{"id":27,"date":"2026-07-18T07:33:35","date_gmt":"2026-07-18T07:33:35","guid":{"rendered":"https:\/\/myexpertservices.com\/blog\/?p=27"},"modified":"2026-07-18T07:33:35","modified_gmt":"2026-07-18T07:33:35","slug":"que-modelo-de-ia-usar-para-cada-tarea","status":"publish","type":"post","link":"https:\/\/myexpertservices.com\/blog\/que-modelo-de-ia-usar-para-cada-tarea\/","title":{"rendered":"Qu\u00e9 modelo de IA usar para cada tarea"},"content":{"rendered":"<p><!--\n  ART\u00cdCULO PARA WORDPRESS \u2014 MyExpertServices \/ myIA\n  C\u00f3mo usar: pega TODO este bloque en un bloque \"HTML personalizado\" de WordPress\n  (Gutenberg) o en el modo \"Texto\/HTML\" del editor cl\u00e1sico.\n  Este bloque NO incluye el t\u00edtulo ni la imagen de portada: a\u00f1\u00e1delos t\u00fa en el\n  campo de t\u00edtulo de la entrada y en la imagen destacada (usa portada.png).\n  Diseno a prueba de temas: todo el texto es oscuro sobre claro, asi que aunque tu\n  plantilla borre fondos, TODO sigue legible. 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Para una pyme, ese ruido es poco \u00fatil: lo que importa no es qui\u00e9n encabeza un ranking global esta semana, sino <strong>qu\u00e9 modelo resuelve mejor tu tarea concreta al mejor coste<\/strong>. Y ah\u00ed la respuesta casi nunca es \u201cuno solo\u201d.<\/p>\n<p>Hemos revisado los <em>benchmarks<\/em> independientes m\u00e1s serios y los precios oficiales de cada proveedor a julio de 2026. La conclusi\u00f3n es clara y, a la vez, liberadora: los cinco o seis mejores modelos est\u00e1n separados por muy pocos puntos, y la mejor decisi\u00f3n es <strong>emparejar cada caso de uso con el modelo id\u00f3neo<\/strong>. Esta gu\u00eda te da ese mapa.<\/p>\n<p>  <!-- ===================== VEREDICTO ===================== --><\/p>\n<div class=\"verdict\">\n    <span class=\"eyebrow\">El veredicto en 30 segundos<\/span><\/p>\n<h2>Lo esencial, sin rodeos<\/h2>\n<ul>\n<li><strong>No hay \u201cmejor modelo\u201d.<\/strong> En preferencia humana (LMArena) todo el top-10 cabe dentro del margen de ruido; la diferencia entre los l\u00edderes es de pocos puntos. Elige por tarea, no por ranking.<\/li>\n<li><strong>Programar y automatizar procesos:<\/strong> Claude Opus 4.8 y GPT-5.6 lideran; GLM-5.2 es la mejor opci\u00f3n open source.<\/li>\n<li><strong>Razonar, investigar y matem\u00e1ticas:<\/strong> GPT-5.6 va en cabeza (GPQA Diamond 94,6 %, AIME 2026 100 %).<\/li>\n<li><strong>Multimodal (imagen, v\u00eddeo, audio) y documentos muy largos:<\/strong> Gemini 3.1 Pro.<\/li>\n<li><strong>Volumen y coste bajo:<\/strong> DeepSeek, Gemini Flash y Claude Haiku hacen el 80 % del trabajo por una fracci\u00f3n del precio.<\/li>\n<li><strong>Datos sensibles \/ on-premise:<\/strong> modelos open source (Llama, Qwen, GLM, Mistral) que puedes alojar t\u00fa.<\/li>\n<li><strong>Regla de oro:<\/strong> un modelo potente para lo cr\u00edtico y uno barato y r\u00e1pido para el volumen. La mayor\u00eda de pymes necesitan 2-3 modelos, no uno.<\/li>\n<\/ul><\/div>\n<p>  <!-- ===================== METODOLOG\u00cdA ===================== --><\/p>\n<h2>C\u00f3mo hemos hecho esta comparativa<\/h2>\n<p>Para evitar sesgos de fabricante, los datos proceden de evaluaciones <strong>independientes<\/strong> y de las <strong>p\u00e1ginas oficiales de precios<\/strong> de cada proveedor, a julio de 2026: el \u00edndice de inteligencia de <a href=\"https:\/\/artificialanalysis.ai\/models\" target=\"_blank\" rel=\"noopener\">Artificial Analysis<\/a>, las votaciones ciegas de <a href=\"https:\/\/lmarena.ai\" target=\"_blank\" rel=\"noopener\">LMArena<\/a> (antes Chatbot Arena), los <em>benchmarks<\/em> de programaci\u00f3n <a href=\"https:\/\/www.vals.ai\/benchmarks\/swebench\" target=\"_blank\" rel=\"noopener\">SWE-bench<\/a> (Verified y Pro) y los de capacidad multimodal (MMMU-Pro, Video-MME).<\/p>\n<div class=\"note\">\n    <b>Aviso honesto sobre los benchmarks.<\/b> Son una br\u00fajula, no un mapa. Algunos ya est\u00e1n \u201csaturados\u201d (los mejores modelos rozan el techo y dejan de diferenciarse) y en julio de 2026 OpenAI public\u00f3 una auditor\u00eda que detect\u00f3 fallos en cerca del 30 % de las tareas de SWE-bench Pro. \u00dasalos como orientaci\u00f3n general y <b>valida siempre con tus propios casos<\/b> antes de decidir.\n  <\/div>\n<p>  <!-- ===================== RADAR ===================== --><\/p>\n<h2>El mapa de modelos, de un vistazo<\/h2>\n<p>Este gr\u00e1fico de ara\u00f1a resume seis dimensiones que importan a una empresa: <strong>razonamiento<\/strong>, <strong>programaci\u00f3n<\/strong>, <strong>capacidad multimodal<\/strong>, <strong>velocidad<\/strong>, <strong>contexto<\/strong> (cu\u00e1nto texto \u201clee\u201d de una vez) y <strong>coste-eficiencia<\/strong>. Se ve a simple vista que cada modelo dibuja una figura distinta: no hay uno que lo domine todo.<\/p>\n<div class=\"card\">\n    <span class=\"eyebrow\">Gr\u00e1fico 1 \u00b7 Comparativa multidimensional<\/span><\/p>\n<h3>Perfil de cada modelo por capacidad<\/h3>\n<p class=\"sub\">\u00cdndice normalizado 0-100 elaborado a partir de los benchmarks citados. 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multimodales (MMMU-Pro, Video-MME), julio 2026.<\/p>\n<\/p><\/div>\n<p>  <!-- ===================== INTELIGENCIA GENERAL ===================== --><\/p>\n<h2>Inteligencia general<\/h2>\n<p>El \u00cdndice de Inteligencia de Artificial Analysis combina nueve pruebas de razonamiento, ciencia, c\u00f3digo y tareas \u201cag\u00e9nticas\u201d (el modelo actuando por pasos con herramientas). En su versi\u00f3n de 2026, ponderada hacia esas tareas ag\u00e9nticas, <strong>el top est\u00e1 extraordinariamente comprimido<\/strong>: los primeros puestos se separan por d\u00e9cimas.