{"id":3446,"date":"2026-07-16T14:19:00","date_gmt":"2026-07-16T12:19:00","guid":{"rendered":"https:\/\/www.coolmod.com\/blog\/?p=3446"},"modified":"2026-07-16T14:19:00","modified_gmt":"2026-07-16T12:19:00","slug":"mini-pcs-como-las-nuevas-workstations-de-ia","status":"publish","type":"post","link":"https:\/\/www.coolmod.com\/blog\/categorias\/destacadas\/mini-pcs-como-las-nuevas-workstations-de-ia\/","title":{"rendered":"Mini PCs como las nuevas Workstations de IA"},"content":{"rendered":"<p><span data-contrast=\"auto\">Hace\u00a05\u00a0a\u00f1os, un Mini PC era sin\u00f3nimo de ofim\u00e1tica.<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Hoy,\u00a0Imagina\u00a0tener\u00a0una\u00a0workstation\u00a0capaz de mover modelos de IA de hasta 200.000 millones de par\u00e1metros&#8230; y que cabe en la palma de la mano. Suena a contradicci\u00f3n, pero es exactamente lo que ha tra\u00eddo el DGX Spark de\u00a0Nvidia.<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Entender por qu\u00e9 este dispositivo est\u00e1 reescribiendo las reglas de las\u00a0<\/span><b><span data-contrast=\"auto\">Workstations para IA<\/span><\/b><span data-contrast=\"auto\"> es clave para cualquier profesional, desarrollador o empresa que se plantee d\u00f3nde y c\u00f3mo va a ejecutar sus cargas de trabajo de inteligencia artificial en 2026.<\/span><\/p>\n<h2 aria-level=\"2\"><span data-contrast=\"none\">\u00bfQu\u00e9 es el DGX Spark y el chip GB10?<\/span><span data-ccp-props=\"{&quot;134245418&quot;:true,&quot;134245529&quot;:true,&quot;335559738&quot;:160,&quot;335559739&quot;:80}\">\u00a0<\/span><\/h2>\n<p><iframe loading=\"lazy\" title=\"NVIDIA RTX Spark Reinvents Windows PCs for the Age of Personal AI\" width=\"640\" height=\"360\" src=\"https:\/\/www.youtube.com\/embed\/H4nJo-oqAro?feature=oembed\" frameborder=\"0\" allow=\"accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share\" referrerpolicy=\"strict-origin-when-cross-origin\" allowfullscreen><\/iframe><\/p>\n<p><span data-contrast=\"auto\">El DGX Spark es un ordenador de escritorio compacto pensado espec\u00edficamente para trabajar con inteligencia artificial en local: entrenar, ajustar y ejecutar modelos sin depender de la nube.\u00a0<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:240,&quot;335559739&quot;:240}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">En su interior monta el\u00a0<\/span><a href=\"https:\/\/www.youtube.com\/watch?v=UaGFUtqravQ\" target=\"_blank\" rel=\"noopener\"><b><span data-contrast=\"auto\">NVIDIA GB10 Grace Blackwell<\/span><\/b><\/a><span data-contrast=\"auto\">, un chip que une en un mismo paquete una\u00a0<\/span><span data-contrast=\"auto\">CPU Arm de 20 n\u00facleos<\/span><span data-contrast=\"auto\">\u00a0(fabricada con tecnolog\u00eda de\u00a0MediaTek) y una\u00a0<\/span><span data-contrast=\"auto\">GPU de arquitectura Blackwell<\/span><span data-contrast=\"auto\">, la misma familia que usa\u00a0Nvidia\u00a0en sus centros de datos m\u00e1s potentes.\u00a0<\/span><b><span data-contrast=\"auto\">Ambas partes se comunican mediante NVLink-C2C<\/span><\/b><span data-contrast=\"auto\">, una interconexi\u00f3n de alta velocidad dise\u00f1ada por\u00a0Nvidia.