{"id":1278,"date":"2026-06-23T14:45:04","date_gmt":"2026-06-23T14:45:04","guid":{"rendered":"https:\/\/convly.ai\/?p=1278"},"modified":"2026-06-23T14:45:04","modified_gmt":"2026-06-23T14:45:04","slug":"deepseek-v4-pro-vs-deepseek-v4-flash","status":"publish","type":"post","link":"https:\/\/convly.ai\/ar\/deepseek-v4-pro-vs-deepseek-v4-flash\/","title":{"rendered":"DeepSeek V4-Pro vs DeepSeek V4-Flash: Specs, Pricing &#038; Which to Choose (2026)"},"content":{"rendered":"<p><strong>\u062f\u064a\u0628 \u0633\u064a\u0643 \u0641\u064a4-\u0628\u0631\u0648<\/strong> \u0645\u0642\u0627\u0628\u0644 <strong>\u062f\u064a\u0628 \u0633\u064a\u0643 V4-\u0641\u0644\u0634<\/strong> \u2014 DeepSeek&#8217;s flagship versus its budget Flash model. Below is the full side-by-side: specifications, API pricing, context window, local hardware requirements, and a clear, data-driven recommendation on which to pick.<\/p>\n<div class=\"cmp\">\n  <table class=\"cmp-table\">\n    <thead><tr><th>\u0627\u0644\u0645\u0648\u0627\u0635\u0641\u0627\u062a<\/th><th><a href=\"https:\/\/convly.ai\/ar\/model\/deepseek-v4-pro\/\">\u062f\u064a\u0628 \u0633\u064a\u0643 \u0641\u064a4-\u0628\u0631\u0648<\/a><\/th><th><a href=\"https:\/\/convly.ai\/ar\/model\/deepseek-v4-flash\/\">\u062f\u064a\u0628 \u0633\u064a\u0643 V4-\u0641\u0644\u0634<\/a><\/th><\/tr><\/thead>\n    <tbody>\n          <tr><td class=\"cmp-spec\">\u0627\u0644\u0645\u0637\u0648\u0650\u0651\u0631<\/td><td class=\"\">\u062f\u064a\u0628 \u0633\u064a\u0643<\/td><td class=\"\">\u062f\u064a\u0628 \u0633\u064a\u0643<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">\u0627\u0644\u0646\u0648\u0639<\/td><td class=\"\">\u0646\u0645\u0648\u0630\u062c \u0644\u063a\u0648\u064a \u0643\u0628\u064a\u0631 (MoE)<\/td><td class=\"\">\u0646\u0645\u0648\u0630\u062c \u0644\u063a\u0648\u064a \u0643\u0628\u064a\u0631 (MoE)<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">\u0639\u062f\u062f \u0627\u0644\u0645\u064e\u0639\u064e\u0627\u0644\u0650\u0645<\/td><td class=\"\">\u0625\u062c\u0645\u0627\u0644\u064a \u0661,\u0666 \u062a\u0631\u064a\u0644\u064a\u0648\u0646 \u0645\u0639\u0627\u0645\u0644 \/ \u0646\u062d\u0648 \u0664\u0669 \u0645\u0644\u064a\u0627\u0631 \u0645\u0639\u0627\u0645\u0644 \u0646\u0634\u0637 (\u062e\u0644\u064a\u0637 \u0645\u0646 \u0627\u0644\u062e\u0628\u0631\u0627\u0621)<\/td><td class=\"\">\u0625\u062c\u0645\u0627\u0644\u064a 284 \u0645\u0644\u064a\u0627\u0631 \u0645\u0639\u0644\u064e\u0651\u0645\u0629 \/ \u0646\u062d\u0648 13 \u0645\u0644\u064a\u0627\u0631 \u0645\u064f\u0641\u0639\u064e\u0651\u0644\u0629 (MoE)<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">\u0646\u0627\u0641\u0630\u0629 \u0627\u0644\u0633\u064a\u0627\u0642<\/td><td class=\"\">\u0645\u0644\u064a\u0648\u0646 \u0631\u0645\u0632<\/td><td class=\"\">\u0645\u0644\u064a\u0648\u0646 \u0631\u0645\u0632<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">\u0627\u0644\u0646\u0645\u0637\u064a\u0629<\/td><td