<\/p>\n<div class=\"card\">\n    <span class=\"eyebrow\">Gr\u00e1fico 2 \u00b7 \u00cdndice de inteligencia (AA)<\/span><\/p>\n<h3>Los modelos m\u00e1s capaces, julio 2026<\/h3>\n<p class=\"sub\">Puntuaci\u00f3n del Artificial Analysis Intelligence Index v4.1 (mayor = mejor).<\/p>\n<div class=\"chartsvg\"><svg viewBox=\"0 0 720 362\" width=\"720\" height=\"362\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" font-family=\"'Inter',system-ui,-apple-system,Segoe UI,Arial,sans-serif\"><line x1=\"196.0\" y1=\"14\" x2=\"196.0\" y2=\"316.0\" stroke=\"#E7ECF4\" stroke-width=\"1\"\/><text x=\"196.0\" y=\"333\" fill=\"#7A8699\" font-size=\"11\" text-anchor=\"middle\">0<\/text><line x1=\"350.7\" y1=\"14\" x2=\"350.7\" y2=\"316.0\" stroke=\"#E7ECF4\" stroke-width=\"1\"\/><text x=\"350.7\" y=\"333\" fill=\"#7A8699\" font-size=\"11\" text-anchor=\"middle\">20<\/text><line x1=\"505.3\" y1=\"14\" x2=\"505.3\" y2=\"316.0\" stroke=\"#E7ECF4\" stroke-width=\"1\"\/><text x=\"505.3\" y=\"333\" fill=\"#7A8699\" font-size=\"11\" text-anchor=\"middle\">40<\/text><line x1=\"660.0\" y1=\"14\" x2=\"660.0\" y2=\"316.0\" stroke=\"#E7ECF4\" stroke-width=\"1\"\/><text x=\"660.0\" y=\"333\" fill=\"#7A8699\" font-size=\"11\" text-anchor=\"middle\">60<\/text><line x1=\"196\" y1=\"316\" x2=\"660\" y2=\"316\" stroke=\"#D3DBE6\" stroke-width=\"1\"\/><text x=\"184\" y=\"31.0\" fill=\"#16223A\" font-size=\"12.5\" text-anchor=\"end\" dominant-baseline=\"middle\">Claude Fable 5 *<\/text><rect x=\"196\" y=\"16\" width=\"463.2\" height=\"30\" rx=\"5\" fill=\"#D97757\"\/><text x=\"667.2\" y=\"31.0\" fill=\"#16223A\" font-size=\"12.5\" font-weight=\"700\" dominant-baseline=\"middle\">59,9<\/text><text x=\"184\" y=\"76.0\" fill=\"#16223A\" font-size=\"12.5\" text-anchor=\"end\" dominant-baseline=\"middle\">GPT-5.6 Sol<\/text><rect x=\"196\" y=\"61\" width=\"455.5\" height=\"30\" rx=\"5\" fill=\"#10A37F\"\/><text x=\"659.5\" y=\"76.0\" fill=\"#16223A\" font-size=\"12.5\" font-weight=\"700\" dominant-baseline=\"middle\">58,9<\/text><text x=\"184\" y=\"121.0\" fill=\"#16223A\" font-size=\"12.5\" text-anchor=\"end\" dominant-baseline=\"middle\">Kimi K3<\/text><rect x=\"196\" y=\"106\" width=\"441.6\" height=\"30\" rx=\"5\" fill=\"#6B7280\"\/><text x=\"645.6\" y=\"121.0\" fill=\"#16223A\" font-size=\"12.5\" font-weight=\"700\" dominant-baseline=\"middle\">57,1<\/text><text x=\"184\" y=\"166.0\" fill=\"#16223A\" font-size=\"12.5\" text-anchor=\"end\" dominant-baseline=\"middle\">Grok 4.5<\/text><rect x=\"196\" y=\"151\" width=\"417.6\" height=\"30\" rx=\"5\" fill=\"#475569\"\/><text x=\"621.6\" y=\"166.0\" fill=\"#16223A\" font-size=\"12.5\" font-weight=\"700\" dominant-baseline=\"middle\">54<\/text><text x=\"184\" y=\"211.0\" fill=\"#16223A\" font-size=\"12.5\" text-anchor=\"end\" dominant-baseline=\"middle\">Claude Sonnet 5<\/text><rect x=\"196\" y=\"196\" width=\"409.9\" height=\"30\" rx=\"5\" fill=\"#D97757\"\/><text x=\"613.9\" y=\"211.0\" fill=\"#16223A\" font-size=\"12.5\" font-weight=\"700\" dominant-baseline=\"middle\">53<\/text><text x=\"184\" y=\"256.0\" fill=\"#16223A\" font-size=\"12.5\" text-anchor=\"end\" dominant-baseline=\"middle\">GPT-5.6 Luna<\/text><rect x=\"196\" y=\"241\" width=\"394.4\" height=\"30\" rx=\"5\" fill=\"#10A37F\"\/><text x=\"598.4\" y=\"256.0\" fill=\"#16223A\" font-size=\"12.5\" font-weight=\"700\" dominant-baseline=\"middle\">51<\/text><text x=\"184\" y=\"301.0\" fill=\"#16223A\" font-size=\"12.5\" text-anchor=\"end\" dominant-baseline=\"middle\">GLM-5.2 (open)<\/text><rect x=\"196\" y=\"286\" width=\"394.4\" height=\"30\" rx=\"5\" fill=\"#EA580C\"\/><text x=\"598.4\" y=\"301.0\" fill=\"#16223A\" font-size=\"12.5\" font-weight=\"700\" dominant-baseline=\"middle\">51<\/text><text x=\"428.0\" y=\"354\" fill=\"#5E6C82\" font-size=\"12\" text-anchor=\"middle\">\u00cdndice de Inteligencia AA (v4.1)<\/text><\/svg><\/div>\n<p class=\"hint\">* Claude Fable 5 lidera el \u00edndice, pero tiene acceso restringido (uso limitado por controles de exportaci\u00f3n y clasificadores de seguridad). Claude Opus 4.8 y Gemini 3.1 Pro se sit\u00faan en la misma franja alta.<\/p>\n<p class=\"src\">Fuente: <a href=\"https:\/\/artificialanalysis.ai\/models\" target=\"_blank\" rel=\"noopener\">Artificial Analysis<\/a> y <a href=\"https:\/\/www.datalearner.com\/en\/leaderboards\" target=\"_blank\" rel=\"noopener\">DataLearner<\/a>, julio 2026.<\/p>\n<\/p><\/div>\n<p>  <!-- ===================== PROGRAMACI\u00d3N ===================== --><\/p>\n<h2>Programaci\u00f3n y desarrollo<\/h2>\n<p>Para automatizar procesos, construir herramientas internas o integrar sistemas, el <em>benchmark<\/em> de referencia es SWE-bench: el modelo debe resolver incidencias reales de GitHub. La versi\u00f3n cl\u00e1sica (Verified) ya est\u00e1 saturada \u2014casi todos superan el 88 %\u2014, as\u00ed que la comparativa \u00fatil es <strong>SWE-bench Pro<\/strong>, m\u00e1s dif\u00edcil y realista para c\u00f3digo privado.<\/p>\n<div class=\"card\">\n    <span class=\"eyebrow\">Gr\u00e1fico 3 \u00b7 Programaci\u00f3n<\/span><\/p>\n<h3>SWE-bench Pro: resolver bugs reales<\/h3>\n<p class=\"sub\">% de incidencias resueltas (mayor = mejor). M\u00e1s exigente que SWE-bench Verified.