{"id":1274,"date":"2026-06-23T14:45:04","date_gmt":"2026-06-23T14:45:04","guid":{"rendered":"https:\/\/convly.ai\/?p=1274"},"modified":"2026-06-23T14:45:04","modified_gmt":"2026-06-23T14:45:04","slug":"mistral-7b-vs-llama-3-1-8b","status":"publish","type":"post","link":"https:\/\/convly.ai\/pt\/mistral-7b-vs-llama-3-1-8b\/","title":{"rendered":"Mistral 7B vs Llama 3.1 8B: Especifica\u00e7\u00f5es, pre\u00e7os e qual escolher (2026)"},"content":{"rendered":"<p><strong>Mistral 7B<\/strong> vs <strong>Llama 3.1 8B<\/strong> \u2014 os cl\u00e1ssicos modelos locais compactos, revisitados. 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, baseada 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\/mistral-7b\/\">Mistral 7B<\/a><\/th><th><a href=\"https:\/\/convly.ai\/pt\/model\/llama-3-1-8b\/\">Llama 3.1 8B<\/a><\/th><\/tr><\/thead>\n    <tbody>\n          <tr><td class=\"cmp-spec\">Desenvolvedor<\/td><td class=\"\">Mistral AI<\/td><td class=\"\">Meta<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Tipo<\/td><td class=\"\">LLM (densa)<\/td><td class=\"\">LLM (densa)<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Par\u00e2metros<\/td><td class=\"\">7B<\/td><td class=\"\">8B<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Janela de contexto<\/td><td class=\"\">32K<\/td><td class=\"cmp-win\">128K<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Modalidade<\/td><td class=\"\">Texto \u2192 Texto<\/td><td class=\"\">Texto \u2192 Texto<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Licen\u00e7a<\/td><td class=\"\">Apache 2.0 (aberta)<\/td><td class=\"\">Llama 3.1 Community (aberta)<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Pesos abertos<\/td><td class=\"\">\u2705 Sim<\/td><td class=\"\">\u2705 Sim<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Pre\u00e7o de entrada (US$\/1 milh\u00e3o)<\/td><td class=\"\">$0.02<\/td><td class=\"\">$0.02<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Pre\u00e7o de sa\u00edda (US$\/1 milh\u00e3o)<\/td><td class=\"\">$0.03<\/td><td class=\"\">$0.03<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">VRAM (4 bits)<\/td><td class=\"\">~4,5 GB<\/td><td class=\"\">~5 GB<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">GPU m\u00ednima (local)<\/td><td class=\"\">Qualquer GPU de 6 GB<\/td><td class=\"\">Qualquer GPU de 8 GB<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">Lan\u00e7ado<\/td><td class=\"\">2023<\/td><td class=\"\">2024<\/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 Mistral 7B e o Llama 3.1 8B t\u00eam pre\u00e7os pr\u00f3ximos, com diferen\u00e7a de cerca de 15%.<\/li><li><strong>Contexto:<\/strong> O Llama 3.1 8B supera o Mistral 7B na janela de contexto (128K vs 32K) \u2014 ideal para documentos longos, grandes bases de c\u00f3digo e entradas extensas em RAG.<\/li><li><strong>Abertura:<\/strong> ambos possuem pesos abertos, portanto podem ser auto-hospedados ou ajustados. Compare suas necessidades de VRAM acima para saber qual GPU pode execut\u00e1-los.<\/li><li><strong>Execute o Mistral 7B localmente:<\/strong> ~~4,5 GB em 4 bits (m\u00ednimo: qualquer GPU de 6 GB).<\/li><li><strong>Execute o Llama 3.1 8B localmente:<\/strong> ~~5 GB em 4 bits (m\u00ednimo: qualquer GPU de 8 GB).<\/li><\/ul>\n  <\/div>\n\n    <div class=\"cmp-rec\">\n    <h3>Qual voc\u00ea deve escolher?<\/h3>\n    <p><strong>Escolha o Mistral 7B<\/strong> se ele se integrar bem \u00e0 sua pilha atual ou se voc\u00ea preferir a Mistral AI.<\/p>\n    <p><strong>Escolha o Llama 3.1 8B<\/strong> se voc\u00ea deseja um custo menor por token para cargas de trabalho de alto volume ou precisa de uma janela de contexto maior.<\/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>Mistral 7B vs Llama 3.1 8B 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":[395,805,809],"class_list":["post-1274","post","type-post","status-publish","format-standard","hentry","category-ai-comparisons","tag-ai-model-comparison","tag-llama-3-1-8b","tag-mistral-7b"],"_links":{"self":[{"href":"https:\/\/convly.ai\/pt\/wp-json\/wp\/v2\/posts\/1274","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=1274"}],"version-history":[{"count":0,"href":"https:\/\/convly.ai\/pt\/wp-json\/wp\/v2\/posts\/1274\/revisions"}],"wp:attachment":[{"href":"https:\/\/convly.ai\/pt\/wp-json\/wp\/v2\/media?parent=1274"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/convly.ai\/pt\/wp-json\/wp\/v2\/categories?post=1274"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/convly.ai\/pt\/wp-json\/wp\/v2\/tags?post=1274"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}