{"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\/pt\/ai-price-performance-index-2026\/","title":{"rendered":"\u00cdndice de Pre\u00e7o-Desempenho de IA 2026: Qual Modelo Oferece Mais Intelig\u00eancia 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\">$20.00<\/text><\/g>\n <\/g>\n<\/svg><figcaption>Blended cost = (3 \u00d7 input + output) \u00f7 4, a 3:1 input-to-output ratio typical of real API traffic. Source: Convly AI models database. Green = best value, orange = most expensive.<\/figcaption><\/figure>\n<p>Os pre\u00e7os dos modelos de IA em 2026 abrangem uma faixa surpreendente \u2014 contudo, o modelo mais caro est\u00e1 longe de ser 100 vezes mais inteligente que o mais barato. Combinamos os pre\u00e7os ao vivo em nosso <a href=\"\/pt\/models\/\">Banco de dados de modelos de IA<\/a> com o independente <strong>\u00cdndice de Intelig\u00eancia Artificial da Artificial Analysis<\/strong> para responder a uma \u00fanica pergunta: <strong>qual modelo oferece mais intelig\u00eancia por d\u00f3lar?<\/strong> A resposta desafia a suposi\u00e7\u00e3o de que voc\u00ea obt\u00e9m exatamente o que paga.<\/p>\n<div class=\"convly-tldr\">\n<h3>Principais conclus\u00f5es<\/h3>\n<ul>\n<li><strong>Diferen\u00e7a de pre\u00e7o de 114\u00d7.<\/strong> Em termos de custo combinado, os modelos de ponta dispon\u00edveis por API variam de aproximadamente US$ 0,18 a US$ 20 por milh\u00e3o de tokens.<\/li>\n<li><strong>Valor \u2260 pre\u00e7o.<\/strong> Os modelos capazes mais baratos entregam <strong>30\u201340\u00d7 mais intelig\u00eancia por d\u00f3lar<\/strong> do que os modelos de ponta mais caros.<\/li>\n<li><strong>DeepSeek V4-Flash<\/strong> oferece aproximadamente <strong>67% da intelig\u00eancia medida do Claude Opus 4.8 a cerca de 1,8% do custo.<\/strong><\/li>\n<li>Pagar o pre\u00e7o m\u00e1ximo garante apenas os <em>\u00faltimos pontos<\/em> de capacidade \u2014 n\u00e3o uma intelig\u00eancia proporcional.<\/li>\n<li>Para a maioria das cargas de trabalho, um modelo de m\u00e9dio porte ou de c\u00f3digo aberto \u00e9 a escolha racional padr\u00e3o; reserve os modelos de ponta apenas para as tarefas mais dif\u00edceis.<\/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=\"\/pt\/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=\"\/pt\/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=\"\/pt\/kimi-k3-explained-2026\/\">Kimi K3 explained<\/a> \u00b7 <a href=\"\/pt\/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-6a75588b915f6\" 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-6a75588b915f6\"  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\/pt\/ai-price-performance-index-2026\/#How_we_measured_it\" >Como fizemos a medi\u00e7\u00e3o<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/convly.ai\/pt\/ai-price-performance-index-2026\/#The_2026_blended-cost_index\" >\u00cdndice de custo combinado 2026<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/convly.ai\/pt\/ai-price-performance-index-2026\/#Intelligence_per_dollar_%E2%80%94_the_value_ranking\" >Intelig\u00eancia por d\u00f3lar \u2014 classifica\u00e7\u00e3o de valor<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/convly.ai\/pt\/ai-price-performance-index-2026\/#What_this_means_for_you\" >O que isso significa para