<\/p>\n<div class=\"chartsvg\"><svg viewBox=\"0 0 720 497\" width=\"720\" height=\"497\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" font-family=\"'Inter',system-ui,-apple-system,Segoe UI,Arial,sans-serif\"><line x1=\"196.0\" y1=\"14\" x2=\"196.0\" y2=\"451.0\" stroke=\"#E7ECF4\" stroke-width=\"1\"\/><text x=\"196.0\" y=\"468\" fill=\"#7A8699\" font-size=\"11\" text-anchor=\"middle\">0<\/text><line x1=\"288.8\" y1=\"14\" x2=\"288.8\" y2=\"451.0\" stroke=\"#E7ECF4\" stroke-width=\"1\"\/><text x=\"288.8\" y=\"468\" fill=\"#7A8699\" font-size=\"11\" text-anchor=\"middle\">20<\/text><line x1=\"381.6\" y1=\"14\" x2=\"381.6\" y2=\"451.0\" stroke=\"#E7ECF4\" stroke-width=\"1\"\/><text x=\"381.6\" y=\"468\" fill=\"#7A8699\" font-size=\"11\" text-anchor=\"middle\">40<\/text><line x1=\"474.4\" y1=\"14\" x2=\"474.4\" y2=\"451.0\" stroke=\"#E7ECF4\" stroke-width=\"1\"\/><text x=\"474.4\" y=\"468\" fill=\"#7A8699\" font-size=\"11\" text-anchor=\"middle\">60<\/text><line x1=\"567.2\" y1=\"14\" x2=\"567.2\" y2=\"451.0\" stroke=\"#E7ECF4\" stroke-width=\"1\"\/><text x=\"567.2\" y=\"468\" fill=\"#7A8699\" font-size=\"11\" text-anchor=\"middle\">80<\/text><line x1=\"660.0\" y1=\"14\" x2=\"660.0\" y2=\"451.0\" stroke=\"#E7ECF4\" stroke-width=\"1\"\/><text x=\"660.0\" y=\"468\" fill=\"#7A8699\" font-size=\"11\" text-anchor=\"middle\">100<\/text><line x1=\"196\" y1=\"451\" x2=\"660\" y2=\"451\" stroke=\"#D3DBE6\" stroke-width=\"1\"\/><text x=\"184\" y=\"31.0\" fill=\"#16223A\" font-size=\"12.5\" text-anchor=\"end\" dominant-baseline=\"middle\">Claude Fable 5 *<\/text><rect x=\"196\" y=\"16\" width=\"372.6\" height=\"30\" rx=\"5\" fill=\"#D97757\"\/><text x=\"576.6\" y=\"31.0\" fill=\"#16223A\" font-size=\"12.5\" font-weight=\"700\" dominant-baseline=\"middle\">80,3<\/text><text x=\"184\" y=\"76.0\" fill=\"#16223A\" font-size=\"12.5\" text-anchor=\"end\" dominant-baseline=\"middle\">Claude Opus 4.8<\/text><rect x=\"196\" y=\"61\" width=\"321.1\" height=\"30\" rx=\"5\" fill=\"#D97757\"\/><text x=\"525.1\" y=\"76.0\" fill=\"#16223A\" font-size=\"12.5\" font-weight=\"700\" dominant-baseline=\"middle\">69,2<\/text><text x=\"184\" y=\"121.0\" fill=\"#16223A\" font-size=\"12.5\" text-anchor=\"end\" dominant-baseline=\"middle\">GPT-5.6 Sol<\/text><rect x=\"196\" y=\"106\" width=\"299.7\" height=\"30\" rx=\"5\" fill=\"#10A37F\"\/><text x=\"503.7\" y=\"121.0\" fill=\"#16223A\" font-size=\"12.5\" font-weight=\"700\" dominant-baseline=\"middle\">64,6<\/text><text x=\"184\" y=\"166.0\" fill=\"#16223A\" font-size=\"12.5\" text-anchor=\"end\" dominant-baseline=\"middle\">GPT-5.6 Terra<\/text><rect x=\"196\" y=\"151\" width=\"294.2\" height=\"30\" rx=\"5\" fill=\"#10A37F\"\/><text x=\"498.2\" y=\"166.0\" fill=\"#16223A\" font-size=\"12.5\" font-weight=\"700\" dominant-baseline=\"middle\">63,4<\/text><text x=\"184\" y=\"211.0\" fill=\"#16223A\" font-size=\"12.5\" text-anchor=\"end\" dominant-baseline=\"middle\">GPT-5.6 Luna<\/text><rect x=\"196\" y=\"196\" width=\"290.9\" height=\"30\" rx=\"5\" fill=\"#10A37F\"\/><text x=\"494.9\" y=\"211.0\" fill=\"#16223A\" font-size=\"12.5\" font-weight=\"700\" dominant-baseline=\"middle\">62,7<\/text><text x=\"184\" y=\"256.0\" fill=\"#16223A\" font-size=\"12.5\" text-anchor=\"end\" dominant-baseline=\"middle\">GLM-5.2 (open)<\/text><rect x=\"196\" y=\"241\" width=\"288.1\" height=\"30\" rx=\"5\" fill=\"#EA580C\"\/><text x=\"492.1\" y=\"256.0\" fill=\"#16223A\" font-size=\"12.5\" font-weight=\"700\" dominant-baseline=\"middle\">62,1<\/text><text x=\"184\" y=\"301.0\" fill=\"#16223A\" font-size=\"12.5\" text-anchor=\"end\" dominant-baseline=\"middle\">Qwen3.7 Max (open)<\/text><rect x=\"196\" y=\"286\" width=\"281.2\" height=\"30\" rx=\"5\" fill=\"#EA580C\"\/><text x=\"485.2\" y=\"301.0\" fill=\"#16223A\" font-size=\"12.5\" font-weight=\"700\" dominant-baseline=\"middle\">60,6<\/text><text x=\"184\" y=\"346.0\" fill=\"#16223A\" font-size=\"12.5\" text-anchor=\"end\" dominant-baseline=\"middle\">MiniMax M3 (open)<\/text><rect x=\"196\" y=\"331\" width=\"273.8\" height=\"30\" rx=\"5\" fill=\"#EA580C\"\/><text x=\"477.8\" y=\"346.0\" fill=\"#16223A\" font-size=\"12.5\" font-weight=\"700\" dominant-baseline=\"middle\">59<\/text><text x=\"184\" y=\"391.0\" fill=\"#16223A\" font-size=\"12.5\" text-anchor=\"end\" dominant-baseline=\"middle\">Kimi K2.6 (open)<\/text><rect x=\"196\" y=\"376\" width=\"271.9\" height=\"30\" rx=\"5\" fill=\"#EA580C\"\/><text x=\"475.9\" y=\"391.0\" fill=\"#16223A\" font-size=\"12.5\" font-weight=\"700\" dominant-baseline=\"middle\">58,6<\/text><text x=\"184\" y=\"436.0\" fill=\"#16223A\" font-size=\"12.5\" text-anchor=\"end\" dominant-baseline=\"middle\">Gemini 3.1 Pro<\/text><rect x=\"196\" y=\"421\" width=\"251.5\" height=\"30\" rx=\"5\" fill=\"#3B82F6\"\/><text x=\"455.5\" y=\"436.0\" fill=\"#16223A\" font-size=\"12.5\" font-weight=\"700\" dominant-baseline=\"middle\">54,2<\/text><text x=\"428.0\" y=\"489\" fill=\"#5E6C82\" font-size=\"12\" text-anchor=\"middle\">% de incidencias resueltas (SWE-bench Pro)<\/text><\/svg><\/div>\n<p class=\"hint\">L\u00e9elo como orientaci\u00f3n: OpenAI detect\u00f3 fallos en ~30 % de las tareas de este test. Claude Opus 4.8 lidera entre los modelos de acceso general; GLM-5.2 encabeza el open source.<\/p>\n<p class=\"src\">Fuente: <a href=\"https:\/\/codingfleet.com\/blog\/swe-bench-pro-leaderboard-2026\/\" target=\"_blank\" rel=\"noopener\">SWE-bench Pro leaderboard<\/a> y <a href=\"https:\/\/www.morphllm.com\/swe-bench-pro\" target=\"_blank\" rel=\"noopener\">Morph<\/a> (cifras de proveedor), 2026.<\/p>\n<\/p><\/div>\n<p>  <!-- ===================== PRECIO ===================== --><\/p>\n<h2>Precio: lo que de verdad decide en una pyme<\/h2>\n<p>Aqu\u00ed es donde las diferencias son enormes. Entre el modelo m\u00e1s barato y el buque insignia m\u00e1s caro hay <strong>hasta 50 veces de diferencia<\/strong> por mill\u00f3n de tokens de salida. Para tareas de alto volumen (atenci\u00f3n al cliente, clasificaci\u00f3n, res\u00famenes), pagar de m\u00e1s no compensa: un modelo econ\u00f3mico hace el trabajo igual de bien.<\/p>\n<div class=\"card\">\n    <span class=\"eyebrow\">Gr\u00e1fico 4 \u00b7 Precio de API<\/span><\/p>\n<h3>Coste por mill\u00f3n de tokens (entrada vs. salida)<\/h3>\n<p class=\"sub\">En d\u00f3lares por 1M de tokens. Menor = m\u00e1s barato. Ojo a la escala entre modelos.