b9 \u03c4\u03bf speculative decoding;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u0395\u03af\u03bd\u03b1\u03b9 \u03c4\u03b5\u03c7\u03bd\u03b9\u03ba\u03ae \u03cc\u03c0\u03bf\u03c5 \u03ad\u03bd\u03b1 \u03bc\u03b9\u03ba\u03c1\u03cc draft model \u03c0\u03c1\u03bf\u03c4\u03b5\u03af\u03bd\u03b5\u03b9 \u03c0\u03bf\u03bb\u03bb\u03ac \u03b5\u03c0\u03cc\u03bc\u03b5\u03bd\u03b1 tokens \u03ba\u03b1\u03b9 \u03c4\u03bf target model \u03c4\u03b1 \u03b5\u03c0\u03b1\u03bb\u03b7\u03b8\u03b5\u03cd\u03b5\u03b9 \u03bc\u03b1\u03b6\u03af, \u03bc\u03b5\u03b9\u03ce\u03bd\u03bf\u03bd\u03c4\u03b1\u03c2 \u03c4\u03b1 \u03c3\u03b5\u03b9\u03c1\u03b9\u03b1\u03ba\u03ac decode steps \u03cc\u03c4\u03b1\u03bd \u03b1\u03c1\u03ba\u03b5\u03c4\u03ad\u03c2 \u03c0\u03c1\u03bf\u03c4\u03ac\u03c3\u03b5\u03b9\u03c2 \u03b3\u03af\u03bd\u03bf\u03bd\u03c4\u03b1\u03b9 \u03b1\u03c0\u03bf\u03b4\u03b5\u03ba\u03c4\u03ad\u03c2.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u0391\u03bb\u03bb\u03ac\u03b6\u03b5\u03b9 \u03c4\u03bf DSpark \u03c4\u03b7\u03bd \u03b1\u03c0\u03ac\u03bd\u03c4\u03b7\u03c3\u03b7 \u03c4\u03bf\u03c5 LFM2.5;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u039c\u03b5 greedy decoding \u03ba\u03b1\u03b9 temperature 0, \u03b7 \u03b5\u03c0\u03b1\u03bb\u03b7\u03b8\u03b5\u03c5\u03bc\u03ad\u03bd\u03b7 \u03b1\u03ba\u03bf\u03bb\u03bf\u03c5\u03b8\u03af\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03af\u03b4\u03b9\u03b1 \u03bc\u03b5 \u03b5\u03ba\u03b5\u03af\u03bd\u03b7 \u03c4\u03bf\u03c5 target-only baseline, \u03b5\u03c0\u03b5\u03b9\u03b4\u03ae \u03ba\u03ac\u03b8\u03b5 draft token \u03b5\u03ba\u03c0\u03ad\u03bc\u03c0\u03b5\u03c4\u03b1\u03b9 \u03bc\u03cc\u03bd\u03bf \u03cc\u03c4\u03b1\u03bd \u03c3\u03c5\u03bc\u03c6\u03c9\u03bd\u03b5\u03af \u03bc\u03b5 \u03c4\u03b7\u03bd \u03b5\u03c0\u03b9\u03bb\u03bf\u03b3\u03ae \u03c4\u03bf\u03c5 target.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u0393\u03b9\u03b1\u03c4\u03af \u03ad\u03c7\u03b5\u03b9 \u03c3\u03b7\u03bc\u03b1\u03c3\u03af\u03b1 \u03c4\u03bf temperature 0;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u0395\u03c0\u03b5\u03b9\u03b4\u03ae \u03b7 \u03c4\u03b5\u03ba\u03bc\u03b7\u03c1\u03b9\u03c9\u03bc\u03ad\u03bd\u03b7 exact \u03b9\u03c3\u03bf\u03b4\u03c5\u03bd\u03b1\u03bc\u03af\u03b1 \u03b1\u03c6\u03bf\u03c1\u03ac greedy \u03b5\u03c0\u03b9\u03bb\u03bf\u03b3\u03ae. \u0394\u03b5\u03bd \u03c0\u03c1\u03ad\u03c0\u03b5\u03b9 \u03bd\u03b1 \u03b8\u03b5\u03c9\u03c1\u03b5\u03af\u03c4\u03b1\u03b9 \u03b4\u03b5\u03b4\u03bf\u03bc\u03ad\u03bd\u03b7 \u03b7 \u03af\u03b4\u03b9\u03b1 \u03c3\u03c5\u03bc\u03c0\u03b5\u03c1\u03b9\u03c6\u03bf\u03c1\u03ac \u03c3\u03b5 \u03ba\u03ac\u03b8\u03b5 sampling configuration \u03c7\u03c9\u03c1\u03af\u03c2 \u03be\u03b5\u03c7\u03c9\u03c1\u03b9\u03c3\u03c4\u03ae \u03b5\u03c0\u03b1\u03bb\u03ae\u03b8\u03b5\u03c5\u03c3\u03b7.