voc\u00ea<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/convly.ai\/pt\/ai-price-performance-index-2026\/#Caveats\" >Reservas<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/convly.ai\/pt\/ai-price-performance-index-2026\/#Bottom_line\" >Conclus\u00e3o<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/convly.ai\/pt\/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\/pt\/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>Como fizemos a medi\u00e7\u00e3o<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<ul>\n<li><strong>Pre\u00e7os<\/strong> \u2014 live input\/output API prices (per 1M tokens) from the Convly <a href=\"https:\/\/convly.ai\/pt\/models\/\">Banco de dados de modelos de IA<\/a>.<\/li>\n<li><strong>Custo combinado<\/strong> \u2014 uma propor\u00e7\u00e3o de 3:1 entre tokens de entrada e sa\u00edda (t\u00edpica do tr\u00e1fego real em APIs): <code>custo combinado = (3 \u00d7 entrada + sa\u00edda) \u00f7 4<\/code>. Isso torna modelos com entrada barata, mas sa\u00edda cara, diretamente compar\u00e1veis.<\/li>\n<li><strong>Desempenho<\/strong> \u2014 o \u00cdndice de Intelig\u00eancia Artificial Analysis (um \u00edndice composto que abrange racioc\u00ednio, programa\u00e7\u00e3o, matem\u00e1tica e conhecimento), utilizado <em>apenas<\/em> quando uma pontua\u00e7\u00e3o atual est\u00e1 publicada para o modelo exato.<\/li>\n<li><strong>Valor<\/strong> \u2014 \u00cdndice de Intelig\u00eancia \u00f7 custo combinado.<\/li>\n<\/ul>\n<h2><span class=\"ez-toc-section\" id=\"The_2026_blended-cost_index\"><\/span>\u00cdndice de custo combinado 2026<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<table class=\"convly-vs\">\n<thead>\n<tr>\n<th>Modelo<\/th>\n<th>Entrada: US$ por 1 milh\u00e3o<\/th>\n<th>Sa\u00edda: US$ por 1 milh\u00e3o<\/th>\n<th>Custo m\u00e9dio ponderado por US$ 1 milh\u00e3o<\/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>$20.00<\/strong><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p>A diferen\u00e7a \u00e9 o ponto central da hist\u00f3ria: <strong>Claude Fable 5 costs 114\u00d7 more per blended token than DeepSeek V4-Flash.<\/strong> Quer obter seus pr\u00f3prios n\u00fameros? Experimente nossa <a href=\"\/pt\/ai-api-cost-calculator\/\">Calculadora de custos de API de IA<\/a>.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Intelligence_per_dollar_%E2%80%94_the_value_ranking\"><\/span>Intelig\u00eancia por d\u00f3lar \u2014 classifica\u00e7\u00e3o de valor<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Agora dividimos a capacidade pelo custo. Usando o \u00cdndice de Intelig\u00eancia Artificial Analysis (quanto maior, mais capaz) em compara\u00e7\u00e3o com o custo combinado, para os modelos com pontua\u00e7\u00e3o atual publicada:<\/p>\n<table class=\"convly-vs\">\n<thead>\n<tr>\n<th>Modelo<\/th>\n<th>\u00cdndice de Intelig\u00eancia<\/th>\n<th>Custo m\u00e9dio ponderado por US$ 1 milh\u00e3o<\/th>\n<th>Intelig\u00eancia 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>O achado \u00e9 contundente: <strong>DeepSeek V4-Flash entrega aproximadamente 37\u00d7 mais intelig\u00eancia por d\u00f3lar do que Claude Opus 4.8<\/strong> \u2014 embora ainda obtenha cerca de dois ter\u00e7os da intelig\u00eancia bruta do Opus. O pr\u00eamio dos modelos de ponta \u00e9 real, mas em termos de <em>capacidade<\/em> \u00e9 pequeno; em termos de <em>pre\u00e7o<\/em> \u00e9 enorme.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"What_this_means_for_you\"><\/span>O que isso significa para voc\u00ea<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<ul>\n<li><strong>O pr\u00eamio dos modelos de ponta compra os \u00faltimos pontos, n\u00e3o uma intelig\u00eancia proporcional.