<\/p>\n<div class=\"chartsvg\"><svg viewBox=\"0 0 720 454\" width=\"720\" height=\"454\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" font-family=\"'Inter',system-ui,-apple-system,Segoe UI,Arial,sans-serif\"><rect x=\"196\" y=\"12\" width=\"14\" height=\"14\" rx=\"3\" fill=\"#3B82F6\"\/><text x=\"216\" y=\"23\" fill=\"#16223A\" font-size=\"12.5\">Entrada ($\/1M)<\/text><rect x=\"346\" y=\"12\" width=\"14\" height=\"14\" rx=\"3\" fill=\"#D97757\"\/><text x=\"366\" y=\"23\" fill=\"#16223A\" font-size=\"12.5\">Salida ($\/1M)<\/text><line x1=\"196.0\" y1=\"38\" x2=\"196.0\" y2=\"408.0\" stroke=\"#E7ECF4\" stroke-width=\"1\"\/><text x=\"196.0\" y=\"425\" fill=\"#7A8699\" font-size=\"11\" text-anchor=\"middle\">$0<\/text><line x1=\"288.8\" y1=\"38\" x2=\"288.8\" y2=\"408.0\" stroke=\"#E7ECF4\" stroke-width=\"1\"\/><text x=\"288.8\" y=\"425\" fill=\"#7A8699\" font-size=\"11\" text-anchor=\"middle\">$5<\/text><line x1=\"381.6\" y1=\"38\" x2=\"381.6\" y2=\"408.0\" stroke=\"#E7ECF4\" stroke-width=\"1\"\/><text x=\"381.6\" y=\"425\" fill=\"#7A8699\" font-size=\"11\" text-anchor=\"middle\">$10<\/text><line x1=\"474.4\" y1=\"38\" x2=\"474.4\" y2=\"408.0\" stroke=\"#E7ECF4\" stroke-width=\"1\"\/><text x=\"474.4\" y=\"425\" fill=\"#7A8699\" font-size=\"11\" text-anchor=\"middle\">$15<\/text><line x1=\"567.2\" y1=\"38\" x2=\"567.2\" y2=\"408.0\" stroke=\"#E7ECF4\" stroke-width=\"1\"\/><text x=\"567.2\" y=\"425\" fill=\"#7A8699\" font-size=\"11\" text-anchor=\"middle\">$20<\/text><line x1=\"660.0\" y1=\"38\" x2=\"660.0\" y2=\"408.0\" stroke=\"#E7ECF4\" stroke-width=\"1\"\/><text x=\"660.0\" y=\"425\" fill=\"#7A8699\" font-size=\"11\" text-anchor=\"middle\">$25<\/text><line x1=\"196\" y1=\"408\" x2=\"660\" y2=\"408\" stroke=\"#D3DBE6\" stroke-width=\"1\"\/><text x=\"184\" y=\"56.0\" fill=\"#16223A\" font-size=\"12.5\" text-anchor=\"end\" dominant-baseline=\"middle\">DeepSeek V3.2<\/text><rect x=\"196\" y=\"42\" width=\"5.2\" height=\"13\" rx=\"3\" fill=\"#3B82F6\"\/><text x=\"207.2\" y=\"48.5\" fill=\"#5E6C82\" font-size=\"11\" dominant-baseline=\"middle\">$0.28<\/text><rect x=\"196\" y=\"58\" width=\"7.8\" height=\"13\" rx=\"3\" fill=\"#D97757\"\/><text x=\"209.8\" y=\"64.5\" fill=\"#16223A\" font-size=\"11\" font-weight=\"700\" dominant-baseline=\"middle\">$0.42<\/text><text x=\"184\" y=\"104.0\" fill=\"#16223A\" font-size=\"12.5\" text-anchor=\"end\" dominant-baseline=\"middle\">Gemini 3 Flash<\/text><rect x=\"196\" y=\"90\" width=\"9.3\" height=\"13\" rx=\"3\" fill=\"#3B82F6\"\/><text x=\"211.3\" y=\"96.5\" fill=\"#5E6C82\" font-size=\"11\" dominant-baseline=\"middle\">$0.5<\/text><rect x=\"196\" y=\"106\" width=\"55.7\" height=\"13\" rx=\"3\" fill=\"#D97757\"\/><text x=\"257.7\" y=\"112.5\" fill=\"#16223A\" font-size=\"11\" font-weight=\"700\" dominant-baseline=\"middle\">$3<\/text><text x=\"184\" y=\"152.0\" fill=\"#16223A\" font-size=\"12.5\" text-anchor=\"end\" dominant-baseline=\"middle\">Claude Haiku 4.5<\/text><rect x=\"196\" y=\"138\" width=\"18.6\" height=\"13\" rx=\"3\" fill=\"#3B82F6\"\/><text x=\"220.6\" y=\"144.5\" fill=\"#5E6C82\" font-size=\"11\" dominant-baseline=\"middle\">$1<\/text><rect x=\"196\" y=\"154\" width=\"92.8\" height=\"13\" rx=\"3\" fill=\"#D97757\"\/><text x=\"294.8\" y=\"160.5\" fill=\"#16223A\" font-size=\"11\" font-weight=\"700\" dominant-baseline=\"middle\">$5<\/text><text x=\"184\" y=\"200.0\" fill=\"#16223A\" font-size=\"12.5\" text-anchor=\"end\" dominant-baseline=\"middle\">GPT-5.6 Luna<\/text><rect x=\"196\" y=\"186\" width=\"18.6\" height=\"13\" rx=\"3\" fill=\"#3B82F6\"\/><text x=\"220.6\" y=\"192.5\" fill=\"#5E6C82\" font-size=\"11\" dominant-baseline=\"middle\">$1<\/text><rect x=\"196\" y=\"202\" width=\"111.4\" height=\"13\" rx=\"3\" fill=\"#D97757\"\/><text x=\"313.4\" y=\"208.5\" fill=\"#16223A\" font-size=\"11\" font-weight=\"700\" dominant-baseline=\"middle\">$6<\/text><text x=\"184\" y=\"248.0\" fill=\"#16223A\" font-size=\"12.5\" text-anchor=\"end\" dominant-baseline=\"middle\">Grok 4.5<\/text><rect x=\"196\" y=\"234\" width=\"37.1\" height=\"13\" rx=\"3\" fill=\"#3B82F6\"\/><text x=\"239.1\" y=\"240.5\" fill=\"#5E6C82\" font-size=\"11\" dominant-baseline=\"middle\">$2<\/text><rect x=\"196\" y=\"250\" width=\"111.4\" height=\"13\" rx=\"3\" fill=\"#D97757\"\/><text x=\"313.4\" y=\"256.5\" fill=\"#16223A\" font-size=\"11\" font-weight=\"700\" dominant-baseline=\"middle\">$6<\/text><text x=\"184\" y=\"296.0\" fill=\"#16223A\" font-size=\"12.5\" text-anchor=\"end\" dominant-baseline=\"middle\">Claude Sonnet 5 \u2020<\/text><rect x=\"196\" y=\"282\" width=\"37.1\" height=\"13\" rx=\"3\" fill=\"#3B82F6\"\/><text x=\"239.1\" y=\"288.5\" fill=\"#5E6C82\" font-size=\"11\" dominant-baseline=\"middle\">$2<\/text><rect x=\"196\" y=\"298\" width=\"185.6\" height=\"13\" rx=\"3\" fill=\"#D97757\"\/><text x=\"387.6\" y=\"304.5\" fill=\"#16223A\" font-size=\"11\" font-weight=\"700\" dominant-baseline=\"middle\">$10<\/text><text x=\"184\" y=\"344.0\" fill=\"#16223A\" font-size=\"12.5\" text-anchor=\"end\" dominant-baseline=\"middle\">Gemini 3.1 Pro<\/text><rect x=\"196\" y=\"330\" width=\"37.1\" height=\"13\" rx=\"3\" fill=\"#3B82F6\"\/><text x=\"239.1\" y=\"336.5\" fill=\"#5E6C82\" font-size=\"11\" dominant-baseline=\"middle\">$2<\/text><rect x=\"196\" y=\"346\" width=\"222.7\" height=\"13\" rx=\"3\" fill=\"#D97757\"\/><text x=\"424.7\" y=\"352.5\" fill=\"#16223A\" font-size=\"11\" font-weight=\"700\" dominant-baseline=\"middle\">$12<\/text><text x=\"184\" y=\"392.0\" fill=\"#16223A\" font-size=\"12.5\" text-anchor=\"end\" dominant-baseline=\"middle\">Claude Opus 4.8<\/text><rect x=\"196\" y=\"378\" width=\"92.8\" height=\"13\" rx=\"3\" fill=\"#3B82F6\"\/><text x=\"294.8\" y=\"384.5\" fill=\"#5E6C82\" font-size=\"11\" dominant-baseline=\"middle\">$5<\/text><rect x=\"196\" y=\"394\" width=\"464.0\" height=\"13\" rx=\"3\" fill=\"#D97757\"\/><text x=\"666.0\" y=\"400.5\" fill=\"#16223A\" font-size=\"11\" font-weight=\"700\" dominant-baseline=\"middle\">$25<\/text><text x=\"428.0\" y=\"446\" fill=\"#5E6C82\" font-size=\"12\" text-anchor=\"middle\">USD por 1M de tokens<\/text><\/svg><\/div>\n<p class=\"hint\">\u2020 Claude Sonnet 5 muestra su precio de introducci\u00f3n (hasta el 31 ago 2026; despu\u00e9s 3 $\/15 $). Existen opciones a\u00fan m\u00e1s baratas de Grok (4.1) y modelos open source autoalojados.