class=\"\">\u0646\u0635 \u2192 \u0646\u0635<\/td><td class=\"\">\u0646\u0635 \u2192 \u0646\u0635<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">\u0627\u0644\u062a\u0631\u062e\u064a\u0635<\/td><td class=\"\">\u0631\u062e\u0635\u0629 \u0645\u0639\u0647\u062f \u0645\u0627\u0633\u0627\u062a\u0634\u0648\u0633\u062a\u0633 \u0644\u0644\u062a\u0643\u0646\u0648\u0644\u0648\u062c\u064a\u0627 MIT (\u0645\u0641\u062a\u0648\u062d\u0629 \u0627\u0644\u0645\u0635\u062f\u0631)<\/td><td class=\"\">\u0631\u062e\u0635\u0629 \u0645\u0639\u0647\u062f \u0645\u0627\u0633\u0627\u062a\u0634\u0648\u0633\u062a\u0633 \u0644\u0644\u062a\u0643\u0646\u0648\u0644\u0648\u062c\u064a\u0627 MIT (\u0645\u0641\u062a\u0648\u062d\u0629 \u0627\u0644\u0645\u0635\u062f\u0631)<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">\u0623\u0648\u0632\u0627\u0646 \u0645\u0641\u062a\u0648\u062d\u0629 \u0627\u0644\u0645\u0635\u062f\u0631<\/td><td class=\"\">\u2705 \u0646\u0639\u0645<\/td><td class=\"\">\u2705 \u0646\u0639\u0645<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">\u0633\u0639\u0631 \u0627\u0644\u0625\u062f\u062e\u0627\u0644 (\u0628\u0627\u0644\u062f\u0648\u0644\u0627\u0631 \u0644\u0643\u0644 \u0645\u0644\u064a\u0648\u0646 \u0631\u0645\u0632)<\/td><td class=\"\">$0.435<\/td><td class=\"cmp-win\">$0.14<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">\u0633\u0639\u0631 \u0627\u0644\u0625\u062e\u0631\u0627\u062c (\u0628\u0627\u0644\u062f\u0648\u0644\u0627\u0631 \u0644\u0643\u0644 \u0645\u0644\u064a\u0648\u0646 \u0631\u0645\u0632)<\/td><td class=\"\">$0.87<\/td><td class=\"\">$0.28<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">\u0630\u0627\u0643\u0631\u0629 \u0627\u0644\u0641\u064a\u062f\u064a\u0648 VRAM (4 \u0628\u062a)<\/td><td class=\"\">\u0646\u062d\u0648 \u0668\u0660\u0660 \u062c\u064a\u062c\u0627\u0628\u0627\u064a\u062a<\/td><td class=\"\">~140 \u062c\u064a\u062c\u0627\u0628\u0627\u064a\u062a<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">\u062d\u062f \u0623\u062f\u0646\u0649 \u0645\u0646 \u0648\u062d\u062f\u0627\u062a \u0645\u0639\u0627\u0644\u062c\u0629 \u0627\u0644\u0631\u0633\u0648\u0645\u0627\u062a \u0627\u0644\u0645\u0637\u0644\u0648\u0628\u0629 \u0645\u062d\u0644\u064a\u064b\u0651\u0627<\/td><td class=\"\">\u062e\u0627\u062f\u0645 \u0645\u062a\u0639\u062f\u062f \u0627\u0644\u0648\u062d\u062f\u0627\u062a \u0627\u0644\u0631\u0633\u0648\u0645\u064a\u0629 (\u0645\u062b\u0644: \u0668 \u0648\u062d\u062f\u0627\u062a H100 \u0633\u0639\u0629 \u0668\u0660 \u062c\u064a\u062c\u0627\u0628\u0627\u064a\u062a)<\/td><td class=\"\">\u0648\u062d\u062f\u062a\u0627 \u0645\u0639\u0627\u0644\u062c\u0629 \u0631\u0633\u0648\u0645\u064a\u0629 H100 \u0628\u0633\u0639\u0629 80 \u062c\u064a\u062c\u0627\u0628\u0627\u064a\u062a (\u0639\u0646\u062f \u0627\u0644\u062a\u0643\u0645\u064a\u0646 