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u0395\u03af\u03bd\u03b1\u03b9 \u03ba\u03ac\u03b8\u03b5 workload 3,18 \u03c6\u03bf\u03c1\u03ad\u03c2 \u03b3\u03c1\u03b7\u03b3\u03bf\u03c1\u03cc\u03c4\u03b5\u03c1\u03bf;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u038c\u03c7\u03b9. \u03a4\u03bf 3,18\u00d7 \u03b5\u03af\u03bd\u03b1\u03b9 \u03b7 \u03ba\u03b1\u03bb\u03cd\u03c4\u03b5\u03c1\u03b7 vendor-reported \u03c0\u03b5\u03c1\u03af\u03c0\u03c4\u03c9\u03c3\u03b7 \u03c3\u03b5 H100 \u03ba\u03b1\u03b9 MATH500. \u0397 \u03b1\u03c0\u03cc\u03b4\u03bf\u03c3\u03b7 \u03b1\u03bb\u03bb\u03ac\u03b6\u03b5\u03b9 \u03b1\u03bd\u03ac \u03bc\u03bf\u03bd\u03c4\u03ad\u03bb\u03bf, dataset, acceptance rate, hardware, backend \u03ba\u03b1\u03b9 \u03c1\u03c5\u03b8\u03bc\u03af\u03c3\u03b5\u03b9\u03c2.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u03a0\u03cc\u03c3\u03b7 \u03b5\u03c0\u03b9\u03c0\u03bb\u03ad\u03bf\u03bd \u03bc\u03bd\u03ae\u03bc\u03b7 \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03c4\u03bf DSpark;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u0395\u03be\u03b1\u03c1\u03c4\u03ac\u03c4\u03b1\u03b9 \u03b1\u03c0\u03cc checkpoint \u03ba\u03b1\u03b9 format. \u039f\u03b9 \u03b4\u03b7\u03bc\u03bf\u03c3\u03b9\u03b5\u03c5\u03bc\u03ad\u03bd\u03bf\u03b9 drafters \u03ad\u03c7\u03bf\u03c5\u03bd 295,7 \u03ae 327,7 \u03b5\u03ba\u03b1\u03c4\u03bf\u03bc\u03bc\u03cd\u03c1\u03b9\u03b1 \u03c0\u03b1\u03c1\u03b1\u03bc\u03ad\u03c4\u03c1\u03bf\u03c5\u03c2, \u03ac\u03c1\u03b1 \u03c7\u03c1\u03b5\u03b9\u03ac\u03b6\u03bf\u03bd\u03c4\u03b1\u03b9 \u03c0\u03c1\u03cc\u03c3\u03b8\u03b5\u03c4\u03b7 \u03bc\u03bd\u03ae\u03bc\u03b7 \u03c0\u03ad\u03c1\u03b1 \u03b1\u03c0\u03cc \u03c4\u03bf target model.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u03a0\u03bf\u03b9\u03b1 runtimes \u03c5\u03c0\u03bf\u03c3\u03c4\u03b7\u03c1\u03af\u03b6\u03bf\u03c5\u03bd \u03c4\u03b1 LFM2.5-DSpark checkpoints;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u0397 Liquid AI \u03c4\u03b5\u03ba\u03bc\u03b7\u03c1\u03b9\u03ce\u03bd\u03b5\u03b9 SGLang \u03b3\u03b9\u03b1 GPU serving \u03ba\u03b1\u03b9 llama.cpp \u03bc\u03b5 Metal \u03b3\u03b9\u03b1 on-device \u03c7\u03c1\u03ae\u03c3\u03b7, \u03bc\u03b5 \u03ba\u03b1\u03c4\u03ac\u03bb\u03bb\u03b7\u03bb\u03b1 builds \u03c0\u03bf\u03c5 \u03c5\u03c0\u03bf\u03c3\u03c4\u03b7\u03c1\u03af\u03b6\u03bf\u03c5\u03bd DSpark \u03ba\u03b1\u03b9 LFM2 targets.