{"id":16007,"date":"2026-08-11T09:34:32","date_gmt":"2026-08-11T07:34:32","guid":{"rendered":"https:\/\/www.palentino.es\/blog\/?p=16007"},"modified":"2026-08-11T09:34:34","modified_gmt":"2026-08-11T07:34:34","slug":"%f0%9f%a7%a0-ia-local-en-2026-hardware-software","status":"publish","type":"post","link":"https:\/\/www.palentino.es\/blog\/%f0%9f%a7%a0-ia-local-en-2026-hardware-software\/","title":{"rendered":"&#x1f9e0; IA local en 2026: hardware + software"},"content":{"rendered":"<div id=\"palen-162247760\" class=\"palen-antes-del-contenido palen-entity-placement\"><div class=\"palen-adlabel\">Anuncios<\/div><script async src=\"\/\/pagead2.googlesyndication.com\/pagead\/js\/adsbygoogle.js?client=ca-pub-2815317153396146\" crossorigin=\"anonymous\"><\/script><ins class=\"adsbygoogle\" style=\"display:inline-block;width:300px;height:250px;\" \ndata-ad-client=\"ca-pub-2815317153396146\" \ndata-ad-slot=\"4593837716\"><\/ins> \n<script> \n(adsbygoogle = window.adsbygoogle || []).push({}); \n<\/script>\n<\/div>\n<p class=\"wp-block-paragraph\">Ejecutar IA en local ya no consiste simplemente en comprar una GPU potente.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">La clave est\u00e1 en equilibrar <strong>memoria, ancho de banda, tama\u00f1o del modelo, contexto y n\u00famero de usuarios<\/strong>.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Una RTX 5090 puede ser extraordinariamente r\u00e1pida, mientras que plataformas con 128, 256 o incluso 512 GB de memoria permiten cargar modelos mucho mayores. Y en entornos profesionales aparecen DGX Spark, RTX PRO, AMD Instinct o Intel Gaudi.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Pero el hardware es solo la mitad del sistema:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Hardware \u2192 CUDA\/ROCm\/MLX \u2192 Ollama, llama.cpp, vLLM\u2026 \u2192 modelo \u2192 Open WebUI\/API\/RAG<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Tambi\u00e9n conviene entender conceptos como <strong>cuantizaci\u00f3n, KV Cache, tokens\/s y MoE (Mixture of Experts)<\/strong>, porque determinan cu\u00e1nto ocupa un modelo y c\u00f3mo se comporta realmente.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">La pregunta correcta no es:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>\u00bfCu\u00e1l es el equipo m\u00e1s potente?<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Sino:<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">&#x1f449; <strong>\u00bfQu\u00e9 modelo quiero ejecutar, con cu\u00e1nto contexto, para cu\u00e1ntos usuarios y a qu\u00e9 velocidad?<\/strong><\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Eso es realmente dimensionar una plataforma de IA local.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">#IA #IALocal #LLM #NVIDIA #AMD #Hardware #MachineLearning #RAG #ArtificialIntelligence<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">&#x1f916; Infograf\u00eda generada mediante IA.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><a href=\"https:\/\/www.palentino.es\/blog\/wp-content\/uploads\/2026\/08\/IA-local.png\"><img loading=\"lazy\" decoding=\"async\" width=\"1024\" height=\"768\" data-attachment-id=\"16008\" data-permalink=\"https:\/\/www.palentino.es\/blog\/%f0%9f%a7%a0-ia-local-en-2026-hardware-software\/ia-local\/\" data-orig-file=\"https:\/\/www.palentino.es\/blog\/wp-content\/uploads\/2026\/08\/IA-local.png\" data-orig-size=\"1448,1086\" data-comments-opened=\"0\" data-image-meta=\"{&quot;aperture&quot;:&quot;0&quot;,&quot;credit&quot;:&quot;&quot;,&quot;camera&quot;:&quot;&quot;,&quot;caption&quot;:&quot;&quot;,&quot;created_timestamp&quot;:&quot;0&quot;,&quot;copyright&quot;:&quot;&quot;,&quot;focal_length&quot;:&quot;0&quot;,&quot;iso&quot;:&quot;0&quot;,&quot;shutter_speed&quot;:&quot;0&quot;,&quot;title&quot;:&quot;&quot;,&quot;orientation&quot;:&quot;0&quot;,&quot;alt&quot;:&quot;&quot;}\" data-image-title=\"IA-local\" data-image-description=\"\" data-image-caption=\"\" data-large-file=\"https:\/\/www.palentino.es\/blog\/wp-content\/uploads\/2026\/08\/IA-local-1024x768.png\" src=\"https:\/\/www.palentino.es\/blog\/wp-content\/uploads\/2026\/08\/IA-local-1024x768.png\" alt=\"\" class=\"wp-image-16008\" srcset=\"https:\/\/www.palentino.es\/blog\/wp-content\/uploads\/2026\/08\/IA-local-1024x768.png 