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:240,&quot;335559739&quot;:240}\">\u00a0<\/span><\/p>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone\" src=\"https:\/\/www.nvidia.com\/content\/nvidiaGDC\/es\/es_ES\/data-center\/nvlink-fusion\/_jcr_content\/root\/responsivegrid\/nv_container_1162613538\/nv_container\/nv_container\/nv_image.coreimg.100.1070.jpeg\/1780245049812\/nvlink-fusion.jpeg\" alt=\"\" width=\"1070\" height=\"601\" \/><\/p>\n<p><span data-contrast=\"auto\">La clave para entender por qu\u00e9 esto es diferente a un PC normal est\u00e1 en la\u00a0<\/span><b><span data-contrast=\"auto\">memoria unificada.<\/span><\/b><span data-contrast=\"auto\">\u00a0E<\/span><span data-contrast=\"auto\">l DGX Spark cuenta con 128 GB de memoria compartida entre CPU y GPU.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:240,&quot;335559739&quot;:240}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">En un PC convencional, la GPU tiene su propia memoria (VRAM), limitada y separada de la RAM del sistema. Aqu\u00ed ambas comparten el mismo pool, lo que permite\u00a0<\/span><b><span data-contrast=\"auto\">cargar modelos de IA mucho m\u00e1s grandes sin quedarte sin espacio.<\/span><\/b><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:240,&quot;335559739&quot;:240}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">En cifras:<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:240,&quot;335559739&quot;:240}\">\u00a0<\/span><\/p>\n<ul>\n<li><b><span data-contrast=\"auto\">128 GB de memoria unificada LPDDR5x<\/span><\/b><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:0}\">\u00a0<\/span><\/li>\n<li><span data-contrast=\"auto\">Hasta\u00a0<\/span><b><span data-contrast=\"auto\">1\u00a0petaFLOP\u00a0de rendimiento de IA<\/span><\/b><span data-contrast=\"auto\">\u00a0(precisi\u00f3n FP4)<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:0}\">\u00a0<\/span><\/li>\n<li><strong>31 TFLOPS en FP32\u00a0<\/strong><\/li>\n<li><span data-contrast=\"auto\"><strong>CPU de 20 n\u00facleos Arm<\/strong> (10 de rendimiento + 10 de eficiencia)<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:0}\">\u00a0<\/span><\/li>\n<li><span data-contrast=\"auto\">Conectividad ConnectX-7 a 200 Gb\/s\u00a0(permite enlazar\u00a0hasta 3 unidades)<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:0}\">\u00a0<\/span><\/li>\n<li><span data-contrast=\"auto\">Un chasis de apenas\u00a0<\/span><b><span data-contrast=\"auto\">150 x 150 x 50,5\u00a0mm y<\/span><\/b><span data-contrast=\"auto\">\u00a0un consumo en torno a los 170 W.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:0}\">\u00a0<\/span><\/li>\n<li><span data-contrast=\"auto\">Capacidad para ejecutar modelos de\u00a0<\/span><b><span data-contrast=\"auto\">inferencia de hasta 200.000 millones de par\u00e1metros<\/span><\/b><span data-contrast=\"auto\">\u00a0y hacer\u00a0<\/span><i><span data-contrast=\"auto\">fine-tuning<\/span><\/i><span data-contrast=\"auto\">\u00a0de modelos de hasta 70.000 millones.<\/span><\/li>\n<\/ul>\n<p><span data-contrast=\"auto\">Todo eso corriendo sobre DGX OS, una versi\u00f3n de Ubuntu 24.04 LTS optimizada por NVIDIA, con el\u00a0stack\u00a0completo de software de IA preinstalado.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:240,&quot;335559739&quot;:240}\">\u00a0<\/span><\/p>\n<h3 aria-level=\"3\"><span data-contrast=\"none\">DGX Spark vs.\u00a0workstation\u00a0tradicional. Comparativa<\/span><span data-ccp-props=\"{&quot;134245418&quot;:true,&quot;134245529&quot;:true,&quot;335559738&quot;:160,&quot;335559739&quot;:80}\">\u00a0<\/span><\/h3>\n<p><span data-contrast=\"auto\">\u00bfSustituye esto a una\u00a0workstation\u00a0con GPU dedicada? No exactamente, pero tiene ciertas ventajas que una\u00a0estaci\u00f3n\u00a0de trabajo no puede ofrecerte.