{"code":"var Component=(()=>{var p=Object.create;var s=Object.defineProperty;var k=Object.getOwnPropertyDescriptor;var m=Object.getOwnPropertyNames;var g=Object.getPrototypeOf,u=Object.prototype.hasOwnProperty;var E=(n,e)=>()=>(e||n((e={exports:{}}).exports,e),e.exports),b=(n,e)=>{for(var l in e)s(n,l,{get:e[l],enumerable:!0})},d=(n,e,l,r)=>{if(e&&typeof e==\"object\"||typeof e==\"function\")for(let a of m(e))!u.call(n,a)&&a!==l&&s(n,a,{get:()=>e[a],enumerable:!(r=k(e,a))||r.enumerable});return n};var y=(n,e,l)=>(l=n!=null?p(g(n)):{},d(e||!n||!n.__esModule?s(l,\"default\",{value:n,enumerable:!0}):l,n)),C=n=>d(s({},\"__esModule\",{value:!0}),n);var h=E((v,c)=>{c.exports=_jsx_runtime});var F={};b(F,{default:()=>o});var i=y(h());function t(n){let e={a:\"a\",code:\"code\",h2:\"h2\",h3:\"h3\",h4:\"h4\",hr:\"hr\",img:\"img\",li:\"li\",ol:\"ol\",p:\"p\",pre:\"pre\",span:\"span\",strong:\"strong\",table:\"table\",tbody:\"tbody\",td:\"td\",th:\"th\",thead:\"thead\",tr:\"tr\",ul:\"ul\",...n.components};return(0,i.jsxs)(i.Fragment,{children:[(0,i.jsx)(e.p,{children:\"macOS Tahoe 26.2 introduce una caracter\\xEDstica revolucionaria que transforma m\\xFAltiples Mac en una supercomputadora de IA unificada utilizando cl\\xFAsteres Thunderbolt 5. Esta gu\\xEDa completa cubre todo, desde los requisitos de hardware hasta la ejecuci\\xF3n de modelos de billones de par\\xE1metros como Kimi K2 Thinking en su propio cl\\xFAster de Mac.\"}),`\n`,(0,i.jsx)(e.p,{children:(0,i.jsx)(e.img,{alt:\"macOS Tahoe Thunderbolt 5 Clustering Guide\",src:\"/images/blog/shared/mac-studio-back-view.webp\",width:\"758\",height:\"372\"})}),`\n`,(0,i.jsx)(e.h2,{id:\"puntos-clave\",children:\"Puntos clave\"}),`\n`,(0,i.jsxs)(e.ul,{children:[`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"El cl\\xFAster Thunderbolt 5\"}),\" en macOS Tahoe 26.2 permite conectar m\\xFAltiples Mac a una velocidad bidireccional de hasta 80 Gbps\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"Cuatro Mac Studio con 512 GB cada uno\"}),\" pueden ejecutar el modelo Kimi K2 Thinking de 1 bill\\xF3n de par\\xE1metros utilizando menos de 500 W de potencia total\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"Los dispositivos compatibles\"}),\" incluyen el Mac mini M4 Pro, MacBook Pro M4 Pro/Max y Mac Studio M3 Ultra\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"El marco MLX\"}),\" y el software \",(0,i.jsx)(e.strong,{children:\"EXO 1.0\"}),\" proporcionan la infraestructura de computaci\\xF3n distribuida\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"No se requiere hardware especial\"}),\" - solo cables est\\xE1ndar Thunderbolt 5 de menos de 2 metros\"]}),`\n`]}),`\n`,(0,i.jsx)(e.hr,{}),`\n`,(0,i.jsx)(e.h2,{id:\"resumen-ejecutivo-entendiendo-la-tecnolog\\xEDa-de-cl\\xFAsteres-mac\",children:\"Resumen ejecutivo: Entendiendo la tecnolog\\xEDa de cl\\xFAsteres Mac\"}),`\n`,(0,i.jsx)(e.h3,{id:\"por-qu\\xE9-es-importante-el-cl\\xFAster-thunderbolt-5\",children:\"Por qu\\xE9 es importante el cl\\xFAster Thunderbolt 5\"}),`\n`,(0,i.jsx)(e.p,{children:\"El lanzamiento de macOS Tahoe 26.2 marca un momento crucial en la estrategia de computaci\\xF3n profesional de Apple. Por primera vez, Apple proporciona soporte nativo y optimizado para conectar m\\xFAltiples Mac en un cl\\xFAster de computaci\\xF3n unificado utilizando el ancho de banda sin precedentes de Thunderbolt 5. Esto no es solo una mejora incremental: cambia fundamentalmente lo que es posible con el hardware Mac.\"}),`\n`,(0,i.jsx)(e.p,{children:(0,i.jsx)(e.strong,{children:\"El problema que resuelve:\"})}),`\n`,(0,i.jsx)(e.p,{children:\"La ejecuci\\xF3n de grandes modelos de IA ha requerido tradicionalmente costosos cl\\xFAsteres de GPU con un consumo masivo de energ\\xEDa. Una configuraci\\xF3n t\\xEDpica para modelos de billones de par\\xE1metros podr\\xEDa incluir:\"}),`\n`,(0,i.jsxs)(e.ul,{children:[`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"Cl\\xFAster NVIDIA H100\"}),\": Hardware de m\\xE1s de $400,000, consumo de energ\\xEDa de m\\xE1s de 10kW\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"Instancias de GPU en la nube\"}),\": $2-5 por hora para instancias capaces\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"Infraestructura de centro de datos personalizada\"}),\": Refrigeraci\\xF3n, distribuci\\xF3n de energ\\xEDa, redes\"]}),`\n`]}),`\n`,(0,i.jsx)(e.p,{children:(0,i.jsx)(e.strong,{children:\"La soluci\\xF3n del cl\\xFAster Mac:\"})}),`\n`,(0,i.jsx)(e.p,{children:\"Con el cl\\xFAster Thunderbolt 5, puede lograr capacidades comparables con:\"}),`\n`,(0,i.jsxs)(e.ul,{children:[`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"4x Mac Studio\"}),\": Hardware de $47,000 (88% de reducci\\xF3n de costos vs H100)\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"Consumo de energ\\xEDa\"}),\": Menos de 500 W (95% de reducci\\xF3n)\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"Sin infraestructura\"}),\": Entorno de oficina est\\xE1ndar\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"Procesamiento local\"}),\": Privacidad de datos completa\"]}),`\n`]}),`\n`,(0,i.jsx)(e.h3,{id:\"qui\\xE9n-se-beneficia-del-cl\\xFAster-mac\",children:\"\\xBFQui\\xE9n se beneficia del cl\\xFAster Mac?\"}),`\n`,(0,i.jsx)(e.p,{children:(0,i.jsx)(e.strong,{children:\"Investigadores de IA e ingenieros de ML:\"})}),`\n`,(0,i.jsxs)(e.ul,{children:[`\n`,(0,i.jsx)(e.li,{children:\"Ejecute modelos de frontera localmente sin dependencias de la nube\"}),`\n`,(0,i.jsx)(e.li,{children:\"Itere m\\xE1s r\\xE1pido con hardware dedicado\"}),`\n`,(0,i.jsx)(e.li,{children:\"Mantenga un control total sobre los datos de entrenamiento\"}),`\n`]}),`\n`,(0,i.jsx)(e.p,{children:(0,i.jsx)(e.strong,{children:\"Profesionales creativos:\"})}),`\n`,(0,i.jsxs)(e.ul,{children:[`\n`,(0,i.jsx)(e.li,{children:\"Renderizado de video distribuido a trav\\xE9s de m\\xFAltiples Mac\"}),`\n`,(0,i.jsx)(e.li,{children:\"Edici\\xF3n asistida por IA con modelos locales\"}),`\n`,(0,i.jsx)(e.li,{children:\"Procesamiento de archivos grandes sin latencia de red\"}),`\n`]}),`\n`,(0,i.jsx)(e.p,{children:(0,i.jsx)(e.strong,{children:\"Equipos de TI empresariales:\"})}),`\n`,(0,i.jsxs)(e.ul,{children:[`\n`,(0,i.jsx)(e.li,{children:\"Implementaciones de IA privadas\"}),`\n`,(0,i.jsx)(e.li,{children:\"Infraestructura de costo predecible\"}),`\n`,(0,i.jsx)(e.li,{children:\"Mantenimiento simplificado en comparaci\\xF3n con los cl\\xFAsteres de GPU\"}),`\n`]}),`\n`,(0,i.jsx)(e.p,{children:(0,i.jsx)(e.strong,{children:\"Desarrolladores independientes:\"})}),`\n`,(0,i.jsxs)(e.ul,{children:[`\n`,(0,i.jsx)(e.li,{children:\"Construya aplicaciones de IA con inferencia local\"}),`\n`,(0,i.jsx)(e.li,{children:\"Pruebe contra modelos grandes durante el desarrollo\"}),`\n`,(0,i.jsx)(e.li,{children:\"Env\\xEDe productos sin costos continuos de API\"}),`\n`]}),`\n`,(0,i.jsx)(e.hr,{}),`\n`,(0,i.jsx)(e.h2,{id:\"qu\\xE9-es-el-cl\\xFAster-thunderbolt-5-mac\",children:\"\\xBFQu\\xE9 es el cl\\xFAster Thunderbolt 5 Mac?