{"id":1798,"date":"2026-09-02T17:53:10","date_gmt":"2026-09-02T15:53:10","guid":{"rendered":"https:\/\/infoimasd.com\/?p=1798"},"modified":"2026-09-02T17:53:46","modified_gmt":"2026-09-02T15:53:46","slug":"quasar-438b-multiverse-computing-modelo-ia-europeo","status":"publish","type":"post","link":"https:\/\/infoimasd.com\/index.php\/2026\/09\/02\/quasar-438b-multiverse-computing-modelo-ia-europeo\/","title":{"rendered":"Multiverse Computing presenta Quasar 438B, el modelo europeo de razonamiento m\u00e1s potente hasta la fecha"},"content":{"rendered":"\n

La compa\u00f1\u00eda Multiverse Computing ha lanzado Quasar 438B<\/a>, su primer gran modelo de lenguaje y el primero orientado a razonamiento empresarial a gran escala<\/strong>. El sistema funciona en ingl\u00e9s y espa\u00f1ol, y alcanza una puntuaci\u00f3n de 43 en el Artificial Analysis Intelligence Index, la cifra m\u00e1s alta registrada por un modelo europeo en este \u00edndice. Se trata de un salto significativo para una empresa que hasta ahora se hab\u00eda especializado en t\u00e9cnicas de compresi\u00f3n y eficiencia de modelos, y que con Quasar da el paso hacia la clase de modelos de m\u00e1s de 400.000 millones de par\u00e1metros.<\/p>\n\n\n\n

Con sus 43 puntos, Quasar 438B se sit\u00faa por delante de Mistral Medium 3.5 (30 puntos), NVIDIA Nemotron 3 Ultra (38 puntos) e Inkling (42 puntos). El liderazgo global del ranking sigue en manos de Claude <\/a>Opus 5, con 63 puntos, lo que deja claro que la distancia con la frontera absoluta del sector todav\u00eda es amplia<\/strong>, aunque Quasar se consolida como la referencia europea del segmento.<\/p>\n\n\n\n

\"\"<\/figure>\n\n\n\n

Velocidad de respuesta a la altura de los modelos punteros<\/h3>\n\n\n\n

M\u00e1s all\u00e1 de la puntuaci\u00f3n, Quasar destaca por su rapidez. Genera una respuesta de 500 tokens, incluyendo el tiempo de razonamiento, en 15,3 segundos. <\/strong>Solo tres modelos de la comparativa son m\u00e1s veloces, y de ellos \u00fanicamente Gemini 3.7 Flash logra adem\u00e1s superarle en el \u00edndice de inteligencia. El resto de sistemas que punt\u00faan por encima de Quasar necesitan bastante m\u00e1s tiempo para responder: solo dos lo hacen en menos de 25 segundos, mientras que los dem\u00e1s tardan entre 38 y 156 segundos. Frente a Mistral Medium 3.5, la comparaci\u00f3n es doblemente favorable para Quasar, que punt\u00faa m\u00e1s alto (43 frente a 30) y responde m\u00e1s r\u00e1pido (15,3 frente a 18,8 segundos).<\/p>\n\n\n\n

Razonamiento sobre contextos largos<\/h3>\n\n\n\n

En la prueba AA-LCR, que mide la capacidad de extraer y conectar informaci\u00f3n repartida en documentos extensos, Quasar obtiene 75,0 puntos, un resultado pr\u00e1cticamente igualado con Grok 4.6 (high) y a menos de un punto de Claude Opus 5 (75,7) y de Qwen3.8 2.4T A95B (75,3).<\/strong> Esta es la evaluaci\u00f3n en la que el modelo europeo se acerca m\u00e1s al grupo de cabeza, superando a Nemotron 3 Ultra por 4 puntos y a Mistral Medium 3.5 por 9,7. Es precisamente en este tipo de tareas (an\u00e1lisis documental, investigaci\u00f3n corporativa y flujos de trabajo con agentes) donde Multiverse Computing <\/a>sit\u00faa el valor diferencial de su modelo.<\/p>\n\n\n\n

Terminal-Bench, el margen de mejora m\u00e1s evidente<\/h3>\n\n\n\n

En Terminal-Bench v2.1, la prueba que eval\u00faa a los agentes trabajando en entornos de terminal reales, Quasar logra 69,3 puntos, por delante de Mistral Medium 3.5 (18,7 puntos menos) y de Nemotron 3 Ultra (15,4 puntos menos), aunque todav\u00eda a distancia del grupo de cabeza, liderado por Claude Opus 5 con 89,1 puntos.<\/strong> Desde Multiverse Computing reconocen que este es el \u00e1rea con m\u00e1s margen de mejora y hacia donde se orientar\u00e1 el siguiente ciclo de desarrollo del modelo.<\/p>\n\n\n\n

Un modelo para agentes empresariales y desarrollo de software<\/h3>\n\n\n\n

Quasar 438B est\u00e1 dise\u00f1ado para organizaciones que despliegan agentes de desarrollo de software, copilotos t\u00e9cnicos, sistemas de investigaci\u00f3n y automatizaci\u00f3n de flujos de trabajo. Sus resultados en Terminal-Bench y en contexto largo respaldan el uso de agentes que necesitan mantener contexto, coordinar acciones y resolver tareas de varios pasos, mientras que su velocidad de respuesta permite integrarlo en productos interactivos sin la latencia habitual de esta clase de modelos. El soporte nativo de ingl\u00e9s y espa\u00f1ol lo convierte adem\u00e1s en una base pr\u00e1ctica para empresas europeas e internacionales que buscan capacidades de razonamiento sin limitar su despliegue a un solo idioma.<\/p>\n\n\n\n

El modelo ya est\u00e1 disponible a trav\u00e9s de la API de CompactifAI<\/strong>, lo que permite a los equipos t\u00e9cnicos probarlo sin necesidad de desplegar infraestructura propia, en l\u00ednea con la estrategia de Multiverse Computing de hacer m\u00e1s accesible y eficiente el acceso a modelos de gran escala.<\/p>\n\n\n\n

<\/p>\n","protected":false},"excerpt":{"rendered":"

Multiverse Computing presenta Quasar 438B, el modelo de razonamiento de IA m\u00e1s potente desarrollado en Europa hasta la fecha. Con 43 puntos en el Artificial Analysis Intelligence Index, supera a Mistral Medium 3.5 y destaca por su alta velocidad de respuesta y rendimiento en contextos largos para entornos empresariales.<\/p>\n","protected":false},"author":1,"featured_media":1799,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_feature_clip_id":0,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_post_was_ever_published":false},"categories":[12,93],"tags":[833,834,831,31,830,835,716,29,829,832,836],"class_list":["post-1798","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-innovacion-sectorial","category-mundo-empresarial","tag-artificial-analysis","tag-compactifai","tag-ia-europea","tag-inteligencia-artificial","tag-llm","tag-mistral-medium-3-5","tag-modelos-de-lenguaje","tag-multiverse-computing","tag-quasar-438b","tag-razonamiento-empresarial","tag-tecnologicas"],"yoast_head":"\nMultiverse Computing presenta Quasar 438B, el modelo europeo de razonamiento m\u00e1s potente hasta la fecha - INFO I+D<\/title>\n<meta name=\"description\" content=\"Multiverse Computing lanza Quasar 438B, el modelo de IA de razonamiento m\u00e1s potente de Europa. 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