<\/span><\/p>\n<table style=\"font-weight: 400;\" data-tablestyle=\"MsoNormalTable\" data-tablelook=\"1696\" aria-rowcount=\"6\">\n<tbody>\n<tr aria-rowindex=\"1\">\n<td data-celllook=\"69905\"><span data-ccp-props=\"{&quot;335551550&quot;:1}\">\u00a0<\/span><\/td>\n<td data-celllook=\"69905\"><b><span data-contrast=\"auto\">DGX Spark (GB10)<\/span><\/b><span data-ccp-props=\"{&quot;335551550&quot;:1}\">\u00a0<\/span><\/td>\n<td data-celllook=\"69905\"><b><span data-contrast=\"auto\">Workstation con GPU dedicada<\/span><\/b><span data-ccp-props=\"{&quot;335551550&quot;:1}\">\u00a0<\/span><\/td>\n<\/tr>\n<tr aria-rowindex=\"2\">\n<td data-celllook=\"69905\"><strong>Memoria disponible para IA\u00a0<\/strong><\/td>\n<td data-celllook=\"69905\"><span data-contrast=\"auto\">128 GB unificados (CPU+GPU)<\/span><span data-ccp-props=\"{&quot;335551550&quot;:1}\">\u00a0<\/span><\/td>\n<td data-celllook=\"69905\"><span data-contrast=\"auto\">Limitada a la VRAM de la GPU (normalmente 16-32 GB en gama alta de consumo)<\/span><span data-ccp-props=\"{&quot;335551550&quot;:1}\">\u00a0<\/span><\/td>\n<\/tr>\n<tr aria-rowindex=\"3\">\n<td data-celllook=\"69905\"><strong>Tama\u00f1o de modelos que soporta<\/strong><span data-ccp-props=\"{&quot;335551550&quot;:1}\">\u00a0<\/span><\/td>\n<td data-celllook=\"69905\"><span data-contrast=\"auto\">Hasta 200B par\u00e1metros<\/span><span data-ccp-props=\"{&quot;335551550&quot;:1}\">\u00a0<\/span><\/td>\n<td data-celllook=\"69905\"><span data-contrast=\"auto\">Depende de la VRAM.\u00a0Modelos grandes requieren varias\u00a0GPUs<\/span><span data-ccp-props=\"{&quot;335551550&quot;:1}\">\u00a0<\/span><\/td>\n<\/tr>\n<tr aria-rowindex=\"4\">\n<td data-celllook=\"69905\"><strong>Ancho de banda de memoria<\/strong><span data-ccp-props=\"{&quot;335551550&quot;:1}\">\u00a0<\/span><\/td>\n<td data-celllook=\"69905\"><span data-contrast=\"auto\">Menor que una GPU dedicada<\/span><span data-ccp-props=\"{&quot;335551550&quot;:1}\">\u00a0<\/span><\/td>\n<td data-celllook=\"69905\"><span data-contrast=\"auto\">Mayor, ideal para m\u00e1ximo rendimiento en entrenamiento<\/span><span data-ccp-props=\"{&quot;335551550&quot;:1}\">\u00a0<\/span><\/td>\n<\/tr>\n<tr aria-rowindex=\"5\">\n<td data-celllook=\"69905\"><strong>Tama\u00f1o f\u00edsico\u00a0<\/strong><\/td>\n<td data-celllook=\"69905\"><span data-contrast=\"auto\">150 x 150 x 50,5 mm<\/span><span data-ccp-props=\"{&quot;335551550&quot;:1}\">\u00a0<\/span><\/td>\n<td data-celllook=\"69905\"><span data-contrast=\"auto\">Torre completa<\/span><span data-ccp-props=\"{&quot;335551550&quot;:1}\">\u00a0<\/span><\/td>\n<\/tr>\n<tr aria-rowindex=\"6\">\n<td data-celllook=\"69905\"><strong>Consumo y ruido\u00a0<\/strong><\/td>\n<td data-celllook=\"69905\"><span data-contrast=\"auto\">Bajo, viable 24\/7 en oficina<\/span><span data-ccp-props=\"{&quot;335551550&quot;:1}\">\u00a0<\/span><\/td>\n<td data-celllook=\"69905\"><span data-contrast=\"auto\">Alto, requiere refrigeraci\u00f3n robusta<\/span><span data-ccp-props=\"{&quot;335551550&quot;:1}\">\u00a0<\/span><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p><img decoding=\"async\" src=\"https:\/\/d1q3zw97enxzq2.cloudfront.net\/images\/nvidia-project-digits-exploded-ve.width-702.format-webp.webp\" alt=\"nvidia-project-digits-exploded-vew-ari-22\" \/><\/p>\n<p><span data-contrast=\"auto\"><strong>El punto d\u00e9bil real del DGX Spark es el ancho de banda de memoria.