{"id":1266,"date":"2026-06-23T14:45:03","date_gmt":"2026-06-23T14:45:03","guid":{"rendered":"https:\/\/convly.ai\/?p=1266"},"modified":"2026-06-23T14:45:03","modified_gmt":"2026-06-23T14:45:03","slug":"deepseek-v4-flash-vs-gemini-3-5-flash","status":"publish","type":"post","link":"https:\/\/convly.ai\/pt\/deepseek-v4-flash-vs-gemini-3-5-flash\/","title":{"rendered":"DeepSeek V4-Flash vs Gemini 3.5 Flash: Especifica\u00e7\u00f5es, pre\u00e7os e qual escolher (2026)"},"content":{"rendered":"<p><strong>DeepSeek V4-Flash<\/strong> vs <strong>Gemini 3.5 Flash<\/strong> \u2014 os dois modelos r\u00e1pidos mais baratos, comparados com base nos custos reais. Abaixo est\u00e1 a compara\u00e7\u00e3o detalhada lado a lado: especifica\u00e7\u00f5es, pre\u00e7os de API, janela de contexto, requisitos de hardware local e uma recomenda\u00e7\u00e3o clara, fundamentada em dados, sobre qual escolher.<\/p>\n<div class=\"cmp\">\n  <table class=\"cmp-table\">\n    <thead><tr><th>Especifica\u00e7\u00f5es<\/th><th><a href=\"https:\/\/convly.ai\/pt\/model\/deepseek-v4-flash\/\">DeepSeek V4-Flash<\/a><\/th><th><a href=\"https:\/\/convly.ai\/pt\/model\/gemini-3-5-flash\/\">Gemini 3.5 Flash<\/a><\/th><\/tr><\/thead>\n    <tbody>\n          <tr><td class=\"cmp-spec\">Desenvolvedor<\/td><td class=\"\">DeepSeek<\/td><td class=\"\">Google<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Tipo<\/td><td class=\"\">LLM (MoE)<\/td><td class=\"\">LLM (multimodal)<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Par\u00e2metros<\/td><td class=\"\">284B no total \/ ~13B ativos (MoE)<\/td><td class=\"\">N\u00e3o divulgado<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Janela de contexto<\/td><td class=\"\">1 milh\u00e3o<\/td><td class=\"\">1 milh\u00e3o<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Modalidade<\/td><td class=\"\">Texto \u2192 Texto<\/td><td class=\"\">Texto, imagem, \u00e1udio, v\u00eddeo \u2192 Texto<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Licen\u00e7a<\/td><td class=\"\">MIT (aberta)<\/td><td class=\"\">Propriet\u00e1rio<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Pesos abertos<\/td><td class=\"\">\u2705 Sim<\/td><td class=\"\">\u274c N\u00e3o<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Pre\u00e7o de entrada (US$\/1 milh\u00e3o)<\/td><td class=\"cmp-win\">$0.14<\/td><td class=\"\">$1.50<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Pre\u00e7o de sa\u00edda (US$\/1 milh\u00e3o)<\/td><td class=\"\">$0.28<\/td><td class=\"\">$9.00<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">VRAM (4 bits)<\/td><td class=\"\">~140 GB<\/td><td class=\"\">\u2014<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">GPU m\u00ednima (local)<\/td><td class=\"\">2\u00d7 H100 80 GB (4 bits)<\/td><td class=\"\">\u2014<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Lan\u00e7ado<\/td><td class=\"\">2026-04<\/td><td class=\"\">2026<\/td><\/tr>\n        <\/tbody>\n  <\/table>\n\n    <div class=\"cmp-verdict\">\n    <h3>Principais diferen\u00e7as<\/h3>\n    <ul><li><strong>Custo:<\/strong> O DeepSeek V4-Flash \u00e9 <strong>1.829% mais barato<\/strong> que o Gemini 3.5 Flash com base no custo por token combinado.<\/li><li><strong>Abertura:<\/strong> DeepSeek V4-Flash possui pesos abertos (pode ser hospedado localmente, privado e ajust\u00e1vel); Gemini 3.5 Flash \u00e9 propriet\u00e1rio (apenas via API, mas totalmente gerenciado).<\/li><li><strong>Execute o DeepSeek V4-Flash localmente:<\/strong> ~~140 GB em 4 bits (m\u00ednimo: 2\u00d7 H100 80 GB (4 bits)).<\/li><\/ul>\n  <\/div>\n\n    <div class=\"cmp-rec\">\n    <h3>Qual voc\u00ea deve escolher?<\/h3>\n    <p><strong>Escolha o DeepSeek V4-Flash<\/strong> se voc\u00ea deseja um custo menor por token para cargas de trabalho de alto volume, ou se deseja hospedar localmente, ajustar finamente ou manter seus dados totalmente privados.<\/p>\n    <p><strong>Escolha o Gemini 3.5 Flash<\/strong> se voc\u00ea preferir uma API totalmente gerenciada, sem infraestrutura para executar.<\/p>\n    <p class=\"cmp-tools\">\u2192 Estime custos reais no <a href=\"\/pt\/ai-api-cost-calculator\/\">Calculadora de custo de API<\/a> \u00b7 verifique o hardware local no <a href=\"\/pt\/llm-vram-calculator\/\">Calculadora de VRAM<\/a> \u00b7 navegue por todos os <a href=\"\/pt\/models\/\">30+ modelos<\/a>.<\/p>\n  <\/div>\n<\/div>\n\n<p>Todas as especifica\u00e7\u00f5es e pre\u00e7os s\u00e3o obtidos em tempo real do nosso <a href=\"\/pt\/models\/\">Banco de dados de modelos de IA<\/a> e mantidos atualizados. Compare qualquer um desses modelos com outros ou estime seus pr\u00f3prios gastos mensais com as calculadoras gratuitas acima.<\/p>","protected":false},"excerpt":{"rendered":"<p>DeepSeek V4-Flash vs Gemini 3.5 Flash compared: specs, API pricing, context window, VRAM and a clear verdict on which model to choose in 2026.<\/p>","protected":false},"author":1,"featured_media":0,"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":[395,797,798],"class_list":["post-1266","post","type-post","status-publish","format-standard","hentry","category-ai-comparisons","tag-ai-model-comparison","tag-deepseek-v4-flash","tag-gemini-3-5-flash"],"_links":{"self":[{"href":"https:\/\/convly.ai\/pt\/wp-json\/wp\/v2\/posts\/1266","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=1266"}],"version-history":[{"count":0,"href":"https:\/\/convly.ai\/pt\/wp-json\/wp\/v2\/posts\/1266\/revisions"}],"wp:attachment":[{"href":"https:\/\/convly.ai\/pt\/wp-json\/wp\/v2\/media?parent=1266"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/convly.ai\/pt\/wp-json\/wp\/v2\/categories?post=1266"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/convly.ai\/pt\/wp-json\/wp\/v2\/tags?post=1266"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}