<\/strong> Voc\u00ea paga 30\u201340\u00d7 mais pelos aproximadamente \u00faltimos ter\u00e7os de capacidade.<\/li>\n<li><strong>Para produ\u00e7\u00e3o em grande volume<\/strong> \u2014 chat, classifica\u00e7\u00e3o, extra\u00e7\u00e3o, RAG \u2014 um modelo barato ou aberto \u00e9 a escolha racional padr\u00e3o.<\/li>\n<li><strong>Reserve os modelos de ponta<\/strong> (Opus 4.8, GPT-5.5, Fable 5) para as tarefas mais dif\u00edceis de racioc\u00ednio e trabalho ag\u00eantico de longo prazo, nas quais os \u00faltimos pontos realmente importam.<\/li>\n<li><strong>Hospedar localmente modelos de pesos abertos muda totalmente os c\u00e1lculos<\/strong> \u2014 seu custo passa a ser o hardware e a energia el\u00e9trica, n\u00e3o por token. Consulte nossa <a href=\"\/pt\/llm-vram-calculator\/\">Calculadora de VRAM<\/a> para verificar quais modelos voc\u00ea consegue executar localmente.<\/li>\n<\/ul>\n<h2><span class=\"ez-toc-section\" id=\"Caveats\"><\/span>Reservas<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>O \u00cdndice de Intelig\u00eancia \u00e9 apenas um indicador composto \u2014 sua tarefa pode atribuir pesos diferentes \u00e0 programa\u00e7\u00e3o, ao contexto longo ou \u00e0 multimodalidade, e os modelos de ponta lideram com maior vantagem nas tarefas ag\u00eanticas mais dif\u00edceis. Os pre\u00e7os tamb\u00e9m mudam, e descontos por cache ou processamento em lote podem reduzir suas despesas reais em 50\u201390%. Trate esta an\u00e1lise como um mapa orientador de valores, n\u00e3o como um veredito definitivo para todas as cargas de trabalho.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Bottom_line\"><\/span>Conclus\u00e3o<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Em 2026, a frase \u00abvoc\u00ea obt\u00e9m o que paga\u00bb simplesmente n\u00e3o se aplica \u00e0s APIs de IA. Os modelos capazes mais baratos entregam a grande maioria da intelig\u00eancia de ponta por uma fra\u00e7\u00e3o m\u00ednima do custo. Escolha o modelo adequado \u00e0 tarefa \u2014 e calcule seu pr\u00f3prio uso com nossa <a href=\"\/pt\/ai-api-cost-calculator\/\">calculadora de custos<\/a> antes de se comprometer.<\/p>\n<p><em>Fontes: \u00cdndice de Intelig\u00eancia Artificial Analysis (pontua\u00e7\u00f5es de intelig\u00eancia); base de dados de modelos da Convly AI (pre\u00e7os). Valores atualizados at\u00e9 junho 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\/pt\/wp-json\/wp\/v2\/posts\/1246","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/convly.ai\/pt\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/convly.ai\/pt\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/convly.ai\/pt\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/convly.ai\/pt\/wp-json\/wp\/v2\/comments?post=1246"}],"version-history":[{"count":5,"href":"https:\/\/convly.ai\/pt\/wp-json\/wp\/v2\/posts\/1246\/revisions"}],"predecessor-version":[{"id":1592,"href":"https:\/\/convly.ai\/pt\/wp-json\/wp\/v2\/posts\/1246\/revisions\/1592"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/convly.ai\/pt\/wp-json\/wp\/v2\/media\/1806"}],"wp:attachment":[{"href":"https:\/\/convly.ai\/pt\/wp-json\/wp\/v2\/media?parent=1246"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/convly.ai\/pt\/wp-json\/wp\/v2\/categories?post=1246"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/convly.ai\/pt\/wp-json\/wp\/v2\/tags?post=1246"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}