<\/p>\n<p class=\"src\">Fuente: p\u00e1ginas oficiales de precios (<a href=\"https:\/\/www.anthropic.com\/pricing\" target=\"_blank\" rel=\"noopener\">Anthropic<\/a>) y <a href=\"https:\/\/intuitionlabs.ai\/articles\/ai-api-pricing-comparison-grok-gemini-openai-claude\" target=\"_blank\" rel=\"noopener\">IntuitionLabs<\/a>, julio 2026.<\/p>\n<\/p><\/div>\n<p>  <!-- ===================== VELOCIDAD ===================== --><\/p>\n<h2>Velocidad<\/h2>\n<p>Para un chatbot o una experiencia en tiempo real, la velocidad (tokens por segundo) marca la diferencia entre fluido y frustrante. Los buques insignia de m\u00e1xima calidad tienden a ser m\u00e1s lentos porque \u201cpiensan\u201d m\u00e1s; para volumen, conviene un modelo r\u00e1pido de gama media.<\/p>\n<div class=\"card\">\n    <span class=\"eyebrow\">Gr\u00e1fico 5 \u00b7 Velocidad<\/span><\/p>\n<h3>Tokens generados por segundo<\/h3>\n<p class=\"sub\">Rendimiento de la API de primera parte (mayor = m\u00e1s r\u00e1pido).<\/p>\n<div class=\"chartsvg\"><svg viewBox=\"0 0 720 227\" width=\"720\" height=\"227\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" font-family=\"'Inter',system-ui,-apple-system,Segoe UI,Arial,sans-serif\"><line x1=\"196.0\" y1=\"14\" x2=\"196.0\" y2=\"181.0\" stroke=\"#E7ECF4\" stroke-width=\"1\"\/><text x=\"196.0\" y=\"198\" fill=\"#7A8699\" font-size=\"11\" text-anchor=\"middle\">0<\/text><line x1=\"288.8\" y1=\"14\" x2=\"288.8\" y2=\"181.0\" stroke=\"#E7ECF4\" stroke-width=\"1\"\/><text x=\"288.8\" y=\"198\" fill=\"#7A8699\" font-size=\"11\" text-anchor=\"middle\">50<\/text><line x1=\"381.6\" y1=\"14\" x2=\"381.6\" y2=\"181.0\" stroke=\"#E7ECF4\" stroke-width=\"1\"\/><text x=\"381.6\" y=\"198\" fill=\"#7A8699\" font-size=\"11\" text-anchor=\"middle\">100<\/text><line x1=\"474.4\" y1=\"14\" x2=\"474.4\" y2=\"181.0\" stroke=\"#E7ECF4\" stroke-width=\"1\"\/><text x=\"474.4\" y=\"198\" fill=\"#7A8699\" font-size=\"11\" text-anchor=\"middle\">150<\/text><line x1=\"567.2\" y1=\"14\" x2=\"567.2\" y2=\"181.0\" stroke=\"#E7ECF4\" stroke-width=\"1\"\/><text x=\"567.2\" y=\"198\" fill=\"#7A8699\" font-size=\"11\" text-anchor=\"middle\">200<\/text><line x1=\"660.0\" y1=\"14\" x2=\"660.0\" y2=\"181.0\" stroke=\"#E7ECF4\" stroke-width=\"1\"\/><text x=\"660.0\" y=\"198\" fill=\"#7A8699\" font-size=\"11\" text-anchor=\"middle\">250<\/text><line x1=\"196\" y1=\"181\" x2=\"660\" y2=\"181\" stroke=\"#D3DBE6\" stroke-width=\"1\"\/><text x=\"184\" y=\"31.0\" fill=\"#16223A\" font-size=\"12.5\" text-anchor=\"end\" dominant-baseline=\"middle\">GPT-5.6 Luna<\/text><rect x=\"196\" y=\"16\" width=\"368.8\" height=\"30\" rx=\"5\" fill=\"#10A37F\"\/><text x=\"572.8\" y=\"31.0\" fill=\"#16223A\" font-size=\"12.5\" font-weight=\"700\" dominant-baseline=\"middle\">198,7<\/text><text x=\"184\" y=\"76.0\" fill=\"#16223A\" font-size=\"12.5\" text-anchor=\"end\" dominant-baseline=\"middle\">Gemini 3.1 Pro<\/text><rect x=\"196\" y=\"61\" width=\"203.2\" height=\"30\" rx=\"5\" fill=\"#3B82F6\"\/><text x=\"407.2\" y=\"76.0\" fill=\"#16223A\" font-size=\"12.5\" font-weight=\"700\" dominant-baseline=\"middle\">109,5<\/text><text x=\"184\" y=\"121.0\" fill=\"#16223A\" font-size=\"12.5\" text-anchor=\"end\" dominant-baseline=\"middle\">Grok 4.5<\/text><rect x=\"196\" y=\"106\" width=\"190.6\" height=\"30\" rx=\"5\" fill=\"#475569\"\/><text x=\"394.6\" y=\"121.0\" fill=\"#16223A\" font-size=\"12.5\" font-weight=\"700\" dominant-baseline=\"middle\">102,7<\/text><text x=\"184\" y=\"166.0\" fill=\"#16223A\" font-size=\"12.5\" text-anchor=\"end\" dominant-baseline=\"middle\">Kimi K3<\/text><rect x=\"196\" y=\"151\" width=\"115.1\" height=\"30\" rx=\"5\" fill=\"#6B7280\"\/><text x=\"319.1\" y=\"166.0\" fill=\"#16223A\" font-size=\"12.5\" font-weight=\"700\" dominant-baseline=\"middle\">62<\/text><text x=\"428.0\" y=\"219\" fill=\"#5E6C82\" font-size=\"12\" text-anchor=\"middle\">tokens por segundo<\/text><\/svg><\/div>\n<p class=\"hint\">Los modelos \u201cFlash\/Haiku\u201d y los de difusi\u00f3n (p. ej. Mercury, ~747 t\/s) son a\u00fan m\u00e1s r\u00e1pidos. Los modelos de razonamiento como Claude Opus priorizan calidad sobre velocidad.<\/p>\n<p class=\"src\">Fuente: <a href=\"https:\/\/artificialanalysis.ai\/models\" target=\"_blank\" rel=\"noopener\">Artificial Analysis<\/a>, julio 2026.<\/p>\n<\/p><\/div>\n<p>  <!-- ===================== CONTEXTO ===================== --><\/p>\n<h2>Contexto: documentos largos y expedientes completos<\/h2>\n<p>La \u201cventana de contexto\u201d es cu\u00e1nto texto puede procesar el modelo de una sola vez. \u00datil para analizar contratos extensos, expedientes o bases de conocimiento enteras sin trocearlas. En 2026 la mayor\u00eda de buques insignia ya ofrecen <strong>1 mill\u00f3n de tokens<\/strong> (unas 750.000 palabras); algunos van mucho m\u00e1s all\u00e1.<\/p>\n<div class=\"card\">\n    <span class=\"eyebrow\">Gr\u00e1fico 6 \u00b7 Ventana de contexto<\/span><\/p>\n<h3>Cu\u00e1nto texto \u201clee\u201d cada modelo de una vez<\/h3>\n<p class=\"sub\">Tokens de entrada. Escala logar\u00edtmica (cada marca \u00d710).