<\/strong> Al usar LPDDR5x en lugar de la VRAM dedicada de una GPU discreta, no compite en velocidad pura con una tarjeta gr\u00e1fica de gama alta.<\/span><\/p>\n<p><span data-contrast=\"auto\">Pero ese no es su objetivo. <strong>Su propuesta<\/strong> es otra, <strong>tener capacidad de memoria masiva para\u00a0<\/strong><\/span><strong><i>trabajar<\/i><\/strong><span data-contrast=\"auto\"><strong>\u00a0con modelos grandes en tu propio escritorio<\/strong>, algo que hasta ahora exig\u00eda infraestructura de servidor.<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Para el d\u00eda a d\u00eda de un desarrollador de IA (prototipar, afinar modelos, validar antes de escalar a la nube) el equilibrio entre potencia y tama\u00f1o cambia por completo el planteamiento de qu\u00e9 se necesita un puesto de trabajo.<\/span><\/p>\n<h2 aria-level=\"2\"><span data-contrast=\"none\">Qu\u00e9 significa que esto quepa en un Mini PC<\/span><span data-ccp-props=\"{&quot;134245418&quot;:true,&quot;134245529&quot;:true,&quot;335559738&quot;:160,&quot;335559739&quot;:80}\">\u00a0<\/span><\/h2>\n<p><span data-contrast=\"auto\">Hasta hace poco, tener 128 GB de memoria accesibles por una GPU implicaba un servidor de rack, refrigeraci\u00f3n industrial y en grandes empresas, hasta una sala dedicada. Ahora solo se enchufa a una toma de corriente y listo.<\/span><span data-ccp-props=\"{}\">\u00a0<\/span><\/p>\n<ul>\n<li><b><span data-contrast=\"auto\">De servidor de rack a escritorio.<\/span><\/b><span data-contrast=\"auto\">\u00a0La misma clase de arquitectura que antes solo exist\u00eda en centros de datos ahora cabe en un volumen menor en tu escritorio.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:240,&quot;335559739&quot;:240}\">\u00a0<\/span><\/li>\n<li><b><span data-contrast=\"auto\">Portabilidad real.<\/span><\/b><span data-contrast=\"auto\">\u00a0Nvidia\u00a0lo plantea directamente como un centro de datos port\u00e1til que cabe en una mochila.\u00a0Pensado para desarrolladores que necesitan prototipar y probar modelos all\u00e1 donde est\u00e9n, sin depender de una conexi\u00f3n a un servidor remoto.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:240,&quot;335559739&quot;:240}\">\u00a0<\/span><\/li>\n<li><b><span data-contrast=\"auto\">Gesti\u00f3n\u00a0headless.<\/span><\/b><span data-contrast=\"auto\">\u00a0No hace falta tenerlo conectado a monitor, teclado y rat\u00f3n.\u00a0se puede administrar en remoto por red, lo que encaja perfectamente con equipos de desarrollo que trabajan de forma distribuida.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:240,&quot;335559739&quot;:240}\">\u00a0<\/span><\/li>\n<li><b><span data-contrast=\"auto\">Edge\u00a0computing<\/span><\/b><span data-contrast=\"auto\">: la posibilidad de desplegar capacidad de IA directamente en el punto donde se genera el dato (una planta de producci\u00f3n, una consulta m\u00e9dica, un estudio de dise\u00f1o) sin depender de la latencia de una conexi\u00f3n a la nube.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:240,&quot;335559739&quot;:240}\">\u00a0<\/span><\/li>\n<li><b><span data-contrast=\"auto\">Escalado en cl\u00faster, sin montar un rack.