{"id":49,"date":"2026-05-18T12:37:26","date_gmt":"2026-05-18T12:37:26","guid":{"rendered":"https:\/\/convly.ai\/gpt5-vs-claude4-vs-gemini3\/"},"modified":"2026-06-10T05:06:10","modified_gmt":"2026-06-10T05:06:10","slug":"gpt5-vs-claude4-vs-gemini3","status":"publish","type":"post","link":"https:\/\/convly.ai\/pt\/gpt5-vs-claude4-vs-gemini3\/","title":{"rendered":"GPT-5 vs Claude 4 vs Gemini 3: qual modelo de IA vence em 2026?"},"content":{"rendered":"<p>Three model families sit at the frontier of AI in 2026: OpenAI&#8217;s <strong>GPT-5<\/strong>, Anthropic&#8217;s <strong>Claude 4<\/strong>, and Google&#8217;s <strong>Gemini 3<\/strong>. They are all genuinely excellent. They are also close enough that &#8220;which is best?&#8221; has no single answer \u2014 the honest answer is &#8220;best at what?&#8221;<\/p>\n<p>This comparison skips the leaderboard horse race, because benchmark rankings change with every release. Instead it focuses on the durable strengths of each family and gives you a practical guide to picking the right one for a given job.<\/p>\n<div class=\"convly-tldr\">\n<h3>Principais conclus\u00f5es<\/h3>\n<ul>\n<li><strong>GPT-5<\/strong> \u2014 the most versatile all-rounder, with the biggest ecosystem of features and integrations.<\/li>\n<li><strong>Claude 4<\/strong> \u2014 the favorite for coding and writing, known for natural prose and reliable instruction-following.<\/li>\n<li><strong>Gemini 3<\/strong> \u2014 the strongest at multimodal work and huge context, deeply tied into Google&#8217;s products.<\/li>\n<li><strong>They&#8217;re close.<\/strong> All three are excellent; pick by use case, not by leaderboard.<\/li>\n<li><strong>Best move:<\/strong> all three have free tiers \u2014 test them on your own tasks.<\/li>\n<\/ul>\n<\/div>\n<div id=\"ez-toc-container\" class=\"ez-toc-v2_0_84 counter-flat ez-toc-counter ez-toc-container-direction\">\n<label for=\"ez-toc-cssicon-toggle-item-6a38bc641a4c6\" 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-6a38bc641a4c6\"  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\/gpt5-vs-claude4-vs-gemini3\/#How_to_think_about_the_comparison\" >How to think about the comparison<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-2\" href=\"https:\/\/convly.ai\/pt\/gpt5-vs-claude4-vs-gemini3\/#GPT-5_OpenAI_%E2%80%94_the_versatile_all-rounder\" >GPT-5 (OpenAI) \u2014 the versatile all-rounder<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-3\" href=\"https:\/\/convly.ai\/pt\/gpt5-vs-claude4-vs-gemini3\/#Claude_4_Anthropic_%E2%80%94_the_coders_and_writers_choice\" >Claude 4 (Anthropic) \u2014 the coder&#8217;s and writer&#8217;s choice<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-4\" href=\"https:\/\/convly.ai\/pt\/gpt5-vs-claude4-vs-gemini3\/#Gemini_3_Google_%E2%80%94_the_multimodal_and_context_leader\" >Gemini 3 (Google) \u2014 the multimodal and context leader<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-5\" href=\"https:\/\/convly.ai\/pt\/gpt5-vs-claude4-vs-gemini3\/#Side-by-side_comparison\" >Side-by-side comparison<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-6\" href=\"https:\/\/convly.ai\/pt\/gpt5-vs-claude4-vs-gemini3\/#Which_should_you_choose\" >Qual deles voc\u00ea deve escolher?<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-7\" href=\"https:\/\/convly.ai\/pt\/gpt5-vs-claude4-vs-gemini3\/#Dont_over-commit\" >Don&#8217;t over-commit<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-8\" href=\"https:\/\/convly.ai\/pt\/gpt5-vs-claude4-vs-gemini3\/#What_it_actually_costs_to_run_at_scale\" >What it actually costs to run at scale<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-9\" href=\"https:\/\/convly.ai\/pt\/gpt5-vs-claude4-vs-gemini3\/#FAQ\" >Perguntas frequentes<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-10\" href=\"https:\/\/convly.ai\/pt\/gpt5-vs-claude4-vs-gemini3\/#Bottom_line\" >Conclus\u00e3o<\/a><\/li><li class='ez-toc-page-1'><a