<\/p>\n<div class=\"chartsvg\"><svg viewBox=\"0 0 720 407\" width=\"720\" height=\"407\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" font-family=\"'Inter',system-ui,-apple-system,Segoe UI,Arial,sans-serif\"><line x1=\"196.0\" y1=\"14\" x2=\"196.0\" y2=\"361.0\" stroke=\"#E7ECF4\" stroke-width=\"1\"\/><text x=\"196.0\" y=\"378\" fill=\"#7A8699\" font-size=\"11\" text-anchor=\"middle\">100K<\/text><line x1=\"426.0\" y1=\"14\" x2=\"426.0\" y2=\"361.0\" stroke=\"#E7ECF4\" stroke-width=\"1\"\/><text x=\"426.0\" y=\"378\" fill=\"#7A8699\" font-size=\"11\" text-anchor=\"middle\">1M<\/text><line x1=\"656.0\" y1=\"14\" x2=\"656.0\" y2=\"361.0\" stroke=\"#E7ECF4\" stroke-width=\"1\"\/><text x=\"656.0\" y=\"378\" fill=\"#7A8699\" font-size=\"11\" text-anchor=\"middle\">10M<\/text><line x1=\"196\" y1=\"361\" x2=\"656\" y2=\"361\" stroke=\"#D3DBE6\" stroke-width=\"1\"\/><text x=\"184\" y=\"31.0\" fill=\"#16223A\" font-size=\"12.5\" text-anchor=\"end\" dominant-baseline=\"middle\">Llama 4 Scout (open)<\/text><rect x=\"196\" y=\"16\" width=\"460.0\" height=\"30\" rx=\"5\" fill=\"#EA580C\"\/><text x=\"664.0\" y=\"31.0\" fill=\"#16223A\" font-size=\"12.5\" font-weight=\"700\" dominant-baseline=\"middle\">10M<\/text><text x=\"184\" y=\"76.0\" fill=\"#16223A\" font-size=\"12.5\" text-anchor=\"end\" dominant-baseline=\"middle\">Grok 4.5<\/text><rect x=\"196\" y=\"61\" width=\"299.2\" height=\"30\" rx=\"5\" fill=\"#475569\"\/><text x=\"503.2\" y=\"76.0\" fill=\"#16223A\" font-size=\"12.5\" font-weight=\"700\" dominant-baseline=\"middle\">2M<\/text><text x=\"184\" y=\"121.0\" fill=\"#16223A\" font-size=\"12.5\" text-anchor=\"end\" dominant-baseline=\"middle\">Gemini 3.1 Pro<\/text><rect x=\"196\" y=\"106\" width=\"230.0\" height=\"30\" rx=\"5\" fill=\"#3B82F6\"\/><text x=\"434.0\" y=\"121.0\" fill=\"#16223A\" font-size=\"12.5\" font-weight=\"700\" dominant-baseline=\"middle\">1M<\/text><text x=\"184\" y=\"166.0\" fill=\"#16223A\" font-size=\"12.5\" text-anchor=\"end\" dominant-baseline=\"middle\">Claude Opus 4.8<\/text><rect x=\"196\" y=\"151\" width=\"230.0\" height=\"30\" rx=\"5\" fill=\"#D97757\"\/><text x=\"434.0\" y=\"166.0\" fill=\"#16223A\" font-size=\"12.5\" font-weight=\"700\" dominant-baseline=\"middle\">1M<\/text><text x=\"184\" y=\"211.0\" fill=\"#16223A\" font-size=\"12.5\" text-anchor=\"end\" dominant-baseline=\"middle\">GPT-5.6<\/text><rect x=\"196\" y=\"196\" width=\"230.0\" height=\"30\" rx=\"5\" fill=\"#10A37F\"\/><text x=\"434.0\" y=\"211.0\" fill=\"#16223A\" font-size=\"12.5\" font-weight=\"700\" dominant-baseline=\"middle\">1M<\/text><text x=\"184\" y=\"256.0\" fill=\"#16223A\" font-size=\"12.5\" text-anchor=\"end\" dominant-baseline=\"middle\">DeepSeek V4<\/text><rect x=\"196\" y=\"241\" width=\"230.0\" height=\"30\" rx=\"5\" fill=\"#7C3AED\"\/><text x=\"434.0\" y=\"256.0\" fill=\"#16223A\" font-size=\"12.5\" font-weight=\"700\" dominant-baseline=\"middle\">1M<\/text><text x=\"184\" y=\"301.0\" fill=\"#16223A\" font-size=\"12.5\" text-anchor=\"end\" dominant-baseline=\"middle\">Kimi K2.6 (open)<\/text><rect x=\"196\" y=\"286\" width=\"96.3\" height=\"30\" rx=\"5\" fill=\"#6B7280\"\/><text x=\"300.3\" y=\"301.0\" fill=\"#16223A\" font-size=\"12.5\" font-weight=\"700\" dominant-baseline=\"middle\">262K<\/text><text x=\"184\" y=\"346.0\" fill=\"#16223A\" font-size=\"12.5\" text-anchor=\"end\" dominant-baseline=\"middle\">Claude Haiku 4.5<\/text><rect x=\"196\" y=\"331\" width=\"69.2\" height=\"30\" rx=\"5\" fill=\"#D97757\"\/><text x=\"273.2\" y=\"346.0\" fill=\"#16223A\" font-size=\"12.5\" font-weight=\"700\" dominant-baseline=\"middle\">200K<\/text><text x=\"426.0\" y=\"399\" fill=\"#5E6C82\" font-size=\"12\" text-anchor=\"middle\">tokens (escala logar\u00edtmica)<\/text><\/svg><\/div>\n<p class=\"hint\">1M de tokens \u2248 750.000 palabras \u2248 1.500 p\u00e1ginas. Para la mayor\u00eda de casos de negocio, 1M es m\u00e1s que suficiente.<\/p>\n<p class=\"src\">Fuente: documentaci\u00f3n de cada proveedor y <a href=\"https:\/\/llm-stats.com\" target=\"_blank\" rel=\"noopener\">LLM Stats<\/a>, julio 2026.<\/p>\n<\/p><\/div>\n<p>  <!-- ===================== MULTIMODAL ===================== --><\/p>\n<h2>Multimodal: im\u00e1genes, v\u00eddeo, audio y documentos<\/h2>\n<p>El caso de negocio m\u00e1s valioso hoy es <strong>extraer datos estructurados de documentos<\/strong>: facturas, contratos, formularios o tickets. Los modelos de visi\u00f3n entienden el documento completo (saben que el n\u00famero junto a \u201cTotal\u201d es el importe), no solo transcriben texto. En 2026, la prueba est\u00e1ndar (MMMU-Pro) tambi\u00e9n est\u00e1 saturada: todos los grandes superan el 80 %. Las diferencias reales aparecen en los ejes finos:<\/p>\n<div class=\"note\">\n    <b>V\u00eddeo y audio \u2192<\/b> Gemini 3.1 Pro domina con claridad. &nbsp;\u00b7&nbsp;<br \/>\n    <b>Gr\u00e1ficas, infograf\u00edas y \u201cc\u00f3digo + imagen\u201d \u2192<\/b> GPT-5.6. &nbsp;\u00b7&nbsp;<br \/>\n    <b>OCR de documentos largos y complejos \u2192<\/b> Claude. &nbsp;\u00b7&nbsp;<br \/>\n    <b>Open source con buen OCR multiling\u00fce \u2192<\/b> Qwen VL.\n  <\/div>\n<p>  <!-- ===================== MATRIZ DE DECISI\u00d3N ===================== --><\/p>\n<h2>Qu\u00e9 modelo para qu\u00e9 tarea<\/h2>\n<p>Esta es la tabla que puedes imprimir y pegar en la pared. Para cada tarea de negocio, el modelo recomendado, una alternativa s\u00f3lida y una opci\u00f3n econ\u00f3mica. El punto de color indica la familia del modelo recomendado.