\"}),`\n`,(0,i.jsx)(e.h3,{id:\"la-evoluci\\xF3n-de-la-computaci\\xF3n-distribuida-en-mac\",children:\"La evoluci\\xF3n de la computaci\\xF3n distribuida en Mac\"}),`\n`,(0,i.jsx)(e.p,{children:\"El cl\\xFAster Thunderbolt 5 Mac representa el renacimiento moderno de Apple de la computaci\\xF3n distribuida en Mac. Los usuarios de Apple de larga data pueden recordar Xgrid, que convert\\xEDa colecciones de Mac en supercomputadoras. El nuevo cl\\xFAster Thunderbolt 5 en macOS Tahoe 26.2 sigue un concepto similar pero opera a velocidades dram\\xE1ticamente m\\xE1s altas.\"}),`\n`,(0,i.jsx)(e.p,{children:(0,i.jsx)(e.strong,{children:\"Contexto hist\\xF3rico:\"})}),`\n`,(0,i.jsxs)(e.ul,{children:[`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"Era Xgrid\"}),\": Limitada a velocidades de Ethernet (1-10 Gbps)\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"Cl\\xFAsteres Thunderbolt 4\"}),\": 40 Gbps, el uso de concentradores reduc\\xEDa las velocidades a 10 Gbps\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"Cl\\xFAsteres Thunderbolt 5\"}),\": 80 Gbps bidireccionales completos, modo r\\xE1faga de 120 Gbps\"]}),`\n`]}),`\n`,(0,i.jsx)(e.h3,{id:\"c\\xF3mo-funciona-el-cl\\xFAster-thunderbolt-5\",children:\"C\\xF3mo funciona el cl\\xFAster Thunderbolt 5\"}),`\n`,(0,i.jsxs)(e.p,{children:[\"La tecnolog\\xEDa de cl\\xFAster utiliza \",(0,i.jsx)(e.strong,{children:\"Acceso directo a memoria remota (RDMA)\"}),\", permitiendo que un Mac acceda directamente a la memoria de otro sin sobrecarga de CPU. Cuando conecta m\\xFAltiples Mac a trav\\xE9s de Thunderbolt 5:\"]}),`\n`,(0,i.jsxs)(e.ol,{children:[`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"Agrupaci\\xF3n de memoria\"}),\": La memoria unificada de cada Mac se vuelve accesible para todo el cl\\xFAster\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"Particionamiento del modelo\"}),\": Los grandes modelos de IA se dividen proporcionalmente entre las m\\xE1quinas\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"Procesamiento paralelo\"}),\": Las cargas de trabajo se distribuyen seg\\xFAn los recursos disponibles\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"Comunicaci\\xF3n de baja latencia\"}),\": El acceso directo a la memoria elimina los cuellos de botella de la red\"]}),`\n`]}),`\n`,(0,i.jsx)(e.p,{children:(0,i.jsx)(e.strong,{children:\"Ejemplo de configuraci\\xF3n de grupo de memoria:\"})}),`\n`,(0,i.jsxs)(e.table,{children:[(0,i.jsx)(e.thead,{children:(0,i.jsxs)(e.tr,{children:[(0,i.jsx)(e.th,{children:\"Configuraci\\xF3n\"}),(0,i.jsx)(e.th,{children:\"Memoria total\"}),(0,i.jsx)(e.th,{children:\"Caso de uso\"})]})}),(0,i.jsxs)(e.tbody,{children:[(0,i.jsxs)(e.tr,{children:[(0,i.jsx)(e.td,{children:\"2x Mac Studio (512 GB)\"}),(0,i.jsx)(e.td,{children:\"1 TB compartido\"}),(0,i.jsx)(e.td,{children:\"Kimi K2 Thinking (594 GB)\"})]}),(0,i.jsxs)(e.tr,{children:[(0,i.jsx)(e.td,{children:\"4x Mac Studio (512 GB)\"}),(0,i.jsx)(e.td,{children:\"2 TB compartido\"}),(0,i.jsx)(e.td,{children:\"M\\xFAltiples modelos de billones de par\\xE1metros\"})]}),(0,i.jsxs)(e.tr,{children:[(0,i.jsx)(e.td,{children:\"4x Mac mini M4 Pro (64 GB)\"}),(0,i.jsx)(e.td,{children:\"256 GB compartido\"}),(0,i.jsx)(e.td,{children:\"Modelos de 70B-200B par\\xE1metros\"})]})]})]}),`\n`,(0,i.jsx)(e.h3,{id:\"ventaja-de-la-memoria-unificada-de-apple-silicon\",children:\"Ventaja de la memoria unificada de Apple Silicon\"}),`\n`,(0,i.jsx)(e.p,{children:\"Una raz\\xF3n clave por la que el cl\\xFAster Mac es tan efectivo radica en la arquitectura de memoria unificada de Apple Silicon. A diferencia de las computadoras tradicionales donde la GPU y la CPU tienen grupos de memoria separados, Apple Silicon comparte la memoria entre todas las unidades de procesamiento.\"}),`\n`,(0,i.jsx)(e.p,{children:(0,i.jsx)(e.strong,{children:\"Beneficios de la memoria unificada para el cl\\xFAster:\"})}),`\n`,(0,i.jsxs)(e.table,{children:[(0,i.jsx)(e.thead,{children:(0,i.jsxs)(e.tr,{children:[(0,i.jsx)(e.th,{children:\"Aspecto\"}),(0,i.jsx)(e.th,{children:\"Arquitectura tradicional\"}),(0,i.jsx)(e.th,{children:\"Apple Silicon\"})]})}),(0,i.jsxs)(e.tbody,{children:[(0,i.jsxs)(e.tr,{children:[(0,i.jsx)(e.td,{children:\"Acceso a memoria\"}),(0,i.jsx)(e.td,{children:\"La GPU copia datos de la RAM\"}),(0,i.jsx)(e.td,{children:\"Acceso compartido directo\"})]}),(0,i.jsxs)(e.tr,{children:[(0,i.jsx)(e.td,{children:\"Ancho de banda\"}),(0,i.jsx)(e.td,{children:\"Limitado por PCIe (64 GB/s)\"}),(0,i.jsx)(e.td,{children:\"Hasta 800 GB/s (M3 Ultra)\"})]}),(0,i.jsxs)(e.tr,{children:[(0,i.jsx)(e.td,{children:\"Eficiencia\"}),(0,i.jsx)(e.td,{children:\"Se requiere duplicaci\\xF3n de datos\"}),(0,i.jsx)(e.td,{children:\"Operaciones de cero copia\"})]}),(0,i.jsxs)(e.tr,{children:[(0,i.jsx)(e.td,{children:\"Escalabilidad\"}),(0,i.jsx)(e.td,{children:\"VRAM limita el tama\\xF1o del modelo\"}),(0,i.jsx)(e.td,{children:\"El grupo unificado escala linealmente\"})]})]})]}),`\n`,(0,i.jsx)(e.p,{children:\"Cuando agrupa m\\xFAltiples Mac, est\\xE1 creando efectivamente un grupo de memoria unificada m\\xE1s grande. Un modelo que es demasiado grande para la memoria de un Mac se puede dividir entre nodos, con cada Mac manteniendo una porci\\xF3n y compartiendo el acceso a trav\\xE9s de Thunderbolt 5.\"}),`\n`,(0,i.jsx)(e.p,{children:(0,i.jsx)(e.strong,{children:\"Ejemplo pr\\xE1ctico:\"})}),`\n`,(0,i.jsxs)(e.ul,{children:[`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"Mac Studio \\xFAnico (512 GB)\"}),\": Puede ejecutar modelos de hasta ~450 GB (dejando margen)\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"2x Mac Studio (1 TB agrupado)\"}),\": Puede ejecutar modelos de hasta ~900 GB\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"4x Mac Studio (2 TB agrupado)\"}),\": Puede ejecutar modelos de hasta ~1.8 TB\"]}),`\n`]}),`\n`,(0,i.jsx)(e.p,{children:\"Esta escala lineal es lo que hace factibles los modelos de billones de par\\xE1metros como Kimi K2 Thinking en hardware Mac.