4-\u0628\u062a)<\/td><\/tr>\n          <tr><td class=\"cmp-spec\">\u062a\u0627\u0631\u064a\u062e \u0627\u0644\u0625\u0635\u062f\u0627\u0631<\/td><td class=\"\">2026-04<\/td><td class=\"\">2026-04<\/td><\/tr>\n        <\/tbody>\n  <\/table>\n\n    <div class=\"cmp-verdict\">\n    <h3>\u0623\u0628\u0631\u0632 \u0627\u0644\u0627\u062e\u062a\u0644\u0627\u0641\u0627\u062a<\/h3>\n    <ul><li><strong>\u0627\u0644\u062a\u0643\u0644\u0641\u0629:<\/strong> DeepSeek V4-Flash is <strong>211% cheaper<\/strong> than DeepSeek V4-Pro on a blended-token basis.<\/li><li><strong>\u062f\u0631\u062c\u0629 \u0627\u0644\u0627\u0646\u0641\u062a\u0627\u062d:<\/strong> \u0643\u0644\u0627 \u0627\u0644\u0646\u0645\u0648\u0630\u062c\u064a\u0646 \u064a\u0645\u062a\u0644\u0643\u0627\u0646 \u0623\u0648\u0632\u0627\u0646\u064b\u0627 \u0645\u0641\u062a\u0648\u062d\u0629 \u0627\u0644\u0645\u0635\u062f\u0631\u060c \u0648\u0628\u0627\u0644\u062a\u0627\u0644\u064a \u064a\u0645\u0643\u0646 \u0627\u0633\u062a\u0636\u0627\u0641\u062a\u0647\u0645\u0627 \u0645\u062d\u0644\u064a\u064b\u0651\u0627 \u0623\u0648 \u062a\u062e\u0635\u064a\u0635\u0647\u0645\u0627 \u062d\u0633\u0628 \u0627\u0644\u062d\u0627\u062c\u0629. \u0642\u0627\u0631\u0646 \u0627\u062d\u062a\u064a\u0627\u062c\u0627\u062a\u0647\u0645\u0627 \u0645\u0646 \u0630\u0627\u0643\u0631\u0629 \u0627\u0644\u0641\u064a\u062f\u064a\u0648 VRAM \u0623\u0639\u0644\u0627\u0647 \u0644\u0645\u0639\u0631\u0641\u0629 \u0645\u0627 \u062a\u062f\u0639\u0645\u0647 \u0648\u062d\u062f\u0629 \u0645\u0639\u0627\u0644\u062c\u0629 \u0627\u0644\u0631\u0633\u0648\u0645\u064a\u0627\u062a \u0627\u0644\u062e\u0627\u0635\u0629 \u0628\u0643.<\/li><li><strong>Run DeepSeek V4-Pro locally:<\/strong> ~~800 GB at 4-bit (min Multi-GPU server (e.g. 8\u00d7 H100 80GB)).<\/li><li><strong>Run DeepSeek V4-Flash locally:<\/strong> ~~140 GB at 4-bit (min 2\u00d7 H100 80GB (4-bit)).<\/li><\/ul>\n  <\/div>\n\n    <div class=\"cmp-rec\">\n    <h3>\u0623\u064a\u064f\u0651\u0647\u0627 \u064a\u062c\u0628 \u0623\u0646 \u062a\u062e\u062a\u0627\u0631\u061f<\/h3>\n    <p><strong>Choose DeepSeek V4-Pro<\/strong> if it fits your existing stack or you prefer DeepSeek.<\/p>\n    <p><strong>Choose DeepSeek V4-Flash<\/strong> \u0625\u0630\u0627 \u0643\u0646\u062a \u062a\u0628\u062d\u062b \u0639\u0646 \u0623\u0642\u0644 \u062a\u0643\u0644\u0641\u0629 \u0644\u0643\u0644 \u0631\u0645\u0632 \u0641\u064a \u0645\u0647\u0627\u0645 \u0630\u0627\u062a \u0627\u0644\u062d\u062c\u0645 \u0627\u0644\u0643\u0628\u064a\u0631.