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u0393\u03b9\u03b1\u03c4\u03af \u03c4\u03bf 8B-A1B \u03ba\u03ad\u03c1\u03b4\u03b9\u03c3\u03b5 \u03bb\u03b9\u03b3\u03cc\u03c4\u03b5\u03c1\u03bf \u03c3\u03c4\u03bf M4 Max;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u0397 Liquid AI \u03b1\u03c0\u03bf\u03b4\u03af\u03b4\u03b5\u03b9 \u03c4\u03bf \u03bc\u03ad\u03c3\u03bf 1,18\u00d7 \u03c3\u03c4\u03b7\u03bd \u03c4\u03c1\u03ad\u03c7\u03bf\u03c5\u03c3\u03b1 MoE \u03c5\u03bb\u03bf\u03c0\u03bf\u03af\u03b7\u03c3\u03b7 \u03c4\u03bf\u03c5 Metal backend \u03ba\u03b1\u03b9 \u03c3\u03c4\u03b7\u03bd \u03b5\u03c0\u03b9\u03c0\u03bb\u03ad\u03bf\u03bd \u03ba\u03af\u03bd\u03b7\u03c3\u03b7 \u03b2\u03b1\u03c1\u03ce\u03bd \u03cc\u03c4\u03b1\u03bd \u03b7 \u03b5\u03c0\u03b1\u03bb\u03ae\u03b8\u03b5\u03c5\u03c3\u03b7 \u03b5\u03bd\u03b5\u03c1\u03b3\u03bf\u03c0\u03bf\u03b9\u03b5\u03af \u03c0\u03b5\u03c1\u03b9\u03c3\u03c3\u03cc\u03c4\u03b5\u03c1\u03bf\u03c5\u03c2 experts.<\/p>\n<\/div>\n<\/details>\n<details class=\"td-faq-item\">\n<summary class=\"td-faq-title\">\u03a0\u03bf\u03b9\u03b1 \u03b5\u03af\u03bd\u03b1\u03b9 \u03b7 \u03c3\u03b7\u03bc\u03b1\u03bd\u03c4\u03b9\u03ba\u03cc\u03c4\u03b5\u03c1\u03b7 \u03bc\u03ad\u03c4\u03c1\u03b7\u03c3\u03b7 \u03c3\u03b5 \u03ad\u03bd\u03b1 pilot;<\/summary>\n<div class=\"td-faq-content\">\n<p>\u0397 end-to-end latency \u03c4\u03c9\u03bd \u03c0\u03c1\u03b1\u03b3\u03bc\u03b1\u03c4\u03b9\u03ba\u03ce\u03bd workflows, \u03bc\u03b1\u03b6\u03af \u03bc\u03b5 p95, acceptance \u03b1\u03bd\u03ac \u03b5\u03c1\u03b3\u03b1\u03c3\u03af\u03b1, \u03bc\u03bd\u03ae\u03bc\u03b7, concurrency, \u03c0\u03bf\u03b9\u03cc\u03c4\u03b7\u03c4\u03b1 \u03b5\u03be\u03cc\u03b4\u03bf\u03c5 \u03ba\u03b1\u03b9 \u03c3\u03c5\u03bc\u03c0\u03b5\u03c1\u03b9\u03c6\u03bf\u03c1\u03ac fallback. \u03a4\u03b1 tokens \u03b1\u03bd\u03ac \u03b4\u03b5\u03c5\u03c4\u03b5\u03c1\u03cc\u03bb\u03b5\u03c0\u03c4\u03bf \u03b4\u03b5\u03bd \u03b1\u03c1\u03ba\u03bf\u03cd\u03bd \u03bc\u03cc\u03bd\u03b1 \u03c4\u03bf\u03c5\u03c2.<\/p>\n<\/div>\n<\/details>\n<\/div>\n<\/section>\n<div class=\"td-source-list\">\n<p id=\"piges\" class=\"td-source-list-title\">\u03a0\u03b7\u03b3\u03ad\u03c2<\/p>\n<ul>\n<li><a href=\"https:\/\/huggingface.co\/blog\/LiquidAI\/lfm25-dspark\" target=\"_blank\" rel=\"noopener\">Liquid AI \u03c3\u03c4\u03bf Hugging Face, Up to 3.2x Faster Inference with LFM2.5-DSpark<\/a><\/li>\n<li><a href=\"https:\/\/huggingface.co\/LiquidAI\/LFM2.5-2.6B-DSpark\" target=\"_blank\" rel=\"noopener\">Liquid AI, LFM2.5-2.6B-DSpark model card<\/a><\/li>\n<li><a href=\"https:\/\/huggingface.co\/LiquidAI\/LFM2.5-8B-A1B-DSpark\" target=\"_blank\" rel=\"noopener\">Liquid AI, LFM2.5-8B-A1B-DSpark model card<\/a><\/li>\n<li><a href=\"https:\/\/arxiv.org\/abs\/2607.05147\" target=\"_blank\" rel=\"noopener\">DSpark paper, Confidence-Scheduled Speculative Decoding with Semi-Autoregressive Generation<\/a><\/li>\n<li><a href=\"https:\/\/github.com\/sgl-project\/sglang\/pull\/31041\" target=\"_blank\" rel=\"noopener\">SGLang, LFM2 