{"id":1246,"date":"2026-06-22T17:39:20","date_gmt":"2026-06-22T17:39:20","guid":{"rendered":"https:\/\/convly.ai\/ai-price-performance-index-2026\/"},"modified":"2026-08-01T06:46:23","modified_gmt":"2026-08-01T06:46:23","slug":"ai-price-performance-index-2026","status":"publish","type":"post","link":"https:\/\/convly.ai\/es\/ai-price-performance-index-2026\/","title":{"rendered":"\u00cdndice de relaci\u00f3n precio-rendimiento en IA 2026: \u00bfqu\u00e9 modelo te ofrece m\u00e1s inteligencia por d\u00f3lar?"},"content":{"rendered":"<p><!--ppi-hero--><\/p>\n<style>\n.ppi-hero{background:linear-gradient(135deg,#0b1220,#16213e);color:#eef2ff;border-radius:14px;padding:28px 26px;margin:0 0 26px}\n.ppi-eyebrow{font-size:12px;letter-spacing:.14em;text-transform:uppercase;color:#8ea2ff!important;margin:0 0 8px;font-weight:700}\n.ppi-headline{font-size:30px;line-height:1.2;margin:0 0 10px;color:#fff!important;font-weight:800}\n.ppi-sub{font-size:16px;line-height:1.55;color:#c7d2fe!important;margin:0 0 20px;max-width:70ch}\n.ppi-stats{display:flex;flex-wrap:wrap;gap:14px;margin:0}\n.ppi-stat{flex:1 1 170px;background:rgba(255,255,255,.06);border:1px solid rgba(255,255,255,.12);border-radius:10px;padding:14px 16px}\n.ppi-num{display:block;font-size:34px;font-weight:800;color:#7bffb0;line-height:1}\n.ppi-stat.b .ppi-num{color:#ffd08a}.ppi-stat.c .ppi-num{color:#8ec5ff}\n.ppi-lab{display:block;font-size:13px;color:#c7d2fe!important;margin-top:6px;line-height:1.35}\n.ppi-chart{overflow-x:auto;margin:24px 0;background:#f8f9fb;border:1px solid #e6e8ef;border-radius:12px;padding:16px}\n.ppi-chart figcaption{font-size:12px;color:#667788;margin-top:8px;text-align:center}\n.ppi-box{border:1px solid #e6e8ef;border-left:4px solid #4263eb;background:#f8f9fb;border-radius:10px;padding:18px 20px;margin:22px 0}\n.ppi-box h2{margin:0 0 10px;font-size:20px}\n.ppi-box blockquote{margin:10px 0;padding:10px 14px;background:#fff;border:1px solid #e6e8ef;border-radius:8px;font-size:14px;color:#334455}\n@media (max-width:600px){.ppi-headline{font-size:23px}.ppi-num{font-size:28px}}\n<\/style>\n<div class=\"ppi-hero\">\n<p class=\"ppi-eyebrow\">Convly Original Study \u00b7 Updated 2026<\/p>\n<div class=\"ppi-headline\">The Price of Intelligence: a 114\u00d7 cost spread across AI models<\/div>\n<p class=\"ppi-sub\">We cross-referenced live API pricing for 30 leading AI models with the independent Artificial Analysis Intelligence Index to answer one question \u2014 which model gives you the most intelligence per dollar? The answer overturns &#8220;you get what you pay for.&#8221;<\/p>\n<div class=\"ppi-stats\">\n<div class=\"ppi-stat a\"><span class=\"ppi-num\">114\u00d7<\/span><span class=\"ppi-lab\">blended-cost spread \u2014 $0.18 to $20 per 1M tokens<\/span><\/div>\n<div class=\"ppi-stat b\"><span class=\"ppi-num\">37\u00d7<\/span><span class=\"ppi-lab\">more intelligence per dollar: DeepSeek V4-Flash vs Claude Opus 4.8<\/span><\/div>\n<div class=\"ppi-stat c\"><span class=\"ppi-num\">~1.8%<\/span><span class=\"ppi-lab\">of Opus&#8217;s cost buys ~67% of its measured