\"}),`\n`,(0,i.jsx)(e.hr,{}),`\n`,(0,i.jsx)(e.h2,{id:\"requisitos-de-hardware-y-compatibilidad\",children:\"Requisitos de hardware y compatibilidad\"}),`\n`,(0,i.jsx)(e.h3,{id:\"modelos-de-mac-compatibles\",children:\"Modelos de Mac compatibles\"}),`\n`,(0,i.jsx)(e.p,{children:(0,i.jsx)(e.strong,{children:\"Soporte nativo Thunderbolt 5 (80 Gbps completos):\"})}),`\n`,(0,i.jsxs)(e.table,{children:[(0,i.jsx)(e.thead,{children:(0,i.jsxs)(e.tr,{children:[(0,i.jsx)(e.th,{children:\"Dispositivo\"}),(0,i.jsx)(e.th,{children:\"Puertos Thunderbolt 5\"}),(0,i.jsx)(e.th,{children:\"Memoria m\\xE1x.\"}),(0,i.jsx)(e.th,{children:\"Notas\"})]})}),(0,i.jsxs)(e.tbody,{children:[(0,i.jsxs)(e.tr,{children:[(0,i.jsx)(e.td,{children:\"Mac Studio (M3 Ultra)\"}),(0,i.jsx)(e.td,{children:\"6\"}),(0,i.jsx)(e.td,{children:\"512 GB\"}),(0,i.jsx)(e.td,{children:\"Mejor para cl\\xFAsteres grandes\"})]}),(0,i.jsxs)(e.tr,{children:[(0,i.jsx)(e.td,{children:\"Mac mini (M4 Pro)\"}),(0,i.jsx)(e.td,{children:\"3 frontales\"}),(0,i.jsx)(e.td,{children:\"64 GB\"}),(0,i.jsx)(e.td,{children:\"Nodos rentables\"})]}),(0,i.jsxs)(e.tr,{children:[(0,i.jsx)(e.td,{children:'MacBook Pro 14\" (M4 Pro)'}),(0,i.jsx)(e.td,{children:\"3\"}),(0,i.jsx)(e.td,{children:\"48 GB\"}),(0,i.jsx)(e.td,{children:\"Cl\\xFAster port\\xE1til\"})]}),(0,i.jsxs)(e.tr,{children:[(0,i.jsx)(e.td,{children:'MacBook Pro 16\" (M4 Max)'}),(0,i.jsx)(e.td,{children:\"3\"}),(0,i.jsx)(e.td,{children:\"128 GB\"}),(0,i.jsx)(e.td,{children:\"Port\\xE1til de alta memoria\"})]})]})]}),`\n`,(0,i.jsx)(e.p,{children:(0,i.jsx)(e.strong,{children:\"Especificaciones importantes:\"})}),`\n`,(0,i.jsxs)(e.ul,{children:[`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"Velocidad Thunderbolt 5\"}),\": 80 Gbps bidireccional (120 Gbps modo r\\xE1faga para video)\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"Ancho de banda de memoria\"}),\": M4 Pro ofrece 273 GB/s, M4 Max ofrece 546 GB/s\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"Longitud del cable\"}),\": Mantener por debajo de 2 metros para un rendimiento \\xF3ptimo\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"Tipo de cable\"}),\": Cables est\\xE1ndar Thunderbolt 5 (compatibles con USB4 v2)\"]}),`\n`]}),`\n`,(0,i.jsx)(e.h3,{id:\"configuraciones-de-cl\\xFAster-recomendadas\",children:\"Configuraciones de cl\\xFAster recomendadas\"}),`\n`,(0,i.jsx)(e.p,{children:(0,i.jsx)(e.strong,{children:\"Cl\\xFAster econ\\xF3mico (Experimentaci\\xF3n de aprendizaje autom\\xE1tico):\"})}),`\n`,(0,i.jsx)(i.Fragment,{children:(0,i.jsx)(e.pre,{className:\"shiki shiki-themes github-light github-dark\",style:{\"--shiki-light\":\"#24292e\",\"--shiki-dark\":\"#e1e4e8\",\"--shiki-light-bg\":\"#fff\",\"--shiki-dark-bg\":\"#24292e\"},tabIndex:\"0\",icon:'<svg viewBox=\"0 0 24 24\"><path d=\"M 6,1 C 4.354992,1 3,2.354992 3,4 v 16 c 0,1.645008 1.354992,3 3,3 h 12 c 1.645008,0 3,-1.354992 3,-3 V 8 7 A 1.0001,1.0001 0 0 0 20.707031,6.2929687 l -5,-5 A 1.0001,1.0001 0 0 0 15,1 h -1 z m 0,2 h 7 v 3 c 0,1.645008 1.354992,3 3,3 h 3 v 11 c 0,0.564129 -0.435871,1 -1,1 H 6 C 5.4358712,21 5,20.564129 5,20 V 4 C 5,3.4358712 5.4358712,3 6,3 Z M 15,3.4140625 18.585937,7 H 16 C 15.435871,7 15,6.5641288 15,6 Z\" fill=\"currentColor\" /></svg>',children:(0,i.jsxs)(e.code,{children:[(0,i.jsx)(e.span,{className:\"line\",children:(0,i.jsx)(e.span,{children:\"4x Mac mini M4 Pro (24 GB cada uno)\"})}),`\n`,(0,i.jsx)(e.span,{className:\"line\",children:(0,i.jsx)(e.span,{children:\"Memoria total: 96 GB compartidos\"})}),`\n`,(0,i.jsx)(e.span,{className:\"line\",children:(0,i.jsx)(e.span,{children:\"Costo: ~$7,200\"})}),`\n`,(0,i.jsx)(e.span,{className:\"line\",children:(0,i.jsx)(e.span,{children:\"Mejor para: Modelos de hasta 70B par\\xE1metros\"})}),`\n`,(0,i.jsx)(e.span,{className:\"line\",children:(0,i.jsx)(e.span,{children:\"Consumo de energ\\xEDa: ~60W inactivo, ~200W pico\"})}),`\n`,(0,i.jsx)(e.span,{className:\"line\",children:(0,i.jsx)(e.span,{children:\"Nivel de ruido: Casi silencioso\"})})]})})}),`\n`,(0,i.jsx)(e.p,{children:\"Esta configuraci\\xF3n es perfecta para desarrolladores que aprenden ML distribuido, peque\\xF1os equipos que experimentan con modelos de c\\xF3digo abierto o ejecutan modelos m\\xE1s peque\\xF1os como Llama 3.1 8B y Mistral 7B con un rendimiento excelente.\"}),`\n`,(0,i.jsx)(e.p,{children:(0,i.jsx)(e.strong,{children:\"Cl\\xFAster profesional (Cargas de trabajo de IA de producci\\xF3n):\"})}),`\n`,(0,i.jsx)(i.Fragment,{children:(0,i.jsx)(e.pre,{className:\"shiki shiki-themes github-light github-dark\",style:{\"--shiki-light\":\"#24292e\",\"--shiki-dark\":\"#e1e4e8\",\"--shiki-light-bg\":\"#fff\",\"--shiki-dark-bg\":\"#24292e\"},tabIndex:\"0\",icon:'<svg viewBox=\"0 0 24 24\"><path d=\"M 6,1 C 4.354992,1 3,2.354992 3,4 v 16 c 0,1.645008 1.354992,3 3,3 h 12 c 1.645008,0 3,-1.354992 3,-3 V 8 7 A 1.0001,1.0001 0 0 0 20.707031,6.2929687 l -5,-5 A 1.0001,1.0001 0 0 0 15,1 h -1 z m 0,2 h 7 v 3 c 0,1.645008 1.354992,3 3,3 h 3 v 11 c 0,0.564129 -0.435871,1 -1,1 H 6 C 5.4358712,21 5,20.564129 5,20 V 4 C 5,3.4358712 5.4358712,3 6,3 Z M 15,3.4140625 18.585937,7 H 16 C 15.435871,7 15,6.5641288 15,6 Z\" fill=\"currentColor\" /></svg>',children:(0,i.jsxs)(e.code,{children:[(0,i.jsx)(e.span,{className:\"line\",children:(0,i.jsx)(e.span,{children:\"4x Mac mini M4 Pro (64 GB cada uno)\"})}),`\n`,(0,i.jsx)(e.span,{className:\"line\",children:(0,i.jsx)(e.span,{children:\"Memoria total: 256 GB compartidos\"})}),`\n`,(0,i.jsx)(e.span,{className:\"line\",children:(0,i.jsx)(e.span,{children:\"Costo: ~$13,200\"})}),`\n`,(0,i.jsx)(e.span,{className:\"line\",children:(0,i.jsx)(e.span,{children:\"Mejor para: Modelos de hasta 200B par\\xE1metros\"})}),`\n`,(0,i.jsx)(e.span,{className:\"line\",children:(0,i.jsx)(e.span,{children:\"Consumo de energ\\xEDa: ~80W inactivo, ~300W pico\"})}),`\n`,(0,i.jsx)(e.span,{className:\"line\",children:(0,i.jsx)(e.span,{children:\"Nivel de ruido: Casi silencioso\"})})]})})}),`\n`,(0,i.jsx)(e.p,{children:\"El nivel profesional desbloquea modelos medianos-grandes como Llama 3.1 70B y puede ejecutar inferencia en modelos de grado empresarial. Este es el punto ideal para la mayor\\xEDa de las empresas que implementan IA local.