and LFM2-MoE DSpark support<\/a><\/li>\n<li><a href=\"https:\/\/github.com\/ggml-org\/llama.cpp\/pull\/27383\" target=\"_blank\" rel=\"noopener\">llama.cpp, DSpark support for LFM2 models<\/a><\/li>\n<li><a href=\"https:\/\/www.liquid.ai\/lfm-license\" target=\"_blank\" rel=\"noopener\">Liquid AI, LFM Open License v1.0<\/a><\/li>\n<\/ul>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>\u03a4\u03bf speculative decoding \u03bc\u03b5 DSpark \u03b5\u03c0\u03b9\u03c4\u03b1\u03c7\u03cd\u03bd\u03b5\u03b9 \u03c4\u03bf LFM2.5 \u03c7\u03c9\u03c1\u03af\u03c2 \u03b1\u03bb\u03bb\u03b1\u03b3\u03ae \u03c4\u03b7\u03c2 greedy \u03b5\u03be\u03cc\u03b4\u03bf\u03c5. \u0394\u03b5\u03af\u03c4\u03b5 \u03c0\u03ce\u03c2 \u03bb\u03b5\u03b9\u03c4\u03bf\u03c5\u03c1\u03b3\u03b5\u03af, \u03c4\u03b9 \u03ad\u03b4\u03b5\u03b9\u03be\u03b1\u03bd H100 \u03ba\u03b1\u03b9 M4 Max \u03ba\u03b1\u03b9 \u03c0\u03ce\u03c2 \u03c3\u03c7\u03b5\u03b4\u03b9\u03ac\u03b6\u03b5\u03c4\u03b1\u03b9 \u03b1\u03c3\u03c6\u03b1\u03bb\u03ad\u03c2 production pilot.<\/p>","protected":false},"author":1,"featured_media":89650,"comment_status":"open","ping_status":"","sticky":false,"template":"","format":"standard","meta":{"_gspb_post_css":"","content-type":"","footnotes":""},"categories":[199],"tags":[6506,8988,19544,19543,19545],"class_list":["post-89641","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-techniti-noimosyni","tag-ai-agents","tag-ai-infrastructure","tag-dspark","tag-lfm2-5","tag-speculative-decoding"],"blocksy_meta":{"styles_descriptor":{"styles":{"desktop":"","tablet":"","mobile":""},"google_fonts":[],"version":7}},"_links":{"self":[{"href":"https:\/\/twodots.gr\/hr\/wp-json\/wp\/v2\/posts\/89641","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/twodots.gr\/hr\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/twodots.gr\/hr\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/twodots.gr\/hr\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/twodots.gr\/hr\/wp-json\/wp\/v2\/comments?post=89641"}],"version-history":[{"count":1,"href":"https:\/\/twodots.gr\/hr\/wp-json\/wp\/v2\/posts\/89641\/revisions"}],"predecessor-version":[{"id":89651,"href":"https:\/\/twodots.gr\/hr\/wp-json\/wp\/v2\/posts\/89641\/revisions\/89651"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/twodots.gr\/hr\/wp-json\/wp\/v2\/media\/89650"}],"wp:attachment":[{"href":"https:\/\/twodots.gr\/hr\/wp-json\/wp\/v2\/media?parent=89641"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/twodots.gr\/hr\/wp-json\/wp\/v2\/categories?post=89641"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/twodots.gr\/hr\/wp-json\/wp\/v2\/tags?post=89641"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}