{"id":20952,"date":"2026-10-21T11:09:40","date_gmt":"2026-10-21T15:09:40","guid":{"rendered":"https:\/\/wp.glbgpt.com\/?p=20952"},"modified":"2026-10-21T11:09:41","modified_gmt":"2026-10-21T15:09:41","slug":"mai-image-2-6-vs-flash","status":"publish","type":"post","link":"https:\/\/wp.glbgpt.com\/fr\/hub\/mai-image-2-6-vs-flash","title":{"rendered":"MAI Image 2.6 vs Flash : comparaison des tarifs, des performances et de la vitesse"},"content":{"rendered":"<p class=\"wp-block-paragraph\"><strong>MAI-Image-2.6 vs Flash comes down to how much you value a stronger first result over cheaper, faster iteration.<\/strong> MAI-Image-2.6-Flash has a representative API price of <strong>$19.50 per 1,000 images<\/strong>, par rapport \u00e0 <strong>$38.90<\/strong> for MAI-Image-2.6 on <a href=\"https:\/\/artificialanalysis.ai\/image\/leaderboard\/editing\">Artificial Analysis\u2019s image-editing leaderboard<\/a>. In Microsoft\u2019s internal 1024 \u00d7 1024 load test, Flash\u2019s median response was <strong>12.2 seconds<\/strong>, par rapport \u00e0 <strong>25.6 seconds<\/strong> for the standard model.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The standard model still has the stronger text-to-image preference score. Flash is the more attractive starting point for repeated edits and high-volume creative work, while MAI-Image-2.6 deserves a look when typography, composition, and a polished final image matter more than turnaround. Figures below were checked on <strong>October 21, 2026<\/strong>; published load-test results and current leaderboard scores have different measurement scopes.<\/p>\n\n\n\n<section aria-label=\"R\u00e9ponse rapide\" style=\"box-sizing:border-box;margin:28px 0;padding:clamp(18px,4vw,30px);border:1px solid #d6e2dc;border-radius:20px;background:#f2f6f4;color:#18352d;font-family:system-ui,sans-serif;line-height:1.55;overflow-wrap:anywhere\"><p style=\"margin:0 0 16px;font-size:13px;font-weight:700;letter-spacing:.08em\">R\u00c9PONSE RAPIDE<\/p><div style=\"display:flex;flex-wrap:wrap;gap:16px\"><div style=\"box-sizing:border-box;flex:1 1 220px;min-width:0;padding:22px;border-radius:14px;background:#e8f0eb\"><div style=\"font-size:14px;font-weight:700\">Lower representative cost<\/div><div style=\"font-size:clamp(26px,4vw,38px);font-weight:750;margin:8px 0;line-height:1.2\">Flash<\/div><div style=\"font-size:14px\">$19.50 \/ 1,000 images \u00b7 about half the standard model\u2019s listed cost<\/div><\/div><div style=\"box-sizing:border-box;flex:1 1 220px;min-width:0;padding:22px;border-radius:14px;background:#eef0fa\"><div style=\"font-size:14px;font-weight:700\">Faster published median<\/div><div style=\"font-size:clamp(26px,4vw,38px);font-weight:750;margin:8px 0;line-height:1.2\">12.2s<\/div><div style=\"font-size:14px\">Flash vs 25.6s for standard \u00b7 Microsoft internal load test<\/div><\/div><div style=\"box-sizing:border-box;flex:1 1 220px;min-width:0;padding:22px;border-radius:14px;background:#f8eae3\"><div style=\"font-size:14px;font-weight:700\">Higher generation score<\/div><div style=\"font-size:clamp(26px,4vw,38px);font-weight:750;margin:8px 0;line-height:1.2\">Standard<\/div><div style=\"font-size:14px\">1166 vs 1119 Elo \u00b7 AA-Image-T2I v2.1 overall<\/div><\/div><\/div><p style=\"font-size:13px;line-height:1.6;margin:18px 0 0\">Price and quality: <a href=\"https:\/\/artificialanalysis.ai\/image\/leaderboard\/text-to-image\">Analyse artificielle<\/a>. Speed: <a href=\"https:\/\/microsoft.ai\/news\/pushing-the-quality-cost-frontier-with-mai-image-2-6\/\">Microsoft\u2019s published test<\/a>. These are source-reported figures; no new same-prompt model test was run for this comparison.