intelligence<\/span><\/div>\n<\/p><\/div>\n<\/div>\n<figure class=\"ppi-chart\">\n<svg viewbox=\"0 0 760 360\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" role=\"img\" aria-label=\"Blended API cost per 1M tokens across nine AI models, ranging from $0.18 to $20 \u2014 a 114x spread\" style=\"width:100%;height:auto;min-width:520px\">\n <text x=\"10\" y=\"22\" font-family=\"system-ui,Arial\" font-size=\"16\" font-weight=\"700\" fill=\"#1a1a2e\">Blended API cost per 1M tokens \u2014 a 114\u00d7 spread (2026)<\/text>\n <g font-family=\"system-ui,Arial\" font-size=\"13\" fill=\"#333\">\n <g><text x=\"160\" y=\"63\" text-anchor=\"end\">DeepSeek V4-Flash<\/text><rect x=\"170\" y=\"50\" width=\"6\" height=\"20\" rx=\"3\" fill=\"#2f9e44\"\/><text x=\"184\" y=\"64\" font-size=\"12\" font-weight=\"700\" fill=\"#2f9e44\">$0.18<\/text><\/g>\n <g><text x=\"160\" y=\"95\" text-anchor=\"end\">DeepSeek V4-Pro<\/text><rect x=\"170\" y=\"82\" width=\"15\" height=\"20\" rx=\"3\" fill=\"#4263eb\"\/><text x=\"191\" y=\"96\" font-size=\"12\" fill=\"#555\">$0.54<\/text><\/g>\n <g><text x=\"160\" y=\"127\" text-anchor=\"end\">Claude Haiku 4.5<\/text><rect x=\"170\" y=\"114\" width=\"56\" height=\"20\" rx=\"3\" fill=\"#4263eb\"\/><text x=\"232\" y=\"128\" font-size=\"12\" fill=\"#555\">$2.00<\/text><\/g>\n <g><text x=\"160\" y=\"159\" text-anchor=\"end\">Gemini 3.5 Flash<\/text><rect x=\"170\" y=\"146\" width=\"95\" height=\"20\" rx=\"3\" fill=\"#4263eb\"\/><text x=\"271\" y=\"160\" font-size=\"12\" fill=\"#555\">$3.38<\/text><\/g>\n <g><text x=\"160\" y=\"191\" text-anchor=\"end\">Gemini 3.1 Pro<\/text><rect x=\"170\" y=\"178\" width=\"126\" height=\"20\" rx=\"3\" fill=\"#4263eb\"\/><text x=\"302\" y=\"192\" font-size=\"12\" fill=\"#555\">$4.50<\/text><\/g>\n <g><text x=\"160\" y=\"223\" text-anchor=\"end\">Claude Sonnet 4.6<\/text><rect x=\"170\" y=\"210\" width=\"168\" height=\"20\" rx=\"3\" fill=\"#4263eb\"\/><text x=\"344\" y=\"224\" font-size=\"12\" fill=\"#555\">$6.00<\/text><\/g>\n <g><text x=\"160\" y=\"255\" text-anchor=\"end\">Claude Opus 4.8<\/text><rect x=\"170\" y=\"242\" width=\"280\" height=\"20\" rx=\"3\" fill=\"#4263eb\"\/><text x=\"456\" y=\"256\" font-size=\"12\" fill=\"#555\">$10.00<\/text><\/g>\n <g><text x=\"160\" y=\"287\" text-anchor=\"end\">GPT-5.5<\/text><rect x=\"170\" y=\"274\" width=\"315\" height=\"20\" rx=\"3\" fill=\"#4263eb\"\/><text x=\"491\" y=\"288\" font-size=\"12\" fill=\"#555\">$11.25<\/text><\/g>\n <g><text x=\"160\" y=\"319\" text-anchor=\"end\">Claude Fable 5<\/text><rect x=\"170\" y=\"306\" width=\"560\" height=\"20\" rx=\"3\" fill=\"#e8590c\"\/><text x=\"700\" y=\"320\" font-size=\"12\" font-weight=\"700\" fill=\"#fff\" text-anchor=\"end\">$20.00<\/text><\/g>\n <\/g>\n<\/svg><figcaption>Blended cost = (3 \u00d7 input + output) \u00f7 4, a 3:1 input-to-output ratio typical of real API traffic. Source: Convly AI models database. Green = best value, orange = most expensive.