\"}),`\n`,(0,i.jsx)(e.p,{children:(0,i.jsx)(e.strong,{children:\"Cl\\xFAster empresarial (Modelos de billones de par\\xE1metros):\"})}),`\n`,(0,i.jsx)(i.Fragment,{children:(0,i.jsx)(e.pre,{className:\"shiki shiki-themes github-light github-dark\",style:{\"--shiki-light\":\"#24292e\",\"--shiki-dark\":\"#e1e4e8\",\"--shiki-light-bg\":\"#fff\",\"--shiki-dark-bg\":\"#24292e\"},tabIndex:\"0\",icon:'<svg viewBox=\"0 0 24 24\"><path d=\"M 6,1 C 4.354992,1 3,2.354992 3,4 v 16 c 0,1.645008 1.354992,3 3,3 h 12 c 1.645008,0 3,-1.354992 3,-3 V 8 7 A 1.0001,1.0001 0 0 0 20.707031,6.2929687 l -5,-5 A 1.0001,1.0001 0 0 0 15,1 h -1 z m 0,2 h 7 v 3 c 0,1.645008 1.354992,3 3,3 h 3 v 11 c 0,0.564129 -0.435871,1 -1,1 H 6 C 5.4358712,21 5,20.564129 5,20 V 4 C 5,3.4358712 5.4358712,3 6,3 Z M 15,3.4140625 18.585937,7 H 16 C 15.435871,7 15,6.5641288 15,6 Z\" fill=\"currentColor\" /></svg>',children:(0,i.jsxs)(e.code,{children:[(0,i.jsx)(e.span,{className:\"line\",children:(0,i.jsx)(e.span,{children:\"4x Mac Studio M3 Ultra (512 GB cada uno)\"})}),`\n`,(0,i.jsx)(e.span,{className:\"line\",children:(0,i.jsx)(e.span,{children:\"Memoria total: 2 TB compartidos\"})}),`\n`,(0,i.jsx)(e.span,{className:\"line\",children:(0,i.jsx)(e.span,{children:\"Costo: ~$47,000 (\\u20AC47,000)\"})}),`\n`,(0,i.jsx)(e.span,{className:\"line\",children:(0,i.jsx)(e.span,{children:\"Mejor para: Kimi K2 Thinking, DeepSeek V3, modelos de frontera\"})}),`\n`,(0,i.jsx)(e.span,{className:\"line\",children:(0,i.jsx)(e.span,{children:\"Consumo de energ\\xEDa: ~100W inactivo, ~500W pico\"})}),`\n`,(0,i.jsx)(e.span,{className:\"line\",children:(0,i.jsx)(e.span,{children:\"Nivel de ruido: Moderado bajo carga\"})})]})})}),`\n`,(0,i.jsx)(e.p,{children:\"Esta configuraci\\xF3n de primer nivel iguala o supera a los cl\\xFAsteres de GPU de centros de datos para cargas de trabajo de inferencia mientras consume una fracci\\xF3n de la energ\\xEDa y no requiere infraestructura especializada.\"}),`\n`,(0,i.jsx)(e.h3,{id:\"gu\\xEDa-de-selecci\\xF3n-de-cables-thunderbolt-5\",children:\"Gu\\xEDa de selecci\\xF3n de cables Thunderbolt 5\"}),`\n`,(0,i.jsx)(e.p,{children:\"Elegir los cables correctos es cr\\xEDtico para el rendimiento del cl\\xFAster. No todos los cables admiten velocidades completas de Thunderbolt 5.\"}),`\n`,(0,i.jsx)(e.p,{children:(0,i.jsx)(e.strong,{children:\"Cables recomendados:\"})}),`\n`,(0,i.jsxs)(e.table,{children:[(0,i.jsx)(e.thead,{children:(0,i.jsxs)(e.tr,{children:[(0,i.jsx)(e.th,{children:\"Cable\"}),(0,i.jsx)(e.th,{children:\"Longitud\"}),(0,i.jsx)(e.th,{children:\"Velocidad m\\xE1x.\"}),(0,i.jsx)(e.th,{children:\"Rango de precios\"})]})}),(0,i.jsxs)(e.tbody,{children:[(0,i.jsxs)(e.tr,{children:[(0,i.jsx)(e.td,{children:\"Apple Thunderbolt 5 Pro\"}),(0,i.jsx)(e.td,{children:\"1m\"}),(0,i.jsx)(e.td,{children:\"120 Gbps\"}),(0,i.jsx)(e.td,{children:\"$69-79\"})]}),(0,i.jsxs)(e.tr,{children:[(0,i.jsx)(e.td,{children:\"OWC Thunderbolt 5\"}),(0,i.jsx)(e.td,{children:\"0.8m\"}),(0,i.jsx)(e.td,{children:\"80 Gbps\"}),(0,i.jsx)(e.td,{children:\"$50-60\"})]}),(0,i.jsxs)(e.tr,{children:[(0,i.jsx)(e.td,{children:\"CalDigit TB5 Cable\"}),(0,i.jsx)(e.td,{children:\"1m\"}),(0,i.jsx)(e.td,{children:\"80 Gbps\"}),(0,i.jsx)(e.td,{children:\"$45-55\"})]}),(0,i.jsxs)(e.tr,{children:[(0,i.jsx)(e.td,{children:\"Belkin Connect Pro\"}),(0,i.jsx)(e.td,{children:\"1m\"}),(0,i.jsx)(e.td,{children:\"80 Gbps\"}),(0,i.jsx)(e.td,{children:\"$40-50\"})]})]})]}),`\n`,(0,i.jsx)(e.p,{children:(0,i.jsx)(e.strong,{children:\"Consejos para la selecci\\xF3n de cables:\"})}),`\n`,(0,i.jsxs)(e.ol,{children:[`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"Mant\\xE9ngase por debajo de 1 metro\"}),\": Los 80 Gbps completos requieren cables cortos y de alta calidad\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"Busque la certificaci\\xF3n USB4 v2\"}),\": Garantiza la compatibilidad con Thunderbolt 5\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"Evite adaptadores\"}),\": Solo conexiones directas TB5 a TB5\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"Compre de marcas de renombre\"}),\": Los cables de imitaci\\xF3n pueden no alcanzar las velocidades nominales\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"Pruebe los cables antes de la implementaci\\xF3n\"}),\": Use \",(0,i.jsx)(e.code,{children:\"system_profiler SPThunderboltDataType\"}),\" para verificar la velocidad del enlace\"]}),`\n`]}),`\n`,(0,i.jsxs)(e.p,{children:[(0,i.jsx)(e.strong,{children:\"Advertencia\"}),': Muchos cables vendidos en l\\xEDnea como \"compatibles con Thunderbolt 5\" solo alcanzan velocidades de Thunderbolt 4. Verifique siempre las especificaciones antes de comprar.']}),`\n`,(0,i.jsx)(e.hr,{}),`\n`,(0,i.jsx)(e.h2,{id:\"pila-de-software-marcos-mlx-y-exo\",children:\"Pila de software: Marcos MLX y EXO\"}),`\n`,(0,i.jsx)(e.h3,{id:\"entendiendo-la-computaci\\xF3n-distribuida-mlx\",children:\"Entendiendo la computaci\\xF3n distribuida MLX\"}),`\n`,(0,i.jsx)(e.p,{children:\"MLX es el marco de matriz de c\\xF3digo abierto de Apple dise\\xF1ado espec\\xEDficamente para el aprendizaje autom\\xE1tico en Apple Silicon. Proporciona soporte nativo para la computaci\\xF3n distribuida a trav\\xE9s de m\\xFAltiples Mac.\"}),`\n`,(0,i.jsx)(e.p,{children:(0,i.jsx)(e.strong,{children:\"Caracter\\xEDsticas clave de MLX:\"})}),`\n`,(0,i.jsxs)(e.ul,{children:[`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"Acceso a memoria unificada\"}),\": Aprovecha la arquitectura de memoria unificada de Apple Silicon\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"Evaluaci\\xF3n perezosa\"}),\": Los c\\xE1lculos solo se ejecutan cuando se necesitan resultados\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"Compilaci\\xF3n din\\xE1mica\"}),\": Compilaci\\xF3n justo a tiempo para un rendimiento \\xF3ptimo\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"Primitivas distribuidas\"}),\": Soporte integrado para operaciones multi-m\\xE1quina\"]}),`\n`]}),`\n`,(0,i.jsx)(e.h3,{id:\"backends-de-comunicaci\\xF3n-mlx\",children:\"Backends de comunicaci\\xF3n MLX\"}),`\n`,(0,i.jsx)(e.p,{children:\"MLX admite tres backends de comunicaci\\xF3n para diferentes casos de uso:\"}),`\n`,(0,i.jsxs)(e.table,{children:[(0,i.jsx)(e.thead,{children:(0,i.jsxs)(e.tr,{children:[(0,i.jsx)(e.th,{children:\"Backend\"}),(0,i.jsx)(e.th,{children:\"Velocidad\"}),(0,i.jsx)(e.th,{children:\"Mejor para\"}),(0,i.jsx)(e.th,{children:\"Complejidad de configuraci\\xF3n\"})]})}),(0,i.jsxs)(e.tbody,{children:[(0,i.jsxs)(e.tr,{children:[(0,i.jsx)(e.td,{children:(0,i.jsx)(e.strong,{children:\"Ring\"})}),(0,i.jsx)(e.td,{children:\"M\\xE1s r\\xE1pido\"}),(0,i.jsx)(e.td,{children:\"Conexiones Thunderbolt\"}),(0,i.jsx)(e.td,{children:\"Media\"})]}),(0,i.jsxs)(e.tr,{children:[(0,i.jsx)(e.td,{children:(0,i.jsx)(e.strong,{children:\"MPI\"})}),(0,i.jsx)(e.td,{children:\"R\\xE1pido\"}),(0,i.jsx)(e.td,{children:\"Redes Ethernet\"}),(0,i.jsx)(e.td,{children:\"Mayor\"})]}),(0,i.jsxs)(e.tr,{children:[(0,i.jsx)(e.td,{children:(0,i.jsx)(e.strong,{children:\"NCCL\"})}),(0,i.jsx)(e.td,{children:\"N/A\"}),(0,i.jsx)(e.td,{children:\"Entornos CUDA\"}),(0,i.jsx)(e.td,{children:\"N/A en Mac\"})]})]})]}),`\n`,(0,i.jsxs)(e.p,{children:[(0,i.jsx)(e.strong,{children:\"Se recomienda el backend Ring para cl\\xFAsteres Thunderbolt 5\"}),\", ya que est\\xE1 optimizado para conexiones directas de igual a igual.