<\/span><\/b><span data-contrast=\"auto\">\u00a0Cuando una sola unidad se queda corta, se pueden conectar dos DGX Spark entre s\u00ed mediante red de 200GbE, combinando hasta 256 GB de memoria total. Para un equipo peque\u00f1o, esto es la diferencia entre invertir en infraestructura de servidor o simplemente apilar dos Mini\u00a0PCs\u00a0sobre la mesa.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:240,&quot;335559739&quot;:240}\">\u00a0<\/span><\/li>\n<li><b><span data-contrast=\"auto\">Consumo y ruido controlados.<\/span><\/b><span data-contrast=\"auto\">\u00a0Al tratarse de un\u00a0SoC\u00a0de bajo consumo\u00a0es perfectamente viable tenerlo encendido de forma continua.<\/span><\/li>\n<\/ul>\n<p><img loading=\"lazy\" decoding=\"async\" class=\"alignnone\" src=\"https:\/\/miro.medium.com\/v2\/resize:fit:1400\/1*uAJS_-_8Phqrs3iSZgDu_g.jpeg\" alt=\"\" width=\"1400\" height=\"933\" \/><\/p>\n<h2 aria-level=\"2\"><span data-contrast=\"none\">Ventajas frente a la nube: IA local vs. tokens de pago<\/span><span data-ccp-props=\"{&quot;134245418&quot;:true,&quot;134245529&quot;:true,&quot;335559738&quot;:160,&quot;335559739&quot;:80}\">\u00a0<\/span><\/h2>\n<p><span data-contrast=\"auto\">M\u00e1s all\u00e1 del hardware,\u00a0estos equipos buscan\u00a0<strong>reducir la dependencia de la nube y del pago por token.<\/strong> Ejecutar modelos e incluso agentes de IA en local significa no depender de llamadas constantes a\u00a0APIs\u00a0externas, lo que se traduce en m\u00e1s control sobre los costes y sobre los datos que procesas.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:240,&quot;335559739&quot;:240}\">\u00a0<\/span><\/p>\n<p><span data-contrast=\"auto\">Si ya est\u00e1s valorando esta disyuntiva entre infraestructura local y suscripciones de IA, te interesa nuestro art\u00edculo sobre\u00a0<\/span><a href=\"https:\/\/www.coolmod.com\/blog\/categorias\/destacadas\/ia-local-vs-suscripciones-de-ia\/\" target=\"_blank\" rel=\"noopener\"><b><span data-contrast=\"none\">IA local vs. IA por suscripci\u00f3n<\/span><\/b><\/a><span data-contrast=\"auto\">\u00a0donde profundizamos en cu\u00e1ndo compensa cada opci\u00f3n.<\/span><\/p>\n<h2 aria-level=\"2\"><span data-contrast=\"none\">\u00bfPara qui\u00e9n es realmente el DGX Spark?<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;134245418&quot;:true,&quot;134245529&quot;:true,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:299,&quot;335559739&quot;:299}\">\u00a0<\/span><\/h2>\n<p><b><span data-contrast=\"auto\"><span style=\"color: #00ff00;\">S\u00ed<\/span> tiene sentido para:<\/span><\/b><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:240,&quot;335559739&quot;:240}\">\u00a0<\/span><\/p>\n<ul>\n<li><span data-contrast=\"auto\"><strong>Desarrolladores de IA<\/strong> que necesitan prototipar, ajustar (fine-tuning) y probar modelos grandes en local<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:0}\">\u00a0<\/span><\/li>\n<li><span data-contrast=\"auto\"><strong>Makers\u00a0y estudios<\/strong> peque\u00f1os que trabajan con modelos de IA de forma habitual<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:0}\">\u00a0<\/span><\/li>\n<li><span data-contrast=\"auto\"><strong>Peque\u00f1as empresas<\/strong> que quieren experimentar con IA propia sin depender de servicios en la nube<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:0}\">\u00a0<\/span><\/li>\n<\/ul>\n<p><b><span data-contrast=\"auto\"><span style=\"color: #ff0000;\">No<\/span> es la opci\u00f3n