<\/p>\n<div class=\"tablewrap\">\n<table>\n<thead>\n<tr>\n<th>Tarea de negocio<\/th>\n<th>Recomendado<\/th>\n<th>Alternativa s\u00f3lida<\/th>\n<th>Opci\u00f3n econ\u00f3mica<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Redacci\u00f3n, marketing y contenidos<\/td>\n<td class=\"m\"><span class=\"dot\" style=\"background:var(--gpt)\"><\/span>GPT-5.6 \/ Claude<\/td>\n<td>Gemini 3.1 Pro<\/td>\n<td>Gemini Flash \u00b7 DeepSeek<\/td>\n<\/tr>\n<tr>\n<td>Programaci\u00f3n y herramientas internas<\/td>\n<td class=\"m\"><span class=\"dot\" style=\"background:var(--cla)\"><\/span>Claude Opus 4.8<\/td>\n<td>GPT-5.6<\/td>\n<td>GLM-5.2 \u00b7 DeepSeek <em>(open)<\/em><\/td>\n<\/tr>\n<tr>\n<td>An\u00e1lisis de datos y hojas de c\u00e1lculo<\/td>\n<td class=\"m\"><span class=\"dot\" style=\"background:var(--gpt)\"><\/span>GPT-5.6 <em>(int\u00e9rprete de c\u00f3digo)<\/em><\/td>\n<td>Gemini 3.1 Pro<\/td>\n<td>DeepSeek<\/td>\n<\/tr>\n<tr>\n<td>Razonamiento complejo e investigaci\u00f3n<\/td>\n<td class=\"m\"><span class=\"dot\" style=\"background:var(--gpt)\"><\/span>GPT-5.6<\/td>\n<td>Gemini 3.1 Pro \u00b7 Grok 4.5<\/td>\n<td>GLM-5.2 <em>(open)<\/em><\/td>\n<\/tr>\n<tr>\n<td>Documentos muy largos (contratos, expedientes)<\/td>\n<td class=\"m\"><span class=\"dot\" style=\"background:var(--gem)\"><\/span>Gemini 3.1 Pro<\/td>\n<td>Grok 4.5 <em>(2M)<\/em><\/td>\n<td>Claude <em>(1M)<\/em><\/td>\n<\/tr>\n<tr>\n<td>Multimodal: im\u00e1genes, v\u00eddeo y audio<\/td>\n<td class=\"m\"><span class=\"dot\" style=\"background:var(--gem)\"><\/span>Gemini 3.1 Pro<\/td>\n<td>GPT-5.6<\/td>\n<td>Qwen VL <em>(open)<\/em><\/td>\n<\/tr>\n<tr>\n<td>Extracci\u00f3n de datos de facturas y documentos<\/td>\n<td class=\"m\"><span class=\"dot\" style=\"background:var(--gem)\"><\/span>Gemini \/ Claude<\/td>\n<td>GPT-5.6<\/td>\n<td>Qwen VL <em>(open)<\/em><\/td>\n<\/tr>\n<tr>\n<td>Atenci\u00f3n al cliente \/ alto volumen<\/td>\n<td class=\"m\"><span class=\"dot\" style=\"background:var(--gem)\"><\/span>Gemini Flash \u00b7 Claude Haiku<\/td>\n<td>GPT-5.6 Luna<\/td>\n<td>DeepSeek<\/td>\n<\/tr>\n<tr>\n<td>Traducci\u00f3n y multiling\u00fce<\/td>\n<td class=\"m\"><span class=\"dot\" style=\"background:var(--gem)\"><\/span>Gemini 3.1 Pro<\/td>\n<td>GPT-5.6<\/td>\n<td>Qwen \u00b7 DeepSeek<\/td>\n<\/tr>\n<tr>\n<td>Datos sensibles \/ on-premise (privacidad)<\/td>\n<td class=\"m\"><span class=\"dot\" style=\"background:var(--open)\"><\/span>Llama 4 \u00b7 Qwen 3.5 <em>(open)<\/em><\/td>\n<td>GLM-5.2<\/td>\n<td>Mistral \u00b7 Gemma<\/td>\n<\/tr>\n<tr>\n<td>B\u00fasqueda con IA \/ informaci\u00f3n en tiempo real<\/td>\n<td class=\"m\"><span class=\"dot\" style=\"background:var(--grok)\"><\/span>Grok 4.5 \u00b7 Perplexity<\/td>\n<td>Gemini<\/td>\n<td>ChatGPT (b\u00fasqueda)<\/td>\n<\/tr>\n<\/tbody>\n<\/table><\/div>\n<p>  <!-- ===================== POR PRESUPUESTO ===================== --><\/p>\n<h2>Elige por presupuesto<\/h2>\n<div class=\"cards3\">\n<div class=\"tier t1\">\n      <span class=\"tag\">Coste ajustado<\/span><\/p>\n<h3>M\u00e1ximo ahorro<\/h3>\n<p class=\"lead\">DeepSeek \u00b7 Gemini Flash \u00b7 Claude Haiku \u00b7 GPT-5.6 Luna \u00b7 open source<\/p>\n<p>Para volumen y tareas sencillas (res\u00famenes, clasificaci\u00f3n, borradores, atenci\u00f3n de primer nivel). Hacen el grueso del trabajo por c\u00e9ntimos.<\/p>\n<\/p><\/div>\n<div class=\"tier t2\">\n      <span class=\"tag\">Punto dulce<\/span><\/p>\n<h3>Calidad-precio<\/h3>\n<p class=\"lead\">Claude Sonnet 5 \u00b7 Gemini 3.1 Pro \u00b7 GPT-5.6 (gama media)<\/p>\n<p>El equilibrio ideal para el d\u00eda a d\u00eda: calidad alta a coste razonable. La opci\u00f3n por defecto para la mayor\u00eda de pymes.<\/p>\n<\/p><\/div>\n<div class=\"tier t3\">\n      <span class=\"tag\">Sin techo<\/span><\/p>\n<h3>M\u00e1xima capacidad<\/h3>\n<p class=\"lead\">Claude Opus 4.8 \u00b7 GPT-5.6 (m\u00e1x.) \u00b7 Gemini 3.1 Pro<\/p>\n<p>Para trabajo cr\u00edtico y ag\u00e9ntico: desarrollo complejo, an\u00e1lisis de alto valor, procesos donde un error sale caro. Reserva su coste para lo que lo justifica.<\/p>\n<\/p><\/div>\n<\/p><\/div>\n<p>  <!-- ===================== FRAMEWORK ===================== --><\/p>\n<h2>5 preguntas para elegir bien<\/h2>\n<div class=\"qa\">\n<div class=\"row\">\n<div class=\"n\">1<\/div>\n<div>\n<div class=\"q\">\u00bfQu\u00e9 tarea concreta vas a resolver?<\/div>\n<div class=\"a\">Programar, redactar, analizar datos, atender clientes\u2026 Empieza por la tarea, no por el modelo.<\/div>\n<\/div>\n<\/div>\n<div class=\"row\">\n<div class=\"n\">2<\/div>\n<div>\n<div class=\"q\">\u00bfQu\u00e9 volumen tendr\u00e1s?<\/div>\n<div class=\"a\">Miles de peticiones al d\u00eda empujan hacia un modelo barato y r\u00e1pido; unas pocas de alto valor justifican el buque insignia.<\/div>\n<\/div>\n<\/div>\n<div class=\"row\">\n<div class=\"n\">3<\/div>\n<div>\n<div class=\"q\">\u00bfC\u00f3mo de sensibles son tus datos?<\/div>\n<div class=\"a\">Si no pueden salir de tu infraestructura (RGPD, secreto comercial), mira modelos open source autoalojados.<\/div>\n<\/div>\n<\/div>\n<div class=\"row\">\n<div class=\"n\">4<\/div>\n<div>\n<div class=\"q\">\u00bfNecesitas imagen, v\u00eddeo o audio?<\/div>\n<div class=\"a\">Si es as\u00ed, el multimodal manda y Gemini o GPT toman ventaja sobre alternativas solo-texto.<\/div>\n<\/div>\n<\/div>\n<div class=\"row\">\n<div class=\"n\">5<\/div>\n<div>\n<div class=\"q\">\u00bfQu\u00e9 integraci\u00f3n tienes ya?<\/div>\n<div class=\"a\">Google Workspace, Microsoft 365 o tu ERP condicionan la elecci\u00f3n tanto como el benchmark. Aprovecha lo que ya usas.<\/div>\n<\/div>\n<\/div><\/div>\n<p>  <!-- ===================== CAVEATS ===================== --><\/p>\n<h2>Lo que los benchmarks no te cuentan<\/h2>\n<p><strong>El coste real es por tarea, no por token.<\/strong> Un modelo caro que resuelve un problema a la primera puede salir m\u00e1s barato que uno econ\u00f3mico que necesita cinco intentos y supervisi\u00f3n humana. Mide el coste de completar la tarea, no el precio de la etiqueta.<\/p>\n<p><strong>La privacidad no es un extra.<\/strong> Antes de enviar datos de clientes a una API externa, revisa el encaje con el RGPD, d\u00f3nde se procesan los datos y qu\u00e9 acuerdo de tratamiento ofrece el proveedor. Para lo m\u00e1s sensible, el open source autoalojado es a menudo la respuesta correcta.<\/p>\n<p><strong>Todo cambia r\u00e1pido.<\/strong> Los nombres, versiones y precios de esta gu\u00eda son de julio de 2026 y quedar\u00e1n desactualizados. La estrategia no: <em>emparejar cada tarea con el modelo adecuado<\/em> seguir\u00e1 siendo v\u00e1lida aunque cambien los protagonistas.<\/p>\n<h2>Conclusi\u00f3n<\/h2>\n<p>La pregunta \u201c\u00bfcu\u00e1l es el mejor modelo de IA?