\"]}),`\n`,(0,i.jsx)(e.h3,{id:\"entendiendo-el-entrenamiento-distribuido-vs-inferencia\",children:\"Entendiendo el entrenamiento distribuido vs inferencia\"}),`\n`,(0,i.jsx)(e.p,{children:\"Antes de sumergirse en la configuraci\\xF3n, es importante entender los dos casos de uso principales para el cl\\xFAster Mac:\"}),`\n`,(0,i.jsxs)(e.p,{children:[(0,i.jsx)(e.strong,{children:\"Inferencia distribuida (Ejecuci\\xF3n de modelos):\"}),`\nEste es el caso de uso principal para la mayor\\xEDa de los usuarios. Cuando ejecuta inferencia:`]}),`\n`,(0,i.jsxs)(e.ul,{children:[`\n`,(0,i.jsx)(e.li,{children:\"El modelo se divide en m\\xFAltiples Mac seg\\xFAn la memoria disponible\"}),`\n`,(0,i.jsx)(e.li,{children:\"Cada Mac contiene una porci\\xF3n de los pesos del modelo\"}),`\n`,(0,i.jsx)(e.li,{children:\"Durante la generaci\\xF3n, los datos fluyen entre los nodos seg\\xFAn sea necesario\"}),`\n`,(0,i.jsx)(e.li,{children:\"No ocurre entrenamiento: est\\xE1 utilizando un modelo pre-entrenado\"}),`\n`]}),`\n`,(0,i.jsxs)(e.p,{children:[(0,i.jsx)(e.strong,{children:\"Entrenamiento distribuido (Creaci\\xF3n de modelos):\"}),`\nPara investigadores y usuarios avanzados:`]}),`\n`,(0,i.jsxs)(e.ul,{children:[`\n`,(0,i.jsx)(e.li,{children:\"Los datos de entrenamiento se dividen entre nodos (paralelismo de datos)\"}),`\n`,(0,i.jsx)(e.li,{children:\"Los gradientes se promedian en todos los nodos despu\\xE9s de cada lote\"}),`\n`,(0,i.jsx)(e.li,{children:\"Los pesos del modelo se sincronizan peri\\xF3dicamente\"}),`\n`,(0,i.jsx)(e.li,{children:\"Requiere significativamente m\\xE1s comunicaci\\xF3n entre nodos\"}),`\n`]}),`\n`,(0,i.jsxs)(e.table,{children:[(0,i.jsx)(e.thead,{children:(0,i.jsxs)(e.tr,{children:[(0,i.jsx)(e.th,{children:\"Caso de uso\"}),(0,i.jsx)(e.th,{children:\"Requisito de ancho de banda\"}),(0,i.jsx)(e.th,{children:\"Complejidad\"}),(0,i.jsx)(e.th,{children:\"Usuarios t\\xEDpicos\"})]})}),(0,i.jsxs)(e.tbody,{children:[(0,i.jsxs)(e.tr,{children:[(0,i.jsx)(e.td,{children:\"Inferencia\"}),(0,i.jsx)(e.td,{children:\"Medio (carga del modelo)\"}),(0,i.jsx)(e.td,{children:\"Baja\"}),(0,i.jsx)(e.td,{children:\"La mayor\\xEDa de los usuarios\"})]}),(0,i.jsxs)(e.tr,{children:[(0,i.jsx)(e.td,{children:\"Ajuste fino\"}),(0,i.jsx)(e.td,{children:\"Alto (sincronizaci\\xF3n de gradientes)\"}),(0,i.jsx)(e.td,{children:\"Media\"}),(0,i.jsx)(e.td,{children:\"Ingenieros de ML\"})]}),(0,i.jsxs)(e.tr,{children:[(0,i.jsx)(e.td,{children:\"Entrenamiento completo\"}),(0,i.jsx)(e.td,{children:\"Muy alto (sincronizaci\\xF3n constante)\"}),(0,i.jsx)(e.td,{children:\"Alta\"}),(0,i.jsx)(e.td,{children:\"Investigadores\"})]})]})]}),`\n`,(0,i.jsx)(e.p,{children:\"Para la mayor\\xEDa de los usuarios de cl\\xFAsteres Mac, la inferencia es el objetivo principal: ejecutar modelos grandes que no cabr\\xEDan en una sola m\\xE1quina.\"}),`\n`,(0,i.jsx)(e.h3,{id:\"exo-gesti\\xF3n-de-cl\\xFAsteres-simplificada\",children:\"EXO: Gesti\\xF3n de cl\\xFAsteres simplificada\"}),`\n`,(0,i.jsx)(e.p,{children:\"EXO (de Exo Labs) proporciona una abstracci\\xF3n de nivel superior para construir cl\\xFAsteres de IA. Apple ha integrado el protocolo de EXO en macOS Tahoe 26.2.\"}),`\n`,(0,i.jsx)(e.p,{children:(0,i.jsx)(e.strong,{children:\"Caracter\\xEDsticas clave de EXO:\"})}),`\n`,(0,i.jsxs)(e.ul,{children:[`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"Autodescubrimiento\"}),\": Detecta autom\\xE1ticamente otros dispositivos en la red\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"Arquitectura de igual a igual\"}),\": Sin jerarqu\\xEDa maestro-trabajador\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"Particionamiento inteligente\"}),\": Divide \\xF3ptimamente los modelos seg\\xFAn las capacidades del dispositivo\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"API compatible con ChatGPT\"}),\": Punto final compatible con OpenAI en \",(0,i.jsx)(e.code,{children:\"localhost:52415\"})]}),`\n`]}),`\n`,(0,i.jsx)(e.hr,{}),`\n`,(0,i.jsx)(e.h2,{id:\"gu\\xEDa-paso-a-paso-de-configuraci\\xF3n-del-cl\\xFAster\",children:\"Gu\\xEDa paso a paso de configuraci\\xF3n del cl\\xFAster\"}),`\n`,(0,i.jsx)(e.h3,{id:\"requisitos-previos\",children:\"Requisitos previos\"}),`\n`,(0,i.jsx)(e.p,{children:\"Antes de comenzar, aseg\\xFArese de tener:\"}),`\n`,(0,i.jsxs)(e.ol,{children:[`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"macOS Tahoe 26.2\"}),\" o posterior instalado en todos los Mac\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"Cables Thunderbolt 5\"}),\" (menos de 2 metros)\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"Python 3.12+\"}),\" instalado\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"SSH sin contrase\\xF1a\"}),\" configurado entre m\\xE1quinas\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.strong,{children:\"Misma red\"}),\" para todas las m\\xE1quinas (para el descubrimiento inicial)\"]}),`\n`]}),`\n`,(0,i.jsx)(e.h3,{id:\"m\\xE9todo-1-configuraci\\xF3n-nativa-mlx-recomendado\",children:\"M\\xE9todo 1: Configuraci\\xF3n nativa MLX (Recomendado)\"}),`\n`,(0,i.jsx)(e.h4,{id:\"paso-1-instalar-mlx\",children:\"Paso 1: Instalar MLX\"}),`\n`,(0,i.jsx)(i.Fragment,{children:(0,i.jsx)(e.pre,{className:\"shiki shiki-themes github-light github-dark\",style:{\"--shiki-light\":\"#24292e\",\"--shiki-dark\":\"#e1e4e8\",\"--shiki-light-bg\":\"#fff\",\"--shiki-dark-bg\":\"#24292e\"},tabIndex:\"0\",icon:'<svg viewBox=\"0 0 24 24\"><path d=\"m 4,4 a 1,1 0 0 0 -0.7070312,0.2929687 1,1 0 0 0 0,1.4140625 L 8.5859375,11 3.2929688,16.292969 a 1,1 0 0 0 0,1.414062 1,1 0 0 0 1.4140624,0 l 5.9999998,-6 a 1.0001,1.0001 0 0 0 0,-1.414062 L 4.7070312,4.2929687 A 1,1 0 0 0 4,4 Z m 8,14 a 1,1 0 0 0 -1,1 1,1 0 0 0 1,1 h 8 a 1,1 0 0 0 1,-1 1,1 0 0 0 -1,-1 z\" fill=\"currentColor\" /></svg>',children:(0,i.jsxs)(e.code,{children:[(0,i.jsx)(e.span,{className:\"line\",children:(0,i.jsx)(e.span,{style:{\"--shiki-light\":\"#6A737D\",\"--shiki-dark\":\"#6A737D\"},children:\"# Instalar MLX a trav\\xE9s de 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Es un modelo de mezcla de expertos (MoE) de 1 bill\\xF3n de par\\xE1metros con 32 mil millones de par\\xE1metros activos. 