class=\"ez-toc-link ez-toc-heading-11\" href=\"https:\/\/convly.ai\/pt\/gpt5-vs-claude4-vs-gemini3\/#Related_articles\" >Artigos relacionados<\/a><\/li><\/ul><\/nav><\/div>\n<h2><span class=\"ez-toc-section\" id=\"How_to_think_about_the_comparison\"><\/span>How to think about the comparison<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Frontier models leapfrog each other constantly. Whichever model tops a benchmark today may be passed next month. So instead of chasing rankings, judge models on the qualities that stay stable across versions: each family&#8217;s <em>character<\/em> \u2014 what it&#8217;s consistently good at, how it behaves, and what ecosystem it sits in.<\/p>\n<p>On that basis, here&#8217;s how the three compare.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"GPT-5_OpenAI_%E2%80%94_the_versatile_all-rounder\"><\/span>GPT-5 (OpenAI) \u2014 the versatile all-rounder<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>GPT-5&#8217;s defining strength is <strong>breadth<\/strong>. It&#8217;s not just a model \u2014 it&#8217;s the center of the largest ecosystem in AI: image generation, voice conversation, web browsing, data analysis, a vast library of custom assistants, and integrations almost everywhere. Whatever you want to do, GPT-5 probably has a path to it.<\/p>\n<p>It&#8217;s a strong performer across the board \u2014 reasoning, coding, writing, multimodal \u2014 without an obvious weakness. For a user who wants <em>one<\/em> model that does the widest possible range of tasks well, GPT-5 is the natural default.<\/p>\n<p><strong>Melhor para:<\/strong> general-purpose use, anyone wanting one tool for everything, and building on the richest ecosystem.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Claude_4_Anthropic_%E2%80%94_the_coders_and_writers_choice\"><\/span>Claude 4 (Anthropic) \u2014 the coder&#8217;s and writer&#8217;s choice<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Claude 4 has two areas where it&#8217;s widely considered the leader: <strong>coding<\/strong> e <strong>writing<\/strong>.<\/p>\n<p>For software development, Claude-powered tools are a developer favorite, and Claude 4 is excellent at multi-file changes, debugging, and working through a real codebase. For writing, it produces the most natural prose of the three \u2014 it avoids the tell-tale AI tics and follows nuanced instructions closely. It&#8217;s also strong at careful reasoning over long, complex documents, and has a reputation for reliability \u2014 doing what you asked, in the format you asked for.<\/p>\n<p>It&#8217;s a more focused product than GPT-5 \u2014 fewer bundled features \u2014 but on its core strengths it&#8217;s the one to beat.<\/p>\n<p><strong>Melhor para:<\/strong> coding, long-form and professional writing, careful document work, and instruction-sensitive tasks.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Gemini_3_Google_%E2%80%94_the_multimodal_and_context_leader\"><\/span>Gemini 3 (Google) \u2014 the multimodal and context leader<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>Gemini 3&#8217;s standout strengths are <strong>multimodal understanding<\/strong> e <strong>massive context<\/strong>. It handles text, images, audio, and video together fluently, and its very large context window lets it work over enormous inputs \u2014 long documents, big codebases, hours of transcript \u2014 in a single pass.<\/p>\n<p>Its other major advantage is <strong>integration with Google<\/strong>. If you live in Search, Gmail, Docs, Drive, and Android, Gemini 3 is woven directly into the tools you already use, often making it the most convenient option simply by being there. It also has strong free access.<\/p>\n<p><strong>Melhor para:<\/strong> multimodal tasks, very large inputs, and anyone deep in the Google ecosystem.