si:<\/span><\/b><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:240,&quot;335559739&quot;:240}\">\u00a0<\/span><\/p>\n<ul>\n<li><span data-contrast=\"auto\">Buscas un PC de uso dom\u00e9stico o para gaming<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:0}\">\u00a0<\/span><\/li>\n<li><span data-contrast=\"auto\">Tu carga de trabajo requiere el m\u00e1ximo rendimiento posible en entrenamiento masivo (ah\u00ed siguen ganando las\u00a0GPUs\u00a0dedicadas de gama alta)<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:0,&quot;335559739&quot;:0}\">\u00a0<\/span><\/li>\n<\/ul>\n<p><span data-teams=\"true\"><div\n            class=\"coolmod-widget-root\"\n            data-products=\"[{&quot;code&quot;:&quot;PROD-045450&quot;,&quot;name&quot;:&quot;Asus Ascent GX10-GG0003BN Nvidia GB10 Grace Blackwell 128GB 1TB DGX Spark IA&quot;,&quot;category&quot;:&quot;Mini PCs&quot;,&quot;image&quot;:&quot;https:\\\/\\\/www.coolmod.com\\\/images\\\/product\\\/large\\\/PROD-045450_1.jpg&quot;,&quot;price&quot;:6599.9499999999998,&quot;old_price&quot;:7299.9499999999998,&quot;discount&quot;:10,&quot;promo&quot;:true,&quot;url&quot;:&quot;https:\\\/\\\/www.coolmod.com\\\/asus-ascent-gx10-gg0003bn-ia-nvidia-gb10-grace-blackwell-128gb-1tb-wifi7\\\/&quot;,&quot;badge&quot;:&quot;Oferta&quot;},{&quot;code&quot;:&quot;PROD-045451&quot;,&quot;name&quot;:&quot;Asus Ascent GX10-GG0026BN Nvidia GB10 Grace Blackwell 128GB 2TB DGX Spark IA&quot;,&quot;category&quot;:&quot;Mini PCs&quot;,&quot;image&quot;:&quot;https:\\\/\\\/www.coolmod.com\\\/images\\\/product\\\/large\\\/PROD-045451_1.jpg&quot;,&quot;price&quot;:8791.9400000000005,&quot;old_price&quot;:null,&quot;discount&quot;:0,&quot;promo&quot;:false,&quot;url&quot;:&quot;https:\\\/\\\/www.coolmod.com\\\/asus-ascent-gx10-gg0026bn-ia-nvidia-gb10-grace-blackwell-128gb-2tb-wifi7\\\/&quot;,&quot;badge&quot;:&quot;&quot;},{&quot;code&quot;:&quot;PROD-046115&quot;,&quot;name&quot;:&quot;Gigabyte AI TOP ATOM Nvidia GB10 Grace Blackwell 128GB 4TB DGX Spark Gen5&quot;,&quot;category&quot;:&quot;Mini PCs&quot;,&quot;image&quot;:&quot;https:\\\/\\\/www.coolmod.com\\\/images\\\/product\\\/large\\\/PROD-046115_1.jpg&quot;,&quot;price&quot;:8516.9500000000007,&quot;old_price&quot;:null,&quot;discount&quot;:0,&quot;promo&quot;:false,&quot;url&quot;:&quot;https:\\\/\\\/www.coolmod.com\\\/gigabyte-ai-top-atom-atagb10-9000-arm-cortex-x295-cortex-a725-nvidia-blackwell-128gb-4tb-dgx-os\\\/&quot;,&quot;badge&quot;:&quot;&quot;},{&quot;code&quot;:&quot;PROD-047796&quot;,&quot;name&quot;:&quot;Asus Ascent GX10-GG0027BN Nvidia GB10 Grace Blackwell 128GB 4TB DGX Spark IA&quot;,&quot;category&quot;:&quot;Mini PCs&quot;,&quot;image&quot;:&quot;https:\\\/\\\/www.coolmod.com\\\/images\\\/product\\\/large\\\/PROD-047796_1.jpg&quot;,&quot;price&quot;:9315.9500000000007,&quot;old_price&quot;:null,&quot;discount&quot;:0,&quot;promo&quot;:false,&quot;url&quot;:&quot;https:\\\/\\\/www.coolmod.com\\\/asus-ascent-gx10-gg0027bn-nvidia-gb10-nvidia-blackwell-128gb-4tb-dgx-os\\\/&quot;,&quot;badge&quot;:&quot;&quot;}]\"\n            data-publish-date=\"2026-07\"\n            data-post-id=\"3446\"\n            data-post-slug=\"mini-pcs-como-las-nuevas-workstations-de-ia\">\n        <\/div><\/span><\/p>\n<p><strong><a href=\"https:\/\/www.coolmod.com\/pcs-sobremesa-mini-pcs\/procesador-gb10\/?ordenacion=precio-mayor#list-category-products\" target=\"_blank\" rel=\"noopener\">Ver todos los Mini PCs con\u00a0GTX Spark en COOLMOD \u2192<\/a><\/strong><\/p>\n<h2 aria-level=\"2\"><span data-contrast=\"none\">Preguntas frecuentes<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;134245418&quot;:true,&quot;134245529&quot;:true,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:299,&quot;335559739&quot;:299}\">\u00a0<\/span><\/h2>\n<p><b><span data-contrast=\"auto\">\u00bfPuedo hacer fine-tuning\u00a0en un DGX Spark?