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seguridad y privacidad de macOS Tahoe\"}),\".\"]}),`\n`,(0,i.jsx)(e.hr,{}),`\n`,(0,i.jsx)(e.h2,{id:\"puntos-de-referencia-de-rendimiento-del-mundo-real\",children:\"Puntos de referencia de rendimiento del mundo real\"}),`\n`,(0,i.jsx)(e.h3,{id:\"comparaci\\xF3n-de-velocidad-de-inferencia\",children:\"Comparaci\\xF3n de velocidad de inferencia\"}),`\n`,(0,i.jsx)(e.p,{children:\"Basado en pruebas comunitarias y demostraciones de Apple:\"}),`\n`,(0,i.jsxs)(e.table,{children:[(0,i.jsx)(e.thead,{children:(0,i.jsxs)(e.tr,{children:[(0,i.jsx)(e.th,{children:\"Modelo\"}),(0,i.jsx)(e.th,{children:\"Configuraci\\xF3n\"}),(0,i.jsx)(e.th,{children:\"Tokens/Segundo\"}),(0,i.jsx)(e.th,{children:\"Comparaci\\xF3n\"})]})}),(0,i.jsxs)(e.tbody,{children:[(0,i.jsxs)(e.tr,{children:[(0,i.jsx)(e.td,{children:\"Llama 3.1 70B\"}),(0,i.jsx)(e.td,{children:\"2x Mac mini M4 Pro (64 GB)\"}),(0,i.jsx)(e.td,{children:\"~35 tok/s\"}),(0,i.jsx)(e.td,{children:\"Comparable a RTX 4090\"})]}),(0,i.jsxs)(e.tr,{children:[(0,i.jsx)(e.td,{children:\"Llama 3.1 405B\"}),(0,i.jsx)(e.td,{children:\"4x Mac Studio (512 GB)\"}),(0,i.jsx)(e.td,{children:\"~15 tok/s\"}),(0,i.jsx)(e.td,{children:\"Supera a la nube A100\"})]}),(0,i.jsxs)(e.tr,{children:[(0,i.jsx)(e.td,{children:\"Kimi K2\"}),(0,i.jsx)(e.td,{children:\"2x Mac Studio (512 GB)\"}),(0,i.jsx)(e.td,{children:\"~20 tok/s\"}),(0,i.jsx)(e.td,{children:\"Primer bill\\xF3n de par\\xE1metros local\"})]}),(0,i.jsxs)(e.tr,{children:[(0,i.jsx)(e.td,{children:\"DeepSeek V3\"}),(0,i.jsx)(e.td,{children:\"4x Mac Studio (512 GB)\"}),(0,i.jsx)(e.td,{children:\"~12 tok/s\"}),(0,i.jsx)(e.td,{children:\"Anteriormente solo en la nube\"})]})]})]}),`\n`,(0,i.jsx)(e.h3,{id:\"an\\xE1lisis-de-latencia\",children:\"An\\xE1lisis de latencia\"}),`\n`,(0,i.jsxs)(e.table,{children:[(0,i.jsx)(e.thead,{children:(0,i.jsxs)(e.tr,{children:[(0,i.jsx)(e.th,{children:\"M\\xE9trica\"}),(0,i.jsx)(e.th,{children:\"Cl\\xFAster 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interrupciones\"})]})]})]}),`\n`,(0,i.jsx)(e.h3,{id:\"comparaci\\xF3n-de-costo-por-token\",children:\"Comparaci\\xF3n de costo por token\"}),`\n`,(0,i.jsx)(e.p,{children:\"Asumiendo operaci\\xF3n 24/7 durante 1 a\\xF1o:\"}),`\n`,(0,i.jsxs)(e.table,{children:[(0,i.jsx)(e.thead,{children:(0,i.jsxs)(e.tr,{children:[(0,i.jsx)(e.th,{children:\"Soluci\\xF3n\"}),(0,i.jsx)(e.th,{children:\"Costo de hardware\"}),(0,i.jsx)(e.th,{children:\"Costo operativo\"}),(0,i.jsx)(e.th,{children:\"Total 1 a\\xF1o\"}),(0,i.jsx)(e.th,{children:\"Costo/1M Tokens\"})]})}),(0,i.jsxs)(e.tbody,{children:[(0,i.jsxs)(e.tr,{children:[(0,i.jsx)(e.td,{children:\"Cl\\xFAster 4x Mac Studio\"}),(0,i.jsx)(e.td,{children:\"$47,000\"}),(0,i.jsx)(e.td,{children:\"~$500\"}),(0,i.jsx)(e.td,{children:\"$47,500\"}),(0,i.jsx)(e.td,{children:\"~$0.02\"})]}),(0,i.jsxs)(e.tr,{children:[(0,i.jsx)(e.td,{children:\"OpenAI GPT-4\"}),(0,i.jsx)(e.td,{children:\"$0\"}),(0,i.jsx)(e.td,{children:\"Basado en 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cl\\xFAster?\"}),`\n`,(0,i.jsx)(e.p,{children:\"El l\\xEDmite pr\\xE1ctico depende de su topolog\\xEDa. Con conexiones Thunderbolt directas (evitando concentradores), puede conectar 4-6 Mac de manera eficiente. El uso de una topolog\\xEDa de anillo permite escalar a m\\xE1s nodos manteniendo el ancho de banda completo. M\\xE1s all\\xE1 de 6 nodos, necesitar\\xE1 una planificaci\\xF3n cuidadosa de la topolog\\xEDa para evitar cuellos de botella de ancho de banda.\"}),`\n`,(0,i.jsx)(e.h3,{id:\"necesito-mac-id\\xE9nticos-para-el-cl\\xFAster\",children:\"\\xBFNecesito Mac id\\xE9nticos para el cl\\xFAster?\"}),`\n`,(0,i.jsx)(e.p,{children:\"No, MLX y EXO admiten cl\\xFAsteres heterog\\xE9neos. Sin embargo, el cl\\xFAster estar\\xE1 limitado por el componente m\\xE1s lento. Para obtener los mejores resultados, use Mac de generaci\\xF3n similar con versiones de Thunderbolt coincidentes. La distribuci\\xF3n de la memoria se ponderar\\xE1 por la RAM disponible de cada nodo.\"}),`\n`,(0,i.jsx)(e.h3,{id:\"puedo-usar-mac-con-thunderbolt-4-en-un-cl\\xFAster\",children:\"\\xBFPuedo usar Mac con Thunderbolt 4 en un cl\\xFAster?\"}),`\n`,(0,i.jsx)(e.p,{children:\"S\\xED, pero el ancho de banda se limitar\\xE1 a 40 Gbps en esas conexiones. Thunderbolt 5 y 4 son compatibles con versiones anteriores. El sistema funcionar\\xE1 a la velocidad m\\xE1s baja al mezclar generaciones. Para un mejor rendimiento, mantenga los nodos TB4 como nodos hoja en lugar de en medio de un anillo.\"}),`\n`,(0,i.jsx)(e.h3,{id:\"cu\\xE1l-es-la-memoria-m\\xEDnima-necesaria-para-el-cl\\xFAster\",children:\"\\xBFCu\\xE1l es la memoria m\\xEDnima necesaria para el cl\\xFAster?\"}),`\n`,(0,i.jsx)(e.p,{children:\"La memoria total del cl\\xFAster debe exceder el requisito de memoria de su modelo con algo de margen para operaciones. Para Llama 3.1 70B (modelo de 140 GB), necesita al menos 3 Mac con 48 GB cada uno (144 GB en total). Recomendamos un margen de 10-20% por encima del tama\\xF1o del modelo.\"}),`\n`,(0,i.jsx)(e.h3,{id:\"es-el-cl\\xFAster-mac-adecuado-para-entrenamiento-o-solo-inferencia\",children:\"\\xBFEs el cl\\xFAster Mac adecuado para entrenamiento o solo inferencia?\"}),`\n`,(0,i.jsx)(e.p,{children:\"\\xA1Ambos! MLX admite entrenamiento distribuido con promedio de gradientes entre nodos. Sin embargo, la inferencia es el caso de uso principal debido a los beneficios de la agrupaci\\xF3n de memoria para modelos grandes. El entrenamiento requiere m\\xE1s comunicaci\\xF3n entre nodos y es m\\xE1s sensible a la latencia de la red.\"}),`\n`,(0,i.jsx)(e.h3,{id:\"c\\xF3mo-se-compara-esto-con-las-instancias-de-gpu-en-la-nube\",children:\"\\xBFC\\xF3mo se compara esto con las instancias de GPU en la nube?\"}),`\n`,(0,i.jsx)(e.p,{children:\"Para uso a largo plazo (m\\xE1s de 6 meses de uso regular), el cl\\xFAster Mac es m\\xE1s rentable. Usted es due\\xF1o del hardware, no tiene cargos por hora y logra un rendimiento competitivo. Para uso ocasional o experimentaci\\xF3n, las instancias en la nube pueden ser m\\xE1s econ\\xF3micas inicialmente.