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Side-by-side_comparison\"><\/span>Side-by-side comparison<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<table class=\"convly-vs\">\n<thead>\n<tr>\n<th>Factor<\/th>\n<th>GPT-5<\/th>\n<th>Claude 4<\/th>\n<th>Gemini 3<\/th>\n<\/tr>\n<\/thead>\n<tbody>\n<tr>\n<td>Melhor em<\/td>\n<td>Versatility, ecosystem<\/td>\n<td>Coding, writing<\/td>\n<td>Multimodal, long context<\/td>\n<\/tr>\n<tr>\n<td>Writing quality<\/td>\n<td>Excelente<\/td>\n<td>Best of the three<\/td>\n<td>Excelente<\/td>\n<\/tr>\n<tr>\n<td>Programa\u00e7\u00e3o<\/td>\n<td>Excelente<\/td>\n<td>Best of the three<\/td>\n<td>Excelente<\/td>\n<\/tr>\n<tr>\n<td>Multimodal<\/td>\n<td>Forte<\/td>\n<td>Forte<\/td>\n<td>Best of the three<\/td>\n<\/tr>\n<tr>\n<td>Ecosystem<\/td>\n<td>Largest<\/td>\n<td>Focused<\/td>\n<td>Built into Google<\/td>\n<\/tr>\n<tr>\n<td>Free tier<\/td>\n<td>Sim<\/td>\n<td>Sim<\/td>\n<td>Yes (generous)<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<h2><span class=\"ez-toc-section\" id=\"Which_should_you_choose\"><\/span>Qual deles voc\u00ea deve escolher?<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<ul>\n<li><strong>You want one model for everything:<\/strong> GPT-5. Its versatility and ecosystem make it the best single subscription for most people.<\/li>\n<li><strong>You write code:<\/strong> Claude 4 \u2014 the developer favorite, and the engine behind the best coding tools.<\/li>\n<li><strong>You write a lot, and quality matters:<\/strong> Claude 4 \u2014 the most natural prose of the three.<\/li>\n<li><strong>You work with images, audio, or video, or very large documents:<\/strong> Gemini 3.<\/li>\n<li><strong>You live in Google&#8217;s apps:<\/strong> Gemini 3, for the seamless integration.<\/li>\n<li><strong>You&#8217;re a developer building an app:<\/strong> all three offer strong APIs \u2014 many teams route each task to whichever model handles it best.<\/li>\n<\/ul>\n<h2><span class=\"ez-toc-section\" id=\"Dont_over-commit\"><\/span>Don&#8217;t over-commit<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>The most useful advice in this whole comparison: don&#8217;t treat the choice as permanent. The lead between these three shifts every few months. All three have free tiers. The smart approach is to keep access to at least two, run your own real tasks through them, and notice which consistently does <em>your<\/em> work best \u2014 then revisit that judgment when any of them ships a major update.<\/p>\n<p><!--ai-enriched--><\/p>\n<h2><span class=\"ez-toc-section\" id=\"What_it_actually_costs_to_run_at_scale\"><\/span>What it actually costs to run at scale<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>The chat subscriptions are roughly at parity, so for casual use price is rarely the deciding factor. The picture changes the moment you build on the API and pay per token. Here the three families diverge sharply, and the headline rate you see quoted is often the least important number.<\/p>\n<p>Every provider now sells a <strong>tiered lineup<\/strong> rather than a single model, and choosing the right tier matters more than choosing the right brand:<\/p>\n<ul>\n<li><strong>Frontier reasoning tier<\/strong> \u2014 the most capable GPT-5, Claude, and Gemini 3 variants. These are priced for high-stakes work, and the top reasoning models can cost an order of magnitude more on output tokens than the base tier. Reach for them only when the answer genuinely needs maximum reasoning.<\/li>\n<li><strong>Balanced tier<\/strong> \u2014 the workhorses. The mid-weight Claude (Sonnet line) and the standard Gemini 3 Pro sit here, and this is where most production traffic should live. Output tokens, not input, dominate the bill, so a model that answers concisely can be cheaper in practice than one with a lower sticker rate.<\/li>\n<li><strong>Fast\/cheap tier<\/strong> \u2014 small models (the Haiku-class Claude, GPT-5&#8217;s mini variants, Gemini Flash) for classification, routing, and high-volume extraction at a fraction of the cost.