{"id":125519,"date":"2025-05-23T15:05:12","date_gmt":"2025-05-23T13:05:12","guid":{"rendered":"https:\/\/prohoster.info\/blog\/novosti-interneta\/mistral-ai-opublikoval-devstral-bolshuyu-yazykovuyu-model-dlya-raboty-s-kodom"},"modified":"2025-05-23T15:05:12","modified_gmt":"2025-05-23T13:05:12","slug":"mistral-ai-opublikoval-devstral-bolshuyu-yazykovuyu-model-dlya-raboty-s-kodom","status":"publish","type":"post","link":"https:\/\/prohoster.info\/sk\/blog\/news\/mistral-ai-opublikoval-devstral-bolshuyu-yazykovuyu-model-dlya-raboty-s-kodom","title":{"rendered":"Mistral AI publikoval Devstral, ve\u013ek\u00fd jazykov\u00fd model na pr\u00e1cu s k\u00f3dom.","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

Spolo\u010dnos\u0165 Mistral AI predstavila ve\u013ek\u00fd jazykov\u00fd model Devstral, optimalizovan\u00fd na rie\u0161enie probl\u00e9mov, ktor\u00e9 sa vyskytn\u00fa po\u010das v\u00fdvoja softv\u00e9ru. Na rozdiel od be\u017en\u00fdch AI modelov, Mistral AI presahuje p\u00edsanie jednotliv\u00fdch funkci\u00ed a dopl\u0148ovanie k\u00f3du a poskytuje mo\u017enosti, ktor\u00e9 umo\u017e\u0148uj\u00fa analyzova\u0165 a kontextualizova\u0165 (ur\u010di\u0165 \u00fa\u010del a logiku fungovania) ve\u013ek\u00e9 k\u00f3dov\u00e9 z\u00e1klady, ur\u010dova\u0165 vz\u0165ahy medzi komponentmi a odha\u013eova\u0165 \u0165a\u017eko identifikovate\u013en\u00e9 chyby v zamotan\u00fdch funkci\u00e1ch. <\/p>\n

Model pokr\u00fdva 23,6 miliardy parametrov, berie do \u00favahy kontext vo 128 tis\u00edcoch tokenov a je publikovan\u00e1 pod licenciou Apache 2.0. S\u0165ahovan\u00fd arch\u00edv s Devstral zaber\u00e1 47 GB a je vhodn\u00fd na pou\u017eitie na lok\u00e1lnych syst\u00e9moch \u2014 na spustenie modelu sta\u010d\u00ed jeden PC s grafickou kartou NVIDIA GeForce RTX 4090 a 32 GB RAM. Model je mo\u017en\u00e9 vyu\u017ei\u0165 v otvoren\u00fdch n\u00e1strojoch SWE-agent a OpenHands na automatiz\u00e1ciu opravy ch\u00fdb, anal\u00fdzu k\u00f3du a vykon\u00e1vanie zmien. <\/p>\n

Syst\u00e9m m\u00f4\u017ee by\u0165 pou\u017eit\u00fd na rie\u0161enie konkr\u00e9tnych probl\u00e9mov (issue) na GitHub a v\u00fdrazne predbehol in\u00e9 projekty v testovacom s\u00fabore SWE-Bench Verified, ktor\u00fd kontroluje spr\u00e1vnos\u0165 rie\u0161enia \u0161tandardn\u00fdch probl\u00e9mov v k\u00f3de (pon\u00faka 500 testov na z\u00e1klade skuto\u010dn\u00fdch chybov\u00fdch hl\u00e1sen\u00ed na GitHub). V tomto teste model Devstral z\u00edskal 46,8%, zatia\u013e \u010do model Claude 3.5 Haiku dosiahol 40,6%, SWE-smith-LM 32B \u2014 40,2% a GPT-4.1-mini \u2014 23,6%. Okrem toho Devstral predbehol aj v\u00e4\u010d\u0161ie modely, ako Deepseek-V3-0324 671B (38,8%) a Qwen3 232B-A22B (34,4%), ktor\u00e9 pokr\u00fdvaj\u00fa stovky mili\u00e1rd parametrov.
\n
Zdroj: opennet.ru<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

\u041a\u043e\u043c\u043f\u0430\u043d\u0438\u044f Mistral AI \u043f\u0440\u0435\u0434\u0441\u0442\u0430\u0432\u0438\u043b\u0430 \u0431\u043e\u043b\u044c\u0448\u0443\u044e \u044f\u0437\u044b\u043a\u043e\u0432\u0443\u044e \u043c\u043e\u0434\u0435\u043b\u044c Devstral, \u043e\u043f\u0442\u0438\u043c\u0438\u0437\u0438\u0440\u043e\u0432\u0430\u043d\u043d\u0443\u044e \u0434\u043b\u044f \u0440\u0435\u0448\u0435\u043d\u0438\u044f \u043f\u0440\u043e\u0431\u043b\u0435\u043c, \u0432\u043e\u0437\u043d\u0438\u043a\u0430\u044e\u0449\u0438\u0445 \u0432 \u043f\u0440\u043e\u0446\u0435\u0441\u0441\u0435 \u0440\u0430\u0437\u0440\u0430\u0431\u043e\u0442\u043a\u0438 \u041f\u041e. \u0412 \u043e\u0442\u043b\u0438\u0447\u0438\u0435 \u043e\u0442 \u0442\u0438\u043f\u043e\u0432\u044b\u0445 AI-\u043c\u043e\u0434\u0435\u043b\u0435\u0439, Mistral AI \u0432\u044b\u0445\u043e\u0434\u0438\u0442 \u0437\u0430 \u0440\u0430\u043c\u043a\u0438 \u043d\u0430\u043f\u0438\u0441\u0430\u043d\u0438\u044f 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