\u201d tiene una respuesta inc\u00f3moda para los titulares y muy c\u00f3moda para tu cuenta de resultados: <strong>depende de la tarea<\/strong>. Los l\u00edderes est\u00e1n tan igualados que la ventaja competitiva ya no est\u00e1 en usar \u201cel m\u00e1s potente\u201d, sino en <strong>orquestar varios modelos con criterio<\/strong>: el potente para lo cr\u00edtico, el econ\u00f3mico para el volumen, el open source para lo sensible. Ese es el trabajo que separa a quien \u201cusa IA\u201d de quien obtiene retorno de ella.<\/p>\n<p>  <!-- ===================== CTA ===================== --><\/p>\n<div class=\"cta\">\n    <span class=\"eyebrow\" style=\"color:#B8730C\">myIA \u00b7 MyExpertServices<\/span><\/p>\n<h2>\u00bfNo sabes por d\u00f3nde empezar?<\/h2>\n<p>En <strong>myIA<\/strong> no vendemos \u201cun modelo\u201d: priorizamos tus casos de uso por retorno, elegimos la herramienta adecuada a cada uno, los ponemos en producci\u00f3n en semanas y formamos a tu equipo para que los adopte de verdad. Sin dependencias de un \u00fanico proveedor.<\/p>\n<p>    <a class=\"btn\" href=\"https:\/\/www.myexpertservices.com\/myIA\/\" target=\"_blank\" rel=\"noopener\">Descubre myIA \u2192<\/a><br \/>\n    &nbsp;&nbsp;<br \/>\n    <a class=\"btn\" style=\"background:transparent !important;color:#16223A !important;border:2px solid #16223A !important\" href=\"https:\/\/www.myexpertservices.com\/calculadora-roi-ia\/\" target=\"_blank\" rel=\"noopener\">Calcula tu ROI de IA<\/a>\n  <\/div>\n<p>  <!-- ===================== FUENTES ===================== --><\/p>\n<h2>Fuentes<\/h2>\n<ol class=\"src-list\">\n<li>Artificial Analysis \u2014 Intelligence Index, velocidad y precios: <a href=\"https:\/\/artificialanalysis.ai\/models\" target=\"_blank\" rel=\"noopener\">artificialanalysis.ai\/models<\/a><\/li>\n<li>LMArena (antes LMSYS Chatbot Arena) \u2014 preferencia humana ciega: <a href=\"https:\/\/lmarena.ai\" target=\"_blank\" rel=\"noopener\">lmarena.ai<\/a><\/li>\n<li>SWE-bench Pro \u2014 leaderboard de programaci\u00f3n (2026): <a href=\"https:\/\/codingfleet.com\/blog\/swe-bench-pro-leaderboard-2026\/\" target=\"_blank\" rel=\"noopener\">codingfleet.com<\/a> \u00b7 <a href=\"https:\/\/www.morphllm.com\/swe-bench-pro\" target=\"_blank\" rel=\"noopener\">morphllm.com<\/a><\/li>\n<li>SWE-bench Verified \u2014 Vals AI: <a href=\"https:\/\/www.vals.ai\/benchmarks\/swebench\" target=\"_blank\" rel=\"noopener\">vals.ai\/benchmarks\/swebench<\/a><\/li>\n<li>Benchmarks multimodales 2026 (v\u00eddeo, audio, gr\u00e1ficas): <a href=\"https:\/\/www.digitalapplied.com\/blog\/multimodal-ai-benchmarks-2026-vision-audio-code\" target=\"_blank\" rel=\"noopener\">digitalapplied.com<\/a> \u00b7 <a href=\"https:\/\/blog.roboflow.com\/best-multimodal-models\/\" target=\"_blank\" rel=\"noopener\">Roboflow<\/a><\/li>\n<li>Precios oficiales \u2014 Anthropic: <a href=\"https:\/\/www.anthropic.com\/pricing\" target=\"_blank\" rel=\"noopener\">anthropic.com\/pricing<\/a><\/li>\n<li>Comparativa de precios de APIs (Grok, Gemini, GPT, Claude): <a href=\"https:\/\/intuitionlabs.ai\/articles\/ai-api-pricing-comparison-grok-gemini-openai-claude\" target=\"_blank\" rel=\"noopener\">intuitionlabs.ai<\/a><\/li>\n<li>LLM Stats \u2014 ranking por inteligencia, velocidad y precio: <a href=\"https:\/\/llm-stats.com\" target=\"_blank\" rel=\"noopener\">llm-stats.com<\/a><\/li>\n<li>DataLearner \u2014 leaderboard en vivo (AA Index + LMArena): <a href=\"https:\/\/www.datalearner.com\/en\/leaderboards\" target=\"_blank\" rel=\"noopener\">datalearner.com<\/a><\/li>\n<li>EdenAI \u2014 Claude Sonnet 5 vs GPT-5.6 vs Gemini 3.1 (precios y contexto): <a href=\"https:\/\/www.edenai.co\/post\/claude-sonnet-5-vs-gpt-5-6-sol-vs-gemini-3-1-benchmarks-pricing-which-to-use\" target=\"_blank\" rel=\"noopener\">edenai.co<\/a><\/li>\n<\/ol>\n<p class=\"fine\">\u00daltima actualizaci\u00f3n: julio de 2026. Los modelos, versiones y precios de IA cambian con gran rapidez; verifica los datos en las fuentes oficiales antes de tomar decisiones. Esta gu\u00eda tiene fines informativos y no constituye asesoramiento contractual ni financiero. Elaborado por MyExpertServices con datos de terceros independientes.<\/p>\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>Inteligencia artificial \u00b7 Gu\u00eda pr\u00e1ctica Una comparativa objetiva y sin favoritismos de los grandes modelos de 2026 \u2014GPT, Gemini, Claude, Grok, DeepSeek y las opciones open source\u2014 para&#8230;<\/p>\n","protected":false},"author":1,"featured_media":28,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-27","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized"],"_links":{"self":[{"href":"https:\/\/myexpertservices.com\/blog\/wp-json\/wp\/v2\/posts\/27","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/myexpertservices.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/myexpertservices.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/myexpertservices.com\/blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/myexpertservices.com\/blog\/wp-json\/wp\/v2\/comments?post=27"}],"version-history":[{"count":9,"href":"https:\/\/myexpertservices.com\/blog\/wp-json\/wp\/v2\/posts\/27\/revisions"}],"predecessor-version":[{"id":39,"href":"https:\/\/myexpertservices.com\/blog\/wp-json\/wp\/v2\/posts\/27\/revisions\/39"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/myexpertservices.com\/blog\/wp-json\/wp\/v2\/media\/28"}],"wp:attachment":[{"href":"https:\/\/myexpertservices.com\/blog\/wp-json\/wp\/v2\/media?parent=27"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/myexpertservices.com\/blog\/wp-json\/wp\/v2\/categories?post=27"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/myexpertservices.com\/blog\/wp-json\/wp\/v2\/tags?post=27"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}