\"}),`\n`,(0,i.jsx)(e.h3,{id:\"puedo-ejecutar-el-cl\\xFAster-247\",children:\"\\xBFPuedo ejecutar el cl\\xFAster 24/7?\"}),`\n`,(0,i.jsxs)(e.p,{children:[\"Absolutamente. El hardware Mac est\\xE1 dise\\xF1ado para un funcionamiento continuo. Los Mac Studio en particular tienen una excelente gesti\\xF3n t\\xE9rmica para cargas de trabajo sostenidas. Monitoree las temperaturas usando el Monitor de Actividad o \",(0,i.jsx)(e.code,{children:\"sudo powermetrics\"}),\" y asegure una ventilaci\\xF3n adecuada.\"]}),`\n`,(0,i.jsx)(e.h3,{id:\"qu\\xE9-sucede-si-falla-un-nodo\",children:\"\\xBFQu\\xE9 sucede si falla un nodo?\"}),`\n`,(0,i.jsx)(e.p,{children:\"Actualmente, el cl\\xFAster MLX no admite intercambio en caliente ni conmutaci\\xF3n por error autom\\xE1tica. Si un nodo se desconecta, el trabajo fallar\\xE1 y deber\\xE1 reiniciarse. Para cargas de trabajo cr\\xEDticas, implemente puntos de control en su c\\xF3digo para reanudar desde el \\xFAltimo estado guardado.\"}),`\n`,(0,i.jsx)(e.h3,{id:\"puedo-usar-el-cl\\xFAster-mientras-ejecuto-cargas-de-trabajo-de-ia\",children:\"\\xBFPuedo usar el cl\\xFAster mientras ejecuto cargas de trabajo de IA?\"}),`\n`,(0,i.jsx)(e.p,{children:\"S\\xED, pero el rendimiento puede verse afectado. La interfaz EXO permite la operaci\\xF3n en segundo plano mientras usa los Mac para otras tareas. Para obtener el mejor rendimiento de inferencia, minimice otras actividades durante cargas de trabajo de IA pesadas.\"}),`\n`,(0,i.jsx)(e.hr,{}),`\n`,(0,i.jsx)(e.h2,{id:\"conclusi\\xF3n\",children:\"Conclusi\\xF3n\"}),`\n`,(0,i.jsx)(e.p,{children:\"El cl\\xFAster Thunderbolt 5 de macOS Tahoe 26.2 representa un cambio de paradigma en la computaci\\xF3n de IA local. Al combinar m\\xFAltiples Mac en una supercomputadora unificada, los usuarios pueden ejecutar modelos de billones de par\\xE1metros a una fracci\\xF3n de los costos de los cl\\xFAsteres de GPU tradicionales.\"}),`\n`,(0,i.jsx)(e.p,{children:(0,i.jsx)(e.strong,{children:\"Beneficios clave:\"})}),`\n`,(0,i.jsxs)(e.ul,{children:[`\n`,(0,i.jsx)(e.li,{children:\"Consumo de energ\\xEDa 10 veces menor que las alternativas de GPU\"}),`\n`,(0,i.jsx)(e.li,{children:\"No se requiere hardware especializado\"}),`\n`,(0,i.jsx)(e.li,{children:\"Configuraci\\xF3n simple con MLX y EXO\"}),`\n`,(0,i.jsx)(e.li,{children:\"Escalable de 2 a 6+ nodos\"}),`\n`,(0,i.jsx)(e.li,{children:\"Procesamiento de IA local y privado\"}),`\n`]}),`\n`,(0,i.jsxs)(e.p,{children:[\"Para los usuarios invertidos en el ecosistema de Apple, esta caracter\\xEDstica por s\\xED sola puede justificar la actualizaci\\xF3n a macOS Tahoe 26.2. Consulte nuestra \",(0,i.jsx)(e.a,{href:\"/blog/macos-tahoe-26-2-update-complete-guide-2025\",children:\"Gu\\xEDa de actualizaci\\xF3n de macOS Tahoe 26.2\"}),\" para obtener instrucciones completas de actualizaci\\xF3n.\"]}),`\n`,(0,i.jsxs)(e.p,{children:[(0,i.jsx)(e.strong,{children:\"\\xBFListo para optimizar su Mac para cargas de trabajo de IA?\"}),\" Comience con nuestra \",(0,i.jsx)(e.a,{href:\"/blog/macos-tahoe-storage-management-optimization-guide-2025\",children:\"Gu\\xEDa de gesti\\xF3n de almacenamiento de macOS Tahoe\"}),\" para asegurarse de tener el espacio adecuado para modelos grandes.\"]}),`\n`,(0,i.jsx)(e.hr,{}),`\n`,(0,i.jsx)(e.h2,{id:\"fuentes\",children:\"Fuentes\"}),`\n`,(0,i.jsxs)(e.ul,{children:[`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.a,{href:\"https://appleinsider.com/articles/25/11/18/macos-tahoe-262-will-give-m5-macs-a-giant-machine-learning-speed-boost\",children:\"ML en macOS Tahoe obtiene impulso de GPU y cl\\xFAster Thunderbolt 5\"}),\" - Apple Insider, noviembre de 2025\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.a,{href:\"https://www.engadget.com/ai/you-can-turn-a-cluster-of-macs-into-an-ai-supercomputer-in-macos-tahoe-262-191500778.html\",children:\"Puedes convertir un cl\\xFAster de Macs en una supercomputadora de IA en macOS Tahoe 26.2\"}),\" - Engadget, noviembre de 2025\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.a,{href:\"https://9to5mac.com/2025/11/19/a-cluster-of-mac-studios-is-just-one-reason-we-no-longer-need-a-mac-pro/\",children:\"Un cl\\xFAster de Mac Studios es solo una raz\\xF3n por la que ya no necesitamos un Mac Pro\"}),\" - 9to5Mac, noviembre de 2025\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.a,{href:\"https://www.heise.de/en/news/AI-Cluster-Four-Macs-with-2-TB-can-run-the-giant-model-Kimi-K2-Thinking-11085716.html\",children:\"Cl\\xFAster de IA: Cuatro Macs con 2 TB pueden ejecutar el modelo gigante Kimi K2 Thinking\"}),\" - Heise Online, noviembre de 2025\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.a,{href:\"https://ml-explore.github.io/mlx/build/html/usage/distributed.html\",children:\"Documentaci\\xF3n de comunicaci\\xF3n distribuida de MLX\"}),\" - Documentos oficiales de Apple MLX\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.a,{href:\"https://github.com/exo-explore/exo\",children:\"EXO: Ejecute su propio cl\\xFAster de IA en casa\"}),\" - EXO Labs GitHub\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.a,{href:\"https://developer.apple.com/videos/play/wwdc2025/298/\",children:\"Explore modelos de lenguaje grandes en Apple silicon con MLX - WWDC25\"}),\" - Apple Developer\"]}),`\n`,(0,i.jsxs)(e.li,{children:[(0,i.jsx)(e.a,{href:\"https://moonshotai.github.io/Kimi-K2/\",children:\"Kimi K2 - Moonshot AI\"}),\" - Oficial Moonshot AI\"]}),`\n`]})]})}function o(n={}){let{wrapper:e}=n.components||{};return e?