<\/p><\/section>\n\n\n\n<div class=\"wp-block-group is-layout-constrained wp-block-group-is-layout-constrained\">\n<figure class=\"wp-block-image size-large\"><a href=\"https:\/\/www.glbgpt.com\/image-edit?inviter=hub_content_image_edit&amp;login=1\"><img alt=\"\" fetchpriority=\"high\" decoding=\"async\" width=\"1024\" height=\"710\" src=\"https:\/\/wp.glbgpt.com\/wp-content\/uploads\/2026\/03\/image-832-1024x710.png\" class=\"wp-image-20547\" srcset=\"https:\/\/wp.glbgpt.com\/wp-content\/uploads\/2026\/03\/image-832-1024x710.png 1024w, https:\/\/wp.glbgpt.com\/wp-content\/uploads\/2026\/03\/image-832-300x208.png 300w, https:\/\/wp.glbgpt.com\/wp-content\/uploads\/2026\/03\/image-832-17x12.png 17w, https:\/\/wp.glbgpt.com\/wp-content\/uploads\/2026\/03\/image-832-767x532.png 767w, https:\/\/wp.glbgpt.com\/wp-content\/uploads\/2026\/03\/image-832-1536x1065.png 1536w, https:\/\/wp.glbgpt.com\/wp-content\/uploads\/2026\/03\/image-832-2048x1420.png 2048w\" sizes=\"(max-width: 1024px) 100vw, 1024px\" \/><\/a><\/figure>\n\n\n\n<div class=\"wp-block-buttons is-content-justification-center is-layout-flex wp-container-core-buttons-is-layout-3e41869c wp-block-buttons-is-layout-flex\">\n<div class=\"wp-block-button\"><a class=\"wp-block-button__link has-background wp-element-button\" href=\"https:\/\/www.glbgpt.com\/image-edit?inviter=hub_content_image_edit&amp;login=1\" style=\"background:linear-gradient(312deg,rgb(255,245,203) 0%,rgb(182,227,212) 26%,rgb(51,167,181) 100%)\">Rendez votre image nette d\u00e8s maintenant<\/a><\/div>\n<\/div>\n<\/div>\n\n\n\n<section aria-label=\"Sommaire\" style=\"box-sizing:border-box;margin:28px 0;padding:clamp(18px,4vw,30px);border:1px solid #d6e2dc;border-radius:20px;background:#f2f6f4;color:#18352d;font-family:system-ui,sans-serif;line-height:1.55;overflow-wrap:anywhere\"><nav aria-label=\"Sommaire de l&#039;article\"><p style=\"margin:0 0 14px;font-weight:700;letter-spacing:.06em;font-size:13px\">CONTENTS<\/p><div style=\"display:flex;flex-wrap:wrap;gap:10px\"><a href=\"#at-a-glance\" style=\"box-sizing:border-box;flex:1 1 260px;min-width:0;display:block;padding:12px 14px;border-radius:10px;text-decoration:none;background:#e2eee7;color:#254438;font-size:14px\"><strong>01<\/strong> &nbsp;MAI-Image-2.6 vs Flash at a glance<\/a><a href=\"#pricing\" style=\"box-sizing:border-box;flex:1 1 260px;min-width:0;display:block;padding:12px 14px;border-radius:10px;text-decoration:none;background:#f0e8ed;color:#254438;font-size:14px\"><strong>02<\/strong> &nbsp;Pricing: roughly half the representative image cost<\/a><a href=\"#benchmarks\" style=\"box-sizing:border-box;flex:1 1 260px;min-width:0;display:block;padding:12px 14px;border-radius:10px;text-decoration:none;background:#e2eee7;color:#254438;font-size:14px\"><strong>03<\/strong> &nbsp;Benchmarks: a clearer generation gap, a closer editing contest<\/a><a href=\"#speed\" style=\"box-sizing:border-box;flex:1 1 260px;min-width:0;display:block;padding:12px 14px;border-radius:10px;text-decoration:none;background:#f0e8ed;color:#254438;font-size:14px\"><strong>04<\/strong> &nbsp;Speed: Flash is about 2.1\u00d7 faster than standard in Microsoft\u2019s test<\/a><a href=\"#capabilities\" style=\"box-sizing:border-box;flex:1 1 260px;min-width:0;display:block;padding:12px 14px;border-radius:10px;text-decoration:none;background:#e2eee7;color:#254438;font-size:14px\"><strong>05<\/strong> &nbsp;What both models can do\u2014and where the work still needs review<\/a><a href=\"#comparison-prompts\" style=\"box-sizing:border-box;flex:1 1 260px;min-width:0;display:block;padding:12px 