<\/figcaption><\/figure>\n<p>Los precios de los modelos de IA en 2026 abarcan un rango asombroso; sin embargo, el modelo m\u00e1s caro no es ni mucho menos 100 veces m\u00e1s inteligente que el m\u00e1s econ\u00f3mico. Combinamos los precios en tiempo real de nuestra <a href=\"\/es\/models\/\">Base de datos de modelos de IA<\/a> con el \u00edndice independiente <strong>\u00cdndice de Inteligencia Artificial de Artificial Analysis<\/strong> para responder una \u00fanica pregunta: <strong>\u00bfqu\u00e9 modelo te ofrece m\u00e1s inteligencia por d\u00f3lar?<\/strong> La respuesta cuestiona la suposici\u00f3n de que lo que pagas es lo que obtienes.<\/p>\n<div class=\"convly-tldr\">\n<h3>Conclusiones clave<\/h3>\n<ul>\n<li><strong>Diferencia de precios de 114\u00d7.<\/strong> En t\u00e9rminos de costo combinado, los modelos punteros disponibles mediante API oscilan entre aproximadamente 0,18 $ y 20 $ por mill\u00f3n de tokens.<\/li>\n<li><strong>Valor \u2260 precio.<\/strong> Los modelos capaces m\u00e1s econ\u00f3micos ofrecen <strong>de 30 a 40 veces m\u00e1s inteligencia por d\u00f3lar<\/strong> que los modelos punteros m\u00e1s caros.<\/li>\n<li><strong>DeepSeek V4-Flash<\/strong> ofrece aproximadamente <strong>el 67 % de la inteligencia medida de Claude Opus 4.8 alrededor del 1,8 % de su costo.<\/strong><\/li>\n<li>Pagar el precio m\u00e1s alto adquiere solo <em>los \u00faltimos puntos<\/em> de capacidad, no una inteligencia proporcional.<\/li>\n<li>Para la mayor\u00eda de las cargas de trabajo, un modelo de gama media o de c\u00f3digo abierto es la opci\u00f3n racional por defecto; reserva los modelos punteros para las tareas m\u00e1s exigentes.<\/li>\n<\/ul>\n<\/div>\n<div class=\"convly-tldr ppi-k3-update\">\n<h3>Update \u2014 July 2026: an open model now tops the table<\/h3>\n<p>Since this study went live, Moonshot released <a href=\"\/es\/kimi-k3-explained-2026\/\">Kimi K3<\/a> (16 July 2026) \u2014 a 2.8-trillion-parameter open-weight mixture-of-experts scoring <strong>57<\/strong> on the Artificial Analysis Intelligence Index, edging past Claude Opus 4.8 (55.7). It is the first open-weight model to outscore a Western frontier flagship, and at $3\/$15 per 1M tokens it returns roughly <strong>1.7\u00d7 the intelligence per dollar of Opus 4.8<\/strong>.<\/p>\n<p>It does not move the headline spread below, though: K3 lands mid-table on value at 6.3 intelligence points per blended dollar. <a href=\"\/es\/glm-5-2-explained-2026\/\">GLM 5.2<\/a> still returns about 2.8\u00d7 more capability per dollar, and DeepSeek V4-Flash roughly 30\u00d7 more. The ultra-cheap-Chinese-model era looks to be ending too \u2014 K3 costs about 3\u00d7 its own predecessor. Full analysis: <a href=\"\/es\/kimi-k3-explained-2026\/\">Kimi K3 explained<\/a> \u00b7 <a href=\"\/es\/kimi-k3-vs-claude-opus-4-8\/\">K3 vs Opus 4.8<\/a>.