1024w, https:\/\/www.palentino.es\/blog\/wp-content\/uploads\/2026\/08\/IA-local-300x225.png 300w, https:\/\/www.palentino.es\/blog\/wp-content\/uploads\/2026\/08\/IA-local.png 1448w\" sizes=\"auto, (max-width: 1024px) 100vw, 1024px\" \/><\/a><\/figure>\n<div id=\"palen-3736356325\" class=\"palen-despues-del-contenido palen-entity-placement\"><div class=\"palen-adlabel\">Anuncios<\/div><script async src=\"\/\/pagead2.googlesyndication.com\/pagead\/js\/adsbygoogle.js?client=ca-pub-2815317153396146\" crossorigin=\"anonymous\"><\/script><ins class=\"adsbygoogle\" style=\"display:block;\" data-ad-client=\"ca-pub-2815317153396146\" \ndata-ad-slot=\"\" \ndata-ad-format=\"auto\" data-full-width-responsive=\"true\"><\/ins>\n<script> \n(adsbygoogle = window.adsbygoogle || []).push({}); \n<\/script>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>Ejecutar IA en local ya no consiste simplemente en comprar una GPU potente. La clave est\u00e1 en equilibrar memoria, ancho de banda, tama\u00f1o del modelo, contexto y n\u00famero de usuarios. Una RTX 5090 puede ser extraordinariamente r\u00e1pida, mientras que plataformas con 128, 256 o incluso 512 GB de memoria permiten cargar modelos mucho mayores. Y en entornos profesionales aparecen DGX Spark, RTX PRO, AMD Instinct o Intel Gaudi. Pero el hardware es solo la mitad del sistema: Hardware \u2192 CUDA\/ROCm\/MLX \u2192 Ollama, llama.cpp, vLLM\u2026 \u2192 modelo \u2192 Open WebUI\/API\/RAG Tambi\u00e9n conviene entender conceptos como cuantizaci\u00f3n, KV Cache, tokens\/s y MoE (Mixture of Experts), porque determinan cu\u00e1nto ocupa un modelo y c\u00f3mo se comporta realmente. La pregunta correcta no es: \u00bfCu\u00e1l es el equipo m\u00e1s potente? Sino: &#x1f449; \u00bfQu\u00e9 modelo quiero ejecutar, con cu\u00e1nto contexto, para cu\u00e1ntos usuarios y a qu\u00e9 velocidad? Eso es realmente dimensionar una plataforma de IA local. #IA #IALocal #LLM #NVIDIA #AMD #Hardware #MachineLearning #RAG #ArtificialIntelligence &#x1f916; Infograf\u00eda generada mediante IA.<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"advanced_seo_description":"","jetpack_seo_html_title":"","jetpack_seo_noindex":false,"_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_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2},"jetpack_post_was_ever_published":false},"categories":[1415],"tags":[],"class_list":["post-16007","post","type-post","status-publish","format-standard","hentry","category-sin-categoria-es"],"views":3,"jetpack_publicize_connections":[],"jetpack_featured_media_url":"","jetpack_shortlink":"https:\/\/wp.me\/p2ECph-4ab","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/www.palentino.es\/blog\/wp-json\/wp\/v2\/posts\/16007","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.palentino.es\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.palentino.es\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.palentino.es\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.palentino.es\/blog\/wp-json\/wp\/v2\/comments?post=16007"}],"version-history":[{"count":1,"href":"https:\/\/www.palentino.es\/blog\/wp-json\/wp\/v2\/posts\/16007\/revisions"}],"predecessor-version":[{"id":16009,"href":"https:\/\/www.palentino.es\/blog\/wp-json\/wp\/v2\/posts\/16007\/revisions\/16009"}],"wp:attachment":[{"href":"https:\/\/www.palentino.es\/blog\/wp-json\/wp\/v2\/media?parent=16007"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.palentino.es\/blog\/wp-json\/wp\/v2\/categories?post=16007"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.palentino.es\/blog\/wp-json\/wp\/v2\/tags?post=16007"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}