14px;border-radius:10px;text-decoration:none;background:#f0e8ed;color:#254438;font-size:14px\"><strong>06<\/strong> &nbsp;Two prompts for a useful side-by-side comparison<\/a><a href=\"#access\" style=\"box-sizing:border-box;flex:1 1 260px;min-width:0;display:block;padding:12px 14px;border-radius:10px;text-decoration:none;background:#e2eee7;color:#254438;font-size:14px\"><strong>07<\/strong> &nbsp;Where to use the models: Playground, Foundry, and comparison workflows<\/a><a href=\"#which-to-choose\" style=\"box-sizing:border-box;flex:1 1 260px;min-width:0;display:block;padding:12px 14px;border-radius:10px;text-decoration:none;background:#f0e8ed;color:#254438;font-size:14px\"><strong>08<\/strong> &nbsp;Lequel choisir ?<\/a><a href=\"#faq\" style=\"box-sizing:border-box;flex:1 1 260px;min-width:0;display:block;padding:12px 14px;border-radius:10px;text-decoration:none;background:#e2eee7;color:#254438;font-size:14px\"><strong>09<\/strong> &nbsp;Foire aux questions<\/a><\/div><\/nav><\/section>\n\n\n\n<h2 id=\"at-a-glance\" class=\"wp-block-heading\">MAI-Image-2.6 vs Flash at a glance<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">\u201cFlash\u201d here means <strong>MAI-Image-2.6-Flash<\/strong>, Microsoft\u2019s faster variant of MAI-Image-2.6. It does not mean a Gemini Flash model or the older MAI-Image-2.5-Flash. Microsoft lists both 2.6 models as <strong>preview<\/strong> deployments with model version <strong>2026-07-31<\/strong> in its <a href=\"https:\/\/learn.microsoft.com\/en-us\/azure\/foundry\/foundry-models\/how-to\/use-foundry-models-mai-image\">Foundry deployment documentation<\/a>. That version label is separate from the public announcement date.<\/p>\n\n\n\n<section aria-label=\"Shared capabilities\" style=\"box-sizing:border-box;margin:28px 0;padding:clamp(18px,4vw,30px);border:1px solid #d6e2dc;border-radius:20px;background:#f2f6f4;color:#18352d;font-family:system-ui,sans-serif;line-height:1.55;overflow-wrap:anywhere\"><div style=\"display:flex;flex-wrap:wrap;gap:16px\"><div style=\"box-sizing:border-box;flex:1 1 220px;min-width:0;padding:22px;border-radius:14px;background:#e8f0eb\"><div style=\"font-size:14px;font-weight:700\">Cr\u00e9ation + \u00e9dition<\/div><div style=\"font-size:clamp(26px,4vw,38px);font-weight:750;margin:8px 0;line-height:1.2\">Both models<\/div><div style=\"font-size:14px\">Text-to-image and image-to-image workflows<\/div><\/div><div style=\"box-sizing:border-box;flex:1 1 220px;min-width:0;padding:22px;border-radius:14px;background:#f5eee2\"><div style=\"font-size:14px;font-weight:700\">Images de r\u00e9f\u00e9rence<\/div><div style=\"font-size:clamp(26px,4vw,38px);font-weight:750;margin:8px 0;line-height:1.2\">Jusqu'\u00e0 5<\/div><div style=\"font-size:14px\">JPEG or PNG references for editing<\/div><\/div><div style=\"box-sizing:border-box;flex:1 1 220px;min-width:0;padding:22px;border-radius:14px;background:#e8edf8\"><div style=\"font-size:14px;font-weight:700\">Maximum output area<\/div><div style=\"font-size:clamp(26px,4vw,38px);font-weight:750;margin:8px 0;line-height:1.2\">2.36 MP<\/div><div style=\"font-size:14px\">2,359,296 pixels \u00b7 equivalent to 1536 \u00d7 1536<\/div><\/div><div style=\"box-sizing:border-box;flex:1 1 220px;min-width:0;padding:22px;border-radius:14px;background:#f5e9e5\"><div style=\"font-size:14px;font-weight:700\">Images per response<\/div><div style=\"font-size:clamp(26px,4vw,38px);font-weight:750;margin:8px 0;line-height:1.2\">1<\/div><div style=\"font-size:14px\">PNG output \u00b7 dimensions remain within the documented pixel limit<\/div><\/div><\/div><p style=\"font-size:13px;line-height:1.6;margin:18px 0 0\">Source : <a href=\"https:\/\/learn.microsoft.com\/en-us\/azure\/foundry\/foundry-models\/concepts\/models-sold-directly-by-azure\">Microsoft\u2019s model specifications<\/a>. A dimension may exceed 1536 pixels if the total area stays within the limit; the documentation specifies a 768 \u00d7 768 minimum.