<\/p>\n<\/div>\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_85 counter-flat ez-toc-counter ez-toc-container-direction\">\n<label for=\"ez-toc-cssicon-toggle-item-6a75590aa11e6\" class=\"ez-toc-cssicon-toggle-label\"><span class=\"\"><span class=\"eztoc-hide\" style=\"display:none;\">Alternar<\/span><span class=\"ez-toc-icon-toggle-span\"><svg style=\"fill: #000000;color:#000000\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" class=\"list-377408\" width=\"20px\" height=\"20px\" viewbox=\"0 0 24 24\" fill=\"none\"><path d=\"M6 6H4v2h2V6zm14 0H8v2h12V6zM4 11h2v2H4v-2zm16 0H8v2h12v-2zM4 16h2v2H4v-2zm16 0H8v2h12v-2z\" fill=\"currentColor\"><\/path><\/svg><svg style=\"fill: #000000;color:#000000\" class=\"arrow-unsorted-368013\" xmlns=\"http:\/\/www.w3.org\/2000\/svg\" width=\"10px\" height=\"10px\" viewbox=\"0 0 24 24\" version=\"1.2\" baseprofile=\"tiny\"><path d=\"M18.2 9.3l-6.2-6.3-6.2 6.3c-.2.2-.3.4-.3.7s.1.5.3.7c.2.2.4.3.7.3h11c.3 0 .5-.1.7-.3.2-.2.3-.5.3-.7s-.1-.5-.3-.7zM5.8 14.7l6.2 6.3 6.2-6.3c.2-.2.3-.5.3-.7s-.1-.5-.3-.7c-.2-.2-.4-.3-.7-.3h-11c-.3 0-.5.1-.7.3-.2.2-.3.5-.3.7s.1.5.3.7z\"\/><\/svg><\/span><\/span><\/label><input type=\"checkbox\"  id=\"ez-toc-cssicon-toggle-item-6a75590aa11e6\"  aria-label=\"Alternar\" \/><nav><ul class='ez-toc-list ez-toc-list-level-1' ><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-1\" href=\"https:\/\/convly.ai\/es\/ai-price-performance-index-2026\/#How_we_measured_it\" >C\u00f3mo lo medimos<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/convly.ai\/es\/ai-price-performance-index-2026\/#The_2026_blended-cost_index\" >\u00cdndice de costo combinado 2026<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/convly.ai\/es\/ai-price-performance-index-2026\/#Intelligence_per_dollar_%E2%80%94_the_value_ranking\" >Inteligencia por d\u00f3lar \u2014 clasificaci\u00f3n por valor<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/convly.ai\/es\/ai-price-performance-index-2026\/#What_this_means_for_you\" >Qu\u00e9 significa esto para ti<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/convly.ai\/es\/ai-price-performance-index-2026\/#Caveats\" >Salvedades<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/convly.ai\/es\/ai-price-performance-index-2026\/#Bottom_line\" >Conclusi\u00f3n<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/convly.ai\/es\/ai-price-performance-index-2026\/#Download_the_data_%E2%80%94_free_open_CC-BY-40\" >Download the data \u2014 free &amp; open (CC-BY-4.0)<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/convly.ai\/es\/ai-price-performance-index-2026\/#Cite_or_republish_this_study\" >Cite or republish this study<\/a><\/li><\/ul><\/nav><\/div>\n<h2><span class=\"ez-toc-section\" id=\"How_we_measured_it\"><\/span>C\u00f3mo lo medimos<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<ul>\n<li><strong>Precios<\/strong> \u2014 live input\/output API prices (per 1M tokens) from the Convly <a href=\"https:\/\/convly.ai\/es\/models\/\">Base de datos de modelos de IA<\/a>.<\/li>\n<li><strong>Coste combinado<\/strong> \u2014 una relaci\u00f3n de tokens de entrada a salida de 3:1 (t\u00edpica del tr\u00e1fico real mediante API): <code>combinado = (3 \u00d7 entrada + salida) \/ 4<\/code>. Esto permite comparar directamente modelos con entradas econ\u00f3micas pero salidas costosas.<\/li>\n<li><strong>Rendimiento<\/strong> \u2014 el \u00cdndice de Inteligencia Artificial Independiente de Artificial Analysis (un \u00edndice compuesto que abarca razonamiento, programaci\u00f3n, matem\u00e1ticas y conocimiento), utilizado <em>solo<\/em> donde se publica una puntuaci\u00f3n actual para el modelo exacto.