{"id":167258,"date":"2026-04-03T05:11:55","date_gmt":"2026-04-03T03:11:56","guid":{"rendered":"https:\/\/prohoster.info\/blog\/novosti-interneta\/google-vypustil-otkrytuyu-ai-model-gemma-4-postroennuyu-na-tehnologiyah-gemini-3"},"modified":"2026-04-03T05:11:55","modified_gmt":"2026-04-03T03:11:56","slug":"google-vypustil-otkrytuyu-ai-model-gemma-4-postroennuyu-na-tehnologiyah-gemini-3","status":"publish","type":"post","link":"https:\/\/prohoster.info\/sv\/blog\/news\/google-vypustil-otkrytuyu-ai-model-gemma-4-postroennuyu-na-tehnologiyah-gemini-3","title":{"rendered":"Google har lanserat den \u00f6ppna AI-modellen Gemma 4, byggd p\u00e5 Gemini 3-teknologin","gt_translate_keys":[{"key":"rendered","format":"text"}]},"content":{"rendered":"

Google har publicerat en ny familj av stora spr\u00e5kliga modeller Gemma 4, baserade p\u00e5 Gemini 3-modellen. Gemma 4 distribueras under Apache-licens i varianter med 2,3, 4,5, 25,2 och 30,7 miljarder parametrar (E2B, E4B, 31B och 26B A4B). E2B- och E4B-varianterna \u00e4r l\u00e4mpliga f\u00f6r anv\u00e4ndning p\u00e5 mobila enheter, Internet of Things (IoT)-system och Raspberry Pi-kort, medan de andra varianterna \u00e4r anv\u00e4ndbara p\u00e5 datorer med konsument-GPU:er. Den modellens kontextstorlek \u00e4r 128 000 tokens f\u00f6r E2B- och E4B-modellerna, och 256 000 tokens f\u00f6r 31B och 26B A4B-modellerna. <\/p>\n

Modellerna \u00e4r flerspr\u00e5kiga och multimodala: de st\u00f6der 35 spr\u00e5k direkt (mer \u00e4n 140 spr\u00e5k anv\u00e4ndes vid tr\u00e4ningen), och kan bearbeta text och bilder (E2B- och E4B-modellerna st\u00f6der dessutom ljudbearbetning). 26B A4B-modellen bygger p\u00e5 MoE-arkitektur (Mixture-of-Experts), d\u00e4r modellen delas upp i en serie expert-n\u00e4tverk (vid svarsgenerering kan endast 3,8 miljarder parametrar anv\u00e4ndas, men hastigheten \u00e4r avsev\u00e4rt h\u00f6gre \u00e4n klassiska stora modeller), medan \u00f6vriga varianter anv\u00e4nder en klassisk monolitisk arkitektur. <\/p>\n

Modellerna st\u00f6der resonemang och anpassningsbara tankes\u00e4tt, och de har en systemroll (System Role) f\u00f6r att bearbeta instruktioner (regler, begr\u00e4nsningar) separat fr\u00e5n data. Modellerna kan anv\u00e4ndas f\u00f6r att skriva kod, k\u00e4nna igen objekt p\u00e5 bilder, g\u00f6ra frame-by-frame analys av video, bearbeta dokument och PDF-filer, utf\u00f6ra optisk teckenigenk\u00e4nning (OCR) f\u00f6r tryckt och handskriven text, k\u00e4nna igen tal och \u00f6vers\u00e4tta mellan spr\u00e5k. Det \u00e4r m\u00f6jligt att anv\u00e4nda dem som autonoma agenter som interagerar med olika verktyg och API:er. <\/p>\n

I de flesta tester \u00f6vertr\u00e4ffade modellerna i Gemma 4-serien modellen Gemma 3 med 27 miljarder parametrar avsev\u00e4rt. Det st\u00f6ds anv\u00e4ndning av Gemma 4 med verktyg och bibliotek som LiteRT-LM, vLLM, llama.cpp, MLX, Ollama, NVIDIA NIM och NeMo, LM Studio, Unsloth, SGLang, Cactus, Basetan, MaxText, Tunix och Keras.

\"Google<\/center>
\"Google<\/center>
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K\u00e4lla: opennet.ru<\/a> <\/p>","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"excerpt":{"rendered":"

\u041a\u043e\u043c\u043f\u0430\u043d\u0438\u044f Google \u043e\u043f\u0443\u0431\u043b\u0438\u043a\u043e\u0432\u0430\u043b\u0430 \u043d\u043e\u0432\u043e\u0435 \u0441\u0435\u043c\u0435\u0439\u0441\u0442\u0432\u043e \u0431\u043e\u043b\u044c\u0448\u0438\u0445 \u044f\u0437\u044b\u043a\u043e\u0432\u044b\u0445 \u043c\u043e\u0434\u0435\u043b\u0435\u0439 Gemma 4, \u043e\u0441\u043d\u043e\u0432\u0430\u043d\u043d\u044b\u0445 \u043d\u0430 \u0442\u0435\u0445\u043d\u043e\u043b\u043e\u0433\u0438\u044f\u0445 \u043c\u043e\u0434\u0435\u043b\u0438 Gemini 3. Gemma 4 \u0440\u0430\u0441\u043f\u0440\u043e\u0441\u0442\u0440\u0430\u043d\u044f\u0435\u0442\u0441\u044f \u043f\u043e\u0434 \u043b\u0438\u0446\u0435\u043d\u0437\u0438\u0435\u0439 Apache \u0432 \u0432\u0430\u0440\u0438\u0430\u043d\u0442\u0430\u0445 \u0441 2.3, 4.5, 25.2 \u0438 30.7 \u043c\u0438\u043b\u043b\u0438\u0430\u0440\u0434\u0430\u043c\u0438 \u043f\u0430\u0440\u0430\u043c\u0435\u0442\u0440\u043e\u0432 (E2B, E4B, 31B \u0438 26B A4B). \u0412\u0430\u0440\u0438\u0430\u043d\u0442\u044b E2B \u0438 E4B \u043f\u043e\u0434\u0445\u043e\u0434\u044f\u0442 \u0434\u043b\u044f \u0438\u0441\u043f\u043e\u043b\u044c\u0437\u043e\u0432\u0430\u043d\u0438\u044f \u043d\u0430 \u043c\u043e\u0431\u0438\u043b\u044c\u043d\u044b\u0445 \u0443\u0441\u0442\u0440\u043e\u0439\u0441\u0442\u0432\u0430\u0445, \u0441\u0438\u0441\u0442\u0435\u043c\u0430\u0445 \u0438\u043d\u0442\u0435\u0440\u043d\u0435\u0442\u0430 \u0432\u0435\u0449\u0435\u0439 (IoT) \u0438 \u043f\u043b\u0430\u0442\u0430\u0445 \u0442\u0438\u043f\u0430 […]<\/p>\n","protected":false,"gt_translate_keys":[{"key":"rendered","format":"html"}]},"author":8,"featured_media":167259,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[702],"tags":[],"class_list":["post-167258","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news"],"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\n","aioseo_head_json":{"title":"\ud83e\udd47Google har sl\u00e4ppt den \u00f6ppna AI-modellen Gemma 4, byggd p\u00e5 Gemini 3-teknologier | ProHoster","description":"Google har publicerat en ny familj av stora spr\u00e5kliga modeller Gemma 4, baserade p\u00e5 Gemini 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