<\/p><\/section>\n\n\n\n<p class=\"wp-block-paragraph\">The useful distinction is the quality, cost, and latency tradeoff. Microsoft describes Flash as offering the same generation and editing capabilities at lower cost and faster speed. That does not establish that every output will look identical. If you are comparing beyond this pair, our <a href=\"https:\/\/www.glbgpt.com\/hub\/best-ai-image-generators\/\">Comparatif des g\u00e9n\u00e9rateurs d'images bas\u00e9s sur l'IA<\/a> covers the broader choice of creative tools.<\/p>\n\n\n\n<h2 id=\"pricing\" class=\"wp-block-heading\">Pricing: roughly half the representative image cost<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">For a practical comparison, the current Artificial Analysis tables list <strong>$38.90 per 1,000 images<\/strong> for MAI-Image-2.6 and <strong>$19.50<\/strong> for Flash. Artificial Analysis defines its pricing basis as the model creator\u2019s API at <strong>1024 \u00d7 1024 with default settings<\/strong>. Microsoft\u2019s own <a href=\"https:\/\/microsoft.ai\/news\/pushing-the-quality-cost-frontier-with-mai-image-2-6\/\">quality\u2013price chart<\/a> uses the same representative values. Those work out to <strong>$0.0389<\/strong> et <strong>$0,0195 par image<\/strong> for that benchmark cost basis.<\/p>\n\n\n\n<section aria-label=\"Representative API cost\" style=\"box-sizing:border-box;margin:28px 0;padding:clamp(18px,4vw,30px);border:1px solid #d6e2dc;border-radius:20px;background:#f2f6f4;color:#18352d;font-family:system-ui,sans-serif;line-height:1.55;overflow-wrap:anywhere\"><div style=\"display:flex;flex-wrap:wrap;gap:16px\"><div style=\"box-sizing:border-box;flex:1 1 220px;min-width:0;padding:22px;border-radius:14px;background:#ececf8\"><div style=\"font-size:14px;font-weight:700\">MAI-Image-2.6<\/div><div style=\"font-size:clamp(26px,4vw,38px);font-weight:750;margin:8px 0;line-height:1.2\">$38.90<\/div><div style=\"font-size:14px\">Per 1,000 images \u00b7 equivalent $0.0389 \/ image<\/div><\/div><div style=\"box-sizing:border-box;flex:1 1 220px;min-width:0;padding:22px;border-radius:14px;background:#dfeee6\"><div style=\"font-size:14px;font-weight:700\">MAI-Image-2.6-Flash<\/div><div style=\"font-size:clamp(26px,4vw,38px);font-weight:750;margin:8px 0;line-height:1.2\">$19.50<\/div><div style=\"font-size:14px\">Per 1,000 images \u00b7 equivalent $0.0195 \/ image<\/div><\/div><\/div><div style=\"margin-top:24px\"><p style=\"margin:0 0 8px;font-weight:700\">10,000-image planning example<\/p><div style=\"padding:12px 0\">Standard <strong>$389<\/strong><div style=\"height:18px;margin-top:6px;background:#7480b8;border-radius:5px;width:100%\"><\/div><\/div><div style=\"padding:12px 0\">Flash <strong>$195<\/strong><div style=\"height:18px;margin-top:6px;background:#247455;border-radius:5px;width:50.13%\"><\/div><\/div><\/div><p style=\"font-size:13px;line-height:1.6;margin:18px 0 0\">Calculation: listed cost per 1,000 images \u00d7 10. Flash saves $194, or about 49.9%, in this fixed-cost example. <a href=\"https:\/\/artificialanalysis.ai\/image\/leaderboard\/editing\">Source and pricing basis<\/a>; checked October 21, 2026. This is a spending estimate, not an audited account charge.