<\/li>\n<li><strong>Valor<\/strong> \u2014 \u00cdndice de Inteligencia \u00f7 costo combinado.<\/li>\n<\/ul>\n<h2><span class=\"ez-toc-section\" id=\"The_2026_blended-cost_index\"><\/span>\u00cdndice de costo combinado 2026<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<table class=\"convly-vs\">\n<thead>\n<tr>\n<th>Modelos<\/th>\n<th>Entrada: $\/1 mill\u00f3n<\/th>\n<th>Salida: $\/1 mill\u00f3n<\/th>\n<th>D\u00f3lares por mill\u00f3n combinados<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>DeepSeek V4-Flash<\/td>\n<td>$0.14<\/td>\n<td>$0.28<\/td>\n<td><strong>$0.18<\/strong><\/td>\n<\/tr>\n<tr>\n<td>DeepSeek V4-Pro<\/td>\n<td>$0.435<\/td>\n<td>$0.87<\/td>\n<td><strong>$0.54<\/strong><\/td>\n<\/tr>\n<tr>\n<td>Claude Haiku 4.5<\/td>\n<td>$1.00<\/td>\n<td>$5.00<\/td>\n<td><strong>$2.00<\/strong><\/td>\n<\/tr>\n<tr>\n<td>Gemini 3.5 Flash<\/td>\n<td>$1.50<\/td>\n<td>$9.00<\/td>\n<td><strong>$3.38<\/strong><\/td>\n<\/tr>\n<tr>\n<td>Gemini 3.1 Pro<\/td>\n<td>$2.00<\/td>\n<td>$12.00<\/td>\n<td><strong>$4.50<\/strong><\/td>\n<\/tr>\n<tr>\n<td>Claude Sonnet 4.6<\/td>\n<td>$3.00<\/td>\n<td>$15.00<\/td>\n<td><strong>$6.00<\/strong><\/td>\n<\/tr>\n<tr>\n<td>Claude Opus 4.8<\/td>\n<td>$5.00<\/td>\n<td>$25.00<\/td>\n<td><strong>$10.00<\/strong><\/td>\n<\/tr>\n<tr>\n<td>GPT-5.5<\/td>\n<td>$5.00<\/td>\n<td>$30.00<\/td>\n<td><strong>$11.25<\/strong><\/td>\n<\/tr>\n<tr>\n<td>Claude Fable 5<\/td>\n<td>$10.00<\/td>\n<td>$50.00<\/td>\n<td><strong>$20.00<\/strong><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>La diferencia es lo relevante: <strong>Claude Fable 5 costs 114\u00d7 more per blended token than DeepSeek V4-Flash.<\/strong> \u00bfDesea obtener sus propios valores? Pruebe nuestra <a href=\"\/es\/ai-api-cost-calculator\/\">Calculadora de costos de API de IA<\/a>.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Intelligence_per_dollar_%E2%80%94_the_value_ranking\"><\/span>Inteligencia por d\u00f3lar \u2014 clasificaci\u00f3n por valor<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Ahora dividimos la capacidad entre el costo. Usando el \u00cdndice de Inteligencia Artificial de Artificial Analysis (mayor = mayor capacidad) frente al costo combinado, para los modelos con una puntuaci\u00f3n actual publicada:<\/p>\n<table class=\"convly-vs\">\n<thead>\n<tr>\n<th>Modelos<\/th>\n<th>\u00cdndice de Inteligencia<\/th>\n<th>D\u00f3lares por mill\u00f3n combinados<\/th>\n<th>Inteligencia por d\u00f3lar<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>DeepSeek V4-Flash<\/td>\n<td>37.4<\/td>\n<td>$0.18<\/td>\n<td><strong>\u2248 208<\/strong><\/td>\n<\/tr>\n<tr>\n<td>Claude Opus 4.8<\/td>\n<td>55.7<\/td>\n<td>$10.00<\/td>\n<td><strong>\u2248 5,6<\/strong><\/td>\n<\/tr>\n<tr>\n<td>GPT-5.5<\/td>\n<td>54.8<\/td>\n<td>$11.25<\/td>\n<td><strong>\u2248 4,9<\/strong><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>El hallazgo es contundente: <strong>DeepSeek V4-Flash ofrece aproximadamente 37 veces m\u00e1s inteligencia por d\u00f3lar que Claude Opus 4.8<\/strong> \u2014 aunque a\u00fan obtiene cerca de dos tercios de la inteligencia bruta de Opus. La prima de los modelos frontera es real, pero en t\u00e9rminos de <em>capacidad<\/em> es peque\u00f1a; en t\u00e9rminos de <em>precio<\/em> es enorme.