<\/span><\/b><span data-contrast=\"auto\">\u00a0S\u00ed. Con 128 GB de memoria unificada, el DGX Spark permite ajustar modelos de hasta 70.000 millones de par\u00e1metros para adaptarlos a casos de uso espec\u00edficos.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:240,&quot;335559739&quot;:240}\">\u00a0<\/span><\/p>\n<p><b><span data-contrast=\"auto\">\u00bfCu\u00e1nta memoria necesito para IA local?<\/span><\/b><span data-contrast=\"auto\">\u00a0Depende del tama\u00f1o del modelo, pero como referencia: 128 GB de memoria unificada permiten trabajar c\u00f3modamente con modelos de hasta 200.000 millones de par\u00e1metros en tareas de inferencia.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:240,&quot;335559739&quot;:240}\">\u00a0<\/span><\/p>\n<p><b><span data-contrast=\"auto\">\u00bfUn DGX Spark sustituye a una\u00a0workstation\u00a0con GPU dedicada?<\/span><\/b><span data-contrast=\"auto\">\u00a0No del todo. Gana en capacidad de memoria para modelos grandes, pero una GPU dedicada de gama alta sigue ofreciendo m\u00e1s ancho de banda y rendimiento puro para entrenamiento intensivo.<\/span><span data-ccp-props=\"{&quot;134233117&quot;:false,&quot;134233118&quot;:false,&quot;335551550&quot;:0,&quot;335551620&quot;:0,&quot;335559738&quot;:240,&quot;335559739&quot;:240}\">\u00a0<\/span><\/p>\n<p><b><span data-contrast=\"auto\">\u00bfSe pueden conectar varios DGX Spark entre s\u00ed?<\/span><\/b><span data-contrast=\"auto\">\u00a0S\u00ed.\u00a0G<\/span><span data-contrast=\"auto\">racias a NVIDIA ConnectX-7, hoy se pueden enlazar\u00a0<\/span><b><span data-contrast=\"auto\">hasta 3 unidades\u00a0<\/span><\/b><span data-contrast=\"auto\">para escalar la capacidad de c\u00f3mputo y 4 con un switch externo.<\/span><\/p>\n<hr \/>\n<p>Si a\u00fan tienes dudas sobre qu\u00e9 configuraci\u00f3n de Mini PC con DGX Spark se ajusta mejor a tu proyecto de IA, o quieres asesoramiento sobre c\u00f3mo integrarlo en tu infraestructura actual, escr\u00edbenos a <a href=\"mailto:comercial@coolmod.com\">comercial@coolmod.com<\/a>. En COOLMOD te ayudamos a elegir el equipo adecuado seg\u00fan tu caso de uso.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Hace\u00a05\u00a0a\u00f1os, un Mini PC era sin\u00f3nimo de ofim\u00e1tica.\u00a0 Hoy,\u00a0Imagina\u00a0tener\u00a0una\u00a0workstation\u00a0capaz de mover modelos de IA de hasta 200.000 millones de par\u00e1metros&#8230; y que cabe en la<\/p>\n","protected":false},"author":10,"featured_media":3462,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[31,168],"tags":[],"class_list":["post-3446","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-destacadas","category-workstations"],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v20.12 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Mini PCs como las nuevas Workstations de IA - Blog COOLMOD<\/title>\n<meta name=\"description\" content=\"Descubre c\u00f3mo el DGX Spark convierte un Mini PC en una workstation de IA real. 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