<\/p><\/section>\n\n\n\n<p class=\"wp-block-paragraph\">Keep three prices separate: the benchmark\u2019s representative API cost, your Azure deployment\u2019s actual charges, and any third-party subscription or credit allowance. Dimensions, reference inputs, request features, and your billing terms can affect the bill. The <a href=\"https:\/\/azure.microsoft.com\/en-us\/pricing\/details\/ai-foundry-models\/microsoft\/\">official Microsoft model-pricing page<\/a> is the place to confirm the applicable rate for your deployment; a leaderboard equivalent is not a universal flat price for every request.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Retries change the economics. At the listed equivalents, two Flash outputs cost $0.0390, almost the same as one standard output at $0.0389. Flash is cheaper per attempt; whether it is cheaper per approved asset depends on how many attempts you need. Count the successful deliverables, not just the generated files.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">If price is your main filter, the separate <a href=\"https:\/\/www.glbgpt.com\/hub\/agnes-image-2-1-flash-pricing\/\">Agnes Image 2.1 Flash pricing breakdown<\/a> offers another model and billing comparison. Its prices belong to that model and route, so they should not be applied to MAI.<\/p>\n\n\n\n<h2 id=\"benchmarks\" class=\"wp-block-heading\">Benchmarks: a clearer generation gap, a closer editing contest<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Le courant <a href=\"https:\/\/artificialanalysis.ai\/image\/leaderboard\/text-to-image\">AA-Image-T2I v2.1 overall leaderboard<\/a> gives MAI-Image-2.6 <strong>1166 \u00b112 Elo<\/strong> and Flash <strong>1119 \u00b112<\/strong>. Their displayed positions are fifth and tenth. These scores come from pairwise human preference votes, so they describe aggregate image preference rather than a percentage of prompts answered correctly.<\/p>\n\n\n\n<section aria-label=\"Current benchmark comparison\" style=\"box-sizing:border-box;margin:28px 0;padding:clamp(18px,4vw,30px);border:1px solid #d6e2dc;border-radius:20px;background:#f2f6f4;color:#18352d;font-family:system-ui,sans-serif;line-height:1.55;overflow-wrap:anywhere\"><p style=\"margin:0 0 18px;font-size:13px;font-weight:700;letter-spacing:.08em\">ARTIFICIAL ANALYSIS \u00b7 OCTOBER 21, 2026<\/p><div style=\"display:flex;flex-wrap:wrap;gap:16px\"><div style=\"box-sizing:border-box;flex:1 1 220px;min-width:0;padding:22px;border-radius:14px;background:#e7eafb\"><div style=\"font-size:14px;font-weight:700\">Text to image \u00b7 standard leads<\/div><div style=\"font-size:clamp(26px,4vw,38px);font-weight:750;margin:8px 0;line-height:1.2\">1166 vs 1119<\/div><div style=\"font-size:14px\">MAI-Image-2.6 \u00b112 \u00b7 Flash \u00b112; displayed ranks 5 and 10<\/div><\/div><div style=\"box-sizing:border-box;flex:1 1 220px;min-width:0;padding:22px;border-radius:14px;background:#e1f1e7\"><div style=\"font-size:14px;font-weight:700\">Image editing \u00b7 close scores<\/div><div style=\"font-size:clamp(26px,4vw,38px);font-weight:750;margin:8px 0;line-height:1.2\">1151 vs 1143<\/div><div style=\"font-size:14px\">MAI-Image-2.6 \u00b112 \u00b7 Flash \u00b113; displayed ranks 4 and 6<\/div><\/div><\/div><p style=\"font-size:13px;line-height:1.6;margin:18px 0 0\">Overall scores and 95% intervals from <a href=\"https:\/\/artificialanalysis.ai\/image\/leaderboard\/text-to-image\">AA-Image-T2I v2.1<\/a> et <a href=\"https:\/\/artificialanalysis.ai\/image\/leaderboard\/editing\">AA-Image-Editing v2.1<\/a>. Each benchmark has its own scale; compare models within the same benchmark.