<\/li>\n<\/ul>\n<p>One detail to watch with Gemini 3: its pricing is <strong>context-tiered<\/strong>. Crossing the 200K-token mark roughly doubles the input rate and pushes the output rate up sharply too, so its enormous context window is not free to actually fill.<\/p>\n<p>The bigger lever is <strong>caching and batching<\/strong>, which all three now support. Prompt caching reuses a fixed system prompt or document at around a 90% discount on those cached input tokens \u2014 decisive for agents and chatbots that resend the same context on every call. Asynchronous batch processing typically cuts the bill by about half for non-urgent jobs. For a repetitive workload, these two features routinely shift effective cost more than the gap between providers does, which is why a raw price-per-token comparison is misleading on its own.<\/p>\n<p><strong>Our advice:<\/strong> ignore the flagship sticker price. Estimate your real input\/output ratio, route the bulk of traffic to a balanced or small model, reserve the frontier tier for the hard 10%, and turn on caching before you compare vendors at all. Do that and the cheapest option is usually whichever family you have already built tooling around \u2014 switching to shave a few cents per million tokens rarely pays for the migration.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"FAQ\"><\/span>Perguntas frequentes<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<h3>Which is the best AI model in 2026 \u2014 GPT-5, Claude 4, or Gemini 3?<\/h3>\n<p>There&#8217;s no single winner \u2014 all three are excellent and the lead shifts constantly. GPT-5 is the most versatile, Claude 4 is best for coding and writing, and Gemini 3 leads on multimodal tasks and large context. The best model depends entirely on what you need it for.<\/p>\n<h3>Which AI model is best for coding?<\/h3>\n<p>Claude 4 is widely regarded as the best for coding in 2026, and powers many of the most popular AI coding tools. GPT-5 and Gemini 3 are also very strong, so it&#8217;s worth testing on your own codebase \u2014 but Claude 4 is the common favorite among developers.<\/p>\n<h3>Which AI model is best for writing?<\/h3>\n<p>Claude 4 produces the most natural-sounding prose of the three and follows nuanced instructions closely, making it the top pick for long-form and professional writing. GPT-5 and Gemini 3 also write very well \u2014 the gap is small but consistent.<\/p>\n<h3>Which model has the biggest context window?<\/h3>\n<p>Gemini 3 leads on context, with a very large window that lets it process enormous inputs \u2014 long documents, large codebases, lengthy transcripts \u2014 in a single request. This is one of its defining advantages over the other two.<\/p>\n<h3>Are these AI models free to use?<\/h3>\n<p>All three offer free tiers that are genuinely capable, with Gemini 3&#8217;s free access being especially generous. Paid plans (around $20\/month for standard tiers) add higher limits and access to the strongest versions. The free tiers are an excellent way to compare them directly.<\/p>\n<h3>Which model is cheapest to run at scale?<\/h3>\n<p>There is no single winner, because it depends on your input-to-output ratio and whether you use caching. On raw rates, the small &#8220;fast&#8221; tier of each family is cheapest, and the base GPT-5 tier has a notably low input price. But the deciding factor is usually prompt caching (around 90% off reused context) and batch processing (roughly half price), which all three offer. Route most traffic to a mid-weight or small model, enable caching, and the differences between providers shrink to noise.<\/p>\n<h3>Do these providers train on my data?<\/h3>\n<p>By default, API and enterprise traffic from OpenAI, Anthropic, and Google is generally not used to train their public models, which is one reason serious products build on the API rather than the consumer apps. On the consumer chat plans the picture is different: all three offer a toggle to opt out of training, but the default and the retention window vary, so check the setting for each. Opting out applies going forward only \u2014 data already used in training cannot be pulled back.