(0,i.jsx)(e,{...n,children:(0,i.jsx)(t,{...n})}):t(n)}return C(F);})();\n;return Component;","toc":[{"title":"Puntos clave","url":"#puntos-clave","depth":2},{"title":"Resumen ejecutivo: Entendiendo la tecnología de clústeres Mac","url":"#resumen-ejecutivo-entendiendo-la-tecnología-de-clústeres-mac","depth":2},{"title":"Por qué es importante el clúster Thunderbolt 5","url":"#por-qué-es-importante-el-clúster-thunderbolt-5","depth":3},{"title":"¿Quién se beneficia del clúster Mac?","url":"#quién-se-beneficia-del-clúster-mac","depth":3},{"title":"¿Qué es el clúster Thunderbolt 5 Mac?","url":"#qué-es-el-clúster-thunderbolt-5-mac","depth":2},{"title":"La evolución de la computación distribuida en Mac","url":"#la-evolución-de-la-computación-distribuida-en-mac","depth":3},{"title":"Cómo funciona el clúster Thunderbolt 5","url":"#cómo-funciona-el-clúster-thunderbolt-5","depth":3},{"title":"Ventaja de la memoria unificada de Apple Silicon","url":"#ventaja-de-la-memoria-unificada-de-apple-silicon","depth":3},{"title":"Requisitos de hardware y compatibilidad","url":"#requisitos-de-hardware-y-compatibilidad","depth":2},{"title":"Modelos de Mac compatibles","url":"#modelos-de-mac-compatibles","depth":3},{"title":"Configuraciones de clúster recomendadas","url":"#configuraciones-de-clúster-recomendadas","depth":3},{"title":"Guía de selección de cables Thunderbolt 5","url":"#guía-de-selección-de-cables-thunderbolt-5","depth":3},{"title":"Pila de software: Marcos MLX y EXO","url":"#pila-de-software-marcos-mlx-y-exo","depth":2},{"title":"Entendiendo la computación distribuida MLX","url":"#entendiendo-la-computación-distribuida-mlx","depth":3},{"title":"Backends de comunicación MLX","url":"#backends-de-comunicación-mlx","depth":3},{"title":"Entendiendo el entrenamiento distribuido vs inferencia","url":"#entendiendo-el-entrenamiento-distribuido-vs-inferencia","depth":3},{"title":"EXO: Gestión de clústeres simplificada","url":"#exo-gestión-de-clústeres-simplificada","depth":3},{"title":"Guía paso a paso de configuración del clúster","url":"#guía-paso-a-paso-de-configuración-del-clúster","depth":2},{"title":"Requisitos previos","url":"#requisitos-previos","depth":3},{"title":"Método 1: Configuración nativa MLX (Recomendado)","url":"#método-1-configuración-nativa-mlx-recomendado","depth":3},{"title":"Paso 1: Instalar MLX","url":"#paso-1-instalar-mlx","depth":4},{"title":"Paso 2: Configurar red Thunderbolt","url":"#paso-2-configurar-red-thunderbolt","depth":4},{"title":"Paso 3: Crear configuración de archivo host","url":"#paso-3-crear-configuración-de-archivo-host","depth":4},{"title":"Paso 4: Probar comunicación distribuida","url":"#paso-4-probar-comunicación-distribuida","depth":4},{"title":"Método 2: Configuración EXO (Fácil de usar)","url":"#método-2-configuración-exo-fácil-de-usar","depth":3},{"title":"Paso 1: Clonar e instalar EXO","url":"#paso-1-clonar-e-instalar-exo","depth":4},{"title":"Paso 2: Configurar MLX para Apple Silicon","url":"#paso-2-configurar-mlx-para-apple-silicon","depth":4},{"title":"Paso 3: Iniciar el clúster","url":"#paso-3-iniciar-el-clúster","depth":4},{"title":"Paso 4: Acceder a la interfaz","url":"#paso-4-acceder-a-la-interfaz","depth":4},{"title":"Ejecución de modelos de lenguaje grandes","url":"#ejecución-de-modelos-de-lenguaje-grandes","depth":2},{"title":"Descarga de modelos","url":"#descarga-de-modelos","depth":3},{"title":"Requisitos de memoria por modelo","url":"#requisitos-de-memoria-por-modelo","depth":3},{"title":"Ejecución de Kimi K2 Thinking","url":"#ejecución-de-kimi-k2-thinking","depth":3},{"title":"Optimización del rendimiento","url":"#optimización-del-rendimiento","depth":2},{"title":"Mejores prácticas de topología de red","url":"#mejores-prácticas-de-topología-de-red","depth":3},{"title":"Pautas de cable y conexión","url":"#pautas-de-cable-y-conexión","depth":3},{"title":"Equilibrio de memoria y computación","url":"#equilibrio-de-memoria-y-computación","depth":3},{"title":"Solución de problemas comunes","url":"#solución-de-problemas-comunes","depth":2},{"title":"Problemas de conexión","url":"#problemas-de-conexión","depth":3},{"title":"Errores MLX","url":"#errores-mlx","depth":3},{"title":"Configuración SSH","url":"#configuración-ssh","depth":3},{"title":"Eficiencia energética y análisis de costos","url":"#eficiencia-energética-y-análisis-de-costos","depth":2},{"title":"Comparación de consumo de energía","url":"#comparación-de-consumo-de-energía","depth":3},{"title":"Costo total de propiedad (TCO)","url":"#costo-total-de-propiedad-tco","depth":3},{"title":"Casos de uso y aplicaciones","url":"#casos-de-uso-y-aplicaciones","depth":2},{"title":"Investigación de aprendizaje automático","url":"#investigación-de-aprendizaje-automático","depth":3},{"title":"Flujos de trabajo creativos profesionales","url":"#flujos-de-trabajo-creativos-profesionales","depth":3},{"title":"Desarrollo y pruebas","url":"#desarrollo-y-pruebas","depth":3},{"title":"Escenarios de implementación empresarial","url":"#escenarios-de-implementación-empresarial","depth":3},{"title":"Futuro del clúster Mac","url":"#futuro-del-clúster-mac","depth":2},{"title":"M5 y más allá","url":"#m5-y-más-allá","depth":3},{"title":"Implicaciones para Mac Pro","url":"#implicaciones-para-mac-pro","depth":3},{"title":"Consideraciones de seguridad y privacidad","url":"#consideraciones-de-seguridad-y-privacidad","depth":2},{"title":"Por qué es importante el procesamiento local","url":"#por-qué-es-importante-el-procesamiento-local","depth":3},{"title":"Puntos de referencia de rendimiento del mundo real","url":"#puntos-de-referencia-de-rendimiento-del-mundo-real","depth":2},{"title":"Comparación de velocidad de inferencia","url":"#comparación-de-velocidad-de-inferencia","depth":3},{"title":"Análisis de latencia","url":"#análisis-de-latencia","depth":3},{"title":"Comparación de costo por token","url":"#comparación-de-costo-por-token","depth":3},{"title":"Preguntas frecuentes","url":"#preguntas-frecuentes","depth":2},{"title":"¿Cuántos Mac puedo conectar en un clúster?","url":"#cuántos-mac-puedo-conectar-en-un-clúster","depth":3},{"title":"¿Necesito Mac idénticos para el clúster?","url":"#necesito-mac-idénticos-para-el-clúster","depth":3},{"title":"¿Puedo usar Mac con Thunderbolt 4 en un clúster?","url":"#puedo-usar-mac-con-thunderbolt-4-en-un-clúster","depth":3},{"title":"¿Cuál es la memoria mínima necesaria para el clúster?","url":"#cuál-es-la-memoria-mínima-necesaria-para-el-clúster","depth":3},{"title":"¿Es el clúster Mac adecuado para entrenamiento o solo inferencia?","url":"#es-el-clúster-mac-adecuado-para-entrenamiento-o-solo-inferencia","depth":3},{"title":"¿Cómo se compara esto con las instancias de GPU en la nube?","url":"#cómo-se-compara-esto-con-las-instancias-de-gpu-en-la-nube","depth":3},{"title":"¿Puedo ejecutar el clúster 24/7?","url":"#puedo-ejecutar-el-clúster-247","depth":3},{"title":"¿Qué sucede si falla un nodo?","url":"#qué-sucede-si-falla-un-nodo","depth":3},{"title":"¿Puedo usar el clúster mientras ejecuto cargas de trabajo de IA?","url":"#puedo-usar-el-clúster-mientras-ejecuto-cargas-de-trabajo-de-ia","depth":3},{"title":"Conclusión","url":"#conclusión","depth":2},{"title":"Fuentes","url":"#fuentes","depth":2}],"estimatedTime":28}