<\/p>\n    <p class=\"cmp-tools\">\u2192 \u0642\u062f\u0650\u0651\u0631 \u0627\u0644\u062a\u0643\u0627\u0644\u064a\u0641 \u0627\u0644\u0641\u0639\u0644\u064a\u0629 \u0628\u0627\u0633\u062a\u062e\u062f\u0627\u0645 <a href=\"\/ar\/ai-api-cost-calculator\/\">\u062d\u0627\u0633\u0628\u0629 \u062a\u0643\u0627\u0644\u064a\u0641 \u0648\u0627\u062c\u0647\u0629 \u0628\u0631\u0645\u062c\u0629 \u0627\u0644\u062a\u0637\u0628\u064a\u0642\u0627\u062a API<\/a> \u00b7 \u062a\u062d\u0642\u0642 \u0645\u0646 \u0627\u0644\u0623\u062c\u0647\u0632\u0629 \u0627\u0644\u0645\u062d\u0644\u064a\u0629 \u0628\u0627\u0633\u062a\u062e\u062f\u0627\u0645 <a href=\"\/ar\/llm-vram-calculator\/\">\u062d\u0627\u0633\u0628\u0629 \u0630\u0627\u0643\u0631\u0629 \u0627\u0644\u0641\u064a\u062f\u064a\u0648 VRAM<\/a> \u00b7 \u0627\u0633\u062a\u0639\u0631\u0636 \u062c\u0645\u064a\u0639 <a href=\"\/ar\/models\/\">\u0623\u0643\u062b\u0631 \u0645\u0646 \u0663\u0660 \u0646\u0645\u0648\u0630\u062c\u064b\u0627<\/a>.<\/p>\n  <\/div>\n<\/div>\n\n<p>\u062c\u0645\u064a\u0639 \u0627\u0644\u0645\u0648\u0627\u0635\u0641\u0627\u062a \u0648\u0627\u0644\u0623\u0633\u0639\u0627\u0631 \u0645\u0633\u062a\u062e\u0644\u0635\u0629 \u0645\u0628\u0627\u0634\u0631\u0629\u064b \u0645\u0646 <a href=\"\/ar\/models\/\">\u0642\u0627\u0639\u062f\u0629 \u0628\u064a\u0627\u0646\u0627\u062a \u0646\u0645\u0627\u0630\u062c \u0627\u0644\u0630\u0643\u0627\u0621 \u0627\u0644\u0627\u0635\u0637\u0646\u0627\u0639\u064a<\/a> \u0648\u0645\u064f\u062d\u062f\u064e\u0651\u062b\u0629 \u0628\u0627\u0633\u062a\u0645\u0631\u0627\u0631. \u0642\u0627\u0631\u0646 \u0623\u064a\u064b\u0651\u0627 \u0645\u0646 \u0627\u0644\u0646\u0645\u0648\u0630\u062c\u064a\u0646 \u0645\u0639 \u063a\u064a\u0631\u0647 \u0645\u0646 \u0627\u0644\u0646\u0645\u0627\u0630\u062c\u060c \u0623\u0648 \u0642\u062f\u0650\u0651\u0631 \u0625\u0646\u0641\u0627\u0642\u0643 \u0627\u0644\u0634\u0647\u0631\u064a \u0628\u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0644\u062d\u0627\u0633\u0628\u0627\u062a \u0627\u0644\u0645\u062c\u0627\u0646\u064a\u0629 \u0623\u0639\u0644\u0627\u0647.<\/p>","protected":false},"excerpt":{"rendered":"<p>DeepSeek V4-Pro vs DeepSeek V4-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":[395,797,794],"class_list":["post-1278","post","type-post","status-publish","format-standard","hentry","category-ai-comparisons","tag-ai-model-comparison","tag-deepseek-v4-flash","tag-deepseek-v4-pro"],"_links":{"self":[{"href":"https:\/\/convly.ai\/ar\/wp-json\/wp\/v2\/posts\/1278","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/convly.ai\/ar\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/convly.ai\/ar\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/convly.ai\/ar\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/convly.ai\/ar\/wp-json\/wp\/v2\/comments?post=1278"}],"version-history":[{"count":0,"href":"https:\/\/convly.ai\/ar\/wp-json\/wp\/v2\/posts\/1278\/revisions"}],"wp:attachment":[{"href":"https:\/\/convly.ai\/ar\/wp-json\/wp\/v2\/media?parent=1278"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/convly.ai\/ar\/wp-json\/wp\/v2\/categories?post=1278"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/convly.ai\/ar\/wp-json\/wp\/v2\/tags?post=1278"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}