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"What_this_means_for_you\"><\/span>Qu\u00e9 significa esto para ti<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<ul>\n<li><strong>La prima de los modelos frontera adquiere \u00fanicamente los \u00faltimos puntos, no una inteligencia proporcional.<\/strong> Se paga de 30 a 40 veces m\u00e1s por aproximadamente el tercio superior de la capacidad.<\/li>\n<li><strong>Para producci\u00f3n a gran volumen<\/strong> \u2014 chat, clasificaci\u00f3n, extracci\u00f3n, RAG \u2014 un modelo econ\u00f3mico o abierto es la opci\u00f3n racional por defecto.<\/li>\n<li><strong>Reserve los modelos frontera<\/strong> (Opus 4.8, GPT-5.5, Fable 5) para las tareas m\u00e1s exigentes de razonamiento y agentes con horizonte largo, donde esos \u00faltimos puntos realmente importan.<\/li>\n<li><strong>El autohospedaje de modelos de pesos abiertos cambia por completo los c\u00e1lculos<\/strong> \u2014 su costo pasa a ser el hardware y la electricidad, no el costo por token. Consulte nuestra <a href=\"\/es\/llm-vram-calculator\/\">Calculadora de VRAM<\/a> para verificar qu\u00e9 modelos puede ejecutar localmente.<\/li>\n<\/ul>\n<h2><span class=\"ez-toc-section\" id=\"Caveats\"><\/span>Salvedades<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>El \u00cdndice de Inteligencia es un indicador compuesto aproximado; su tarea podr\u00eda ponderar de forma distinta la programaci\u00f3n, el contexto largo o la multimodalidad, y los modelos frontera lideran con mayor ventaja en las tareas agentivas m\u00e1s complejas. Asimismo, los precios cambian, y el almacenamiento en cach\u00e9 o los descuentos por lotes pueden reducir las facturas reales entre un 50 % y un 90 %. Considere este an\u00e1lisis como un mapa orientativo de valor, no como un veredicto definitivo para cada carga de trabajo.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Bottom_line\"><\/span>Conclusi\u00f3n<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>En 2026, la frase \u00ablo que pagas es lo que obtienes\u00bb es simplemente falsa para las APIs de IA. Los modelos capaces m\u00e1s econ\u00f3micos ofrecen la inmensa mayor\u00eda de la inteligencia frontera a una fracci\u00f3n m\u00ednima del costo. Ajuste el modelo a la tarea \u2014y ejecute su propio uso a trav\u00e9s de nuestra <a href=\"\/es\/ai-api-cost-calculator\/\">calculadora de costos<\/a> antes de comprometerte.<\/p>\n<p><em>Fuentes: \u00cdndice de Inteligencia Artificial de Artificial Analysis (puntuaciones de inteligencia); Base de datos de modelos de Convly AI (precios). Las cifras son vigentes a junio de 2026.