<\/p>\n<h3>Is it hard to switch between GPT-5, Claude, and Gemini later?<\/h3>\n<p>Switching the model itself is easy; the APIs are similar and many teams route through an abstraction layer that swaps providers with a config change. The lock-in is everywhere else: prompts tuned to one model&#8217;s quirks, cached context, function-calling schemas, and provider-specific features. Plan for a short re-tuning and evaluation pass rather than a drop-in swap, and avoid leaning on any one vendor&#8217;s proprietary extensions if portability matters to you.<\/p>\n<h2><span class=\"ez-toc-section\" id=\"Bottom_line\"><\/span>Conclus\u00e3o<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<p>GPT-5, Claude 4, and Gemini 3 are three excellent models with three distinct characters. <strong>GPT-5<\/strong> is the versatile all-rounder with the biggest ecosystem. <strong>Claude 4<\/strong> is the specialist&#8217;s choice for coding and writing. <strong>Gemini 3<\/strong> owns multimodal work, huge context, and Google integration.<\/p>\n<p>Pick by your actual use case, not by this week&#8217;s benchmark. And since all three have free tiers, the best decision you can make is to stop reading comparisons and test them on your own work \u2014 the right model for <em>you<\/em> will become obvious within a few real tasks.<\/p>\n<p><!--related-block--><\/p>\n<div class=\"convly-related\">\n<h2><span class=\"ez-toc-section\" id=\"Related_articles\"><\/span>Artigos relacionados<span class=\"ez-toc-section-end\"><\/span><\/h2>\n<ul>\n<li><a href=\"https:\/\/convly.ai\/pt\/rx-7900-xtx-vs-rtx-4090-for-ai\/\">AMD RX 7900 XTX versus RTX 4090 para IA em 2026: O ROCm consegue competir?<\/a><\/li>\n<li><a href=\"https:\/\/convly.ai\/pt\/rtx-5080-vs-rtx-4080-super-for-ai\/\">RTX 5080 versus RTX 4080 Super para IA em 2026: Diferen\u00e7a geracional ou atualiza\u00e7\u00e3o lateral?<\/a><\/li>\n<li><a href=\"https:\/\/convly.ai\/pt\/rtx-5070-ti-vs-rtx-4070-ti-super-for-ai\/\">RTX 5070 Ti versus RTX 4070 Ti Super para IA em 2026: Confronto na faixa intermedi\u00e1ria<\/a><\/li>\n<li><a href=\"https:\/\/convly.ai\/pt\/rtx-4090-vs-rtx-3090-for-ai\/\">RTX 4090 versus RTX 3090 para IA em 2026: Vale a pena fazer a atualiza\u00e7\u00e3o?<\/a><\/li>\n<\/ul>\n<\/div>","protected":false},"excerpt":{"rendered":"<p>The three frontier AI models compared. We break down GPT-5, Claude 4, and Gemini 3 by real strengths \u2014 coding, writing, research, multimodal \u2014 so you can pick the right one.<\/p>","protected":false},"author":0,"featured_media":50,"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":[246],"tags":[395,451,449,450,448],"class_list":["post-49","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai-comparisons","tag-ai-model-comparison","tag-best-ai-model","tag-claude-4","tag-gemini-3","tag-gpt-5"],"_links":{"self":[{"href":"https:\/\/convly.ai\/pt\/wp-json\/wp\/v2\/posts\/49","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"}],"replies":[{"embeddable":true,"href":"https:\/\/convly.ai\/pt\/wp-json\/wp\/v2\/comments?post=49"}],"version-history":[{"count":3,"href":"https:\/\/convly.ai\/pt\/wp-json\/wp\/v2\/posts\/49\/revisions"}],"predecessor-version":[{"id":1047,"href":"https:\/\/convly.ai\/pt\/wp-json\/wp\/v2\/posts\/49\/revisions\/1047"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/convly.ai\/pt\/wp-json\/wp\/v2\/media\/50"}],"wp:attachment":[{"href":"https:\/\/convly.ai\/pt\/wp-json\/wp\/v2\/media?parent=49"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/convly.ai\/pt\/wp-json\/wp\/v2\/categories?post=49"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/convly.ai\/pt\/wp-json\/wp\/v2\/tags?post=49"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}