<\/p><\/section>\n\n\n\n<figure style=\"margin:28px 0\"><img decoding=\"async\" src=\"https:\/\/static.futureshareai.com\/glb_features\/mcp\/4\/mai-image-2-6-vs-flash-aa-text-to-image_2c638057ad5b4036911b2dbc9e3ac986.webp\" alt=\"Artificial Analysis AA-Image-T2I v2.1 leaderboard showing MAI-Image-2.6 at 1166 Elo and Flash at 1119 Elo\" style=\"display:block;width:100%;height:auto;border:1px solid #d9e0dc;border-radius:12px\" loading=\"lazy\"\/><figcaption style=\"font-size:13px;line-height:1.6;margin-top:10px\">Artificial Analysis, AA-Image-T2I v2.1 overall leaderboard, captured October 21, 2026. Scores, intervals, model identities, and representative API prices remain visible.<\/figcaption><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\">Editing looks much closer. The <a href=\"https:\/\/artificialanalysis.ai\/image\/leaderboard\/editing\">AA-Image-Editing v2.1 overall leaderboard<\/a> listes <strong>1151 \u00b112<\/strong> for standard and <strong>1143 \u00b113<\/strong> for Flash. Their 95% intervals overlap. The eight-point difference is a reason to test your actual editing task, not a basis for claiming an obvious winner on every edit.<\/p>\n\n\n\n<figure style=\"margin:28px 0\"><img decoding=\"async\" src=\"https:\/\/static.futureshareai.com\/glb_features\/mcp\/4\/mai-image-2-6-vs-flash-aa-editing_cfdebb01704840cf855dbe0a80a78079.webp\" alt=\"Artificial Analysis AA-Image-Editing v2.1 leaderboard showing 1151 Elo for MAI-Image-2.6 and 1143 for Flash\" style=\"display:block;width:100%;height:auto;border:1px solid #d9e0dc;border-radius:12px\" loading=\"lazy\"\/><figcaption style=\"font-size:13px;line-height:1.6;margin-top:10px\">Artificial Analysis, AA-Image-Editing v2.1 overall leaderboard, captured October 21, 2026. The displayed uncertainty ranges overlap for the two MAI models.<\/figcaption><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\">Older launch claims need their dates. In its September 4 announcement, Microsoft reported standard MAI-Image-2.6 at No. 2 for generation and No. 1 for editing on Artificial Analysis. The same announcement reports No. 2 on Arena for both tasks. Those are <a href=\"https:\/\/microsoft.ai\/news\/pushing-the-quality-cost-frontier-with-mai-image-2-6\/\">September 4, 2026 rankings<\/a>, not the October 21 positions above. Arena and Artificial Analysis also run separate leaderboards; their Elo values should not be combined.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Microsoft\u2019s earlier <a href=\"https:\/\/microsoft.ai\/news\/mai-image-2-6-launches-at-no-2-on-arena-ahead-of-google-meta-and-xai\/\">August 10 launch post<\/a> reports a 79-point overall Arena gain and a 91-point text-rendering gain over MAI-Image-2.5. Those improvements compare 2.6 with 2.5, not 2.6 with Flash. They help explain the newer model\u2019s focus, but do not quantify the quality sacrificed by choosing Flash.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The current leaderboards also include newer GPT Image 2.5 variants. Our <a href=\"https:\/\/www.glbgpt.com\/hub\/chatgpt-images-2-5-review\/\">Test du ChatGPT Images 2.5<\/a> is a useful next comparison if you want to weigh the MAI pair against that model family. A model\u2019s leaderboard result and the features of a consumer image app remain separate questions.<\/p>\n\n\n\n<h2 id=\"speed\" class=\"wp-block-heading\">Speed: Flash is about 2.1\u00d7 faster than standard in Microsoft\u2019s test<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Microsoft publishes an internal load test at <strong>100 requests per minute and 1024 \u00d7 1024 resolution<\/strong>. The chart reports median response time and a band extending to the 90th percentile. Flash\u2019s median is <strong>