<\/em><\/p>\n<div class=\"ppi-box\">\n<h2><span class=\"ez-toc-section\" id=\"Download_the_data_%E2%80%94_free_open_CC-BY-40\"><\/span>Download the data \u2014 free &amp; open (CC-BY-4.0)<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>The full 30-model dataset (prices, specs, intelligence scores and value ratios) is open for anyone to analyse or republish with attribution:<\/p>\n<ul>\n<li><a href=\"https:\/\/github.com\/Sakd99\/ai-models-database\" rel=\"noopener\" target=\"_blank\">CSV + JSON on GitHub<\/a><\/li>\n<li><a href=\"https:\/\/huggingface.co\/datasets\/sakd99\/ai-models-database\" rel=\"noopener\" target=\"_blank\">Dataset on Hugging Face<\/a><\/li>\n<\/ul>\n<\/div>\n<div class=\"ppi-box\">\n<h2><span class=\"ez-toc-section\" id=\"Cite_or_republish_this_study\"><\/span>Cite or republish this study<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Free to cite, quote or embed with a link back. Suggested credit:<\/p>\n<blockquote><p>&#8220;The AI Price\/Performance Index 2026,&#8221; Convly \u2014 https:\/\/convly.ai\/ai-price-performance-index-2026\/<\/p><\/blockquote>\n<p><strong>Headline finding for reference:<\/strong> a 114\u00d7 blended-cost spread separates the cheapest capable AI model ($0.18\/1M tokens) from the most expensive ($20\/1M), yet the best-value model returns roughly <strong>37\u00d7 the intelligence-per-dollar<\/strong> of the priciest frontier model while still scoring about two-thirds of its raw intelligence. Journalists and researchers: the underlying data is downloadable above, and we&#8217;re happy to share the full methodology or a high-resolution chart on request.<\/p>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>We combined live API pricing with the Artificial Analysis Intelligence Index to rank AI models by intelligence per dollar. The price spread is 114\u00d7 \u2014 but value tells a very different story.<\/p>","protected":false},"author":1,"featured_media":1806,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"categories":[247],"tags":[787,790,421,654,788,789],"class_list":["post-1246","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai-benchmarks","tag-ai-pricing","tag-claude","tag-deepseek","tag-gpt-5-5","tag-llm-cost","tag-price-performance"],"_links":{"self":[{"href":"https:\/\/convly.ai\/es\/wp-json\/wp\/v2\/posts\/1246","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/convly.ai\/es\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/convly.ai\/es\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/convly.ai\/es\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/convly.ai\/es\/wp-json\/wp\/v2\/comments?post=1246"}],"version-history":[{"count":5,"href":"https:\/\/convly.ai\/es\/wp-json\/wp\/v2\/posts\/1246\/revisions"}],"predecessor-version":[{"id":1592,"href":"https:\/\/convly.ai\/es\/wp-json\/wp\/v2\/posts\/1246\/revisions\/1592"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/convly.ai\/es\/wp-json\/wp\/v2\/media\/1806"}],"wp:attachment":[{"href":"https:\/\/convly.ai\/es\/wp-json\/wp\/v2\/media?parent=1246"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/convly.ai\/es\/wp-json\/wp\/v2\/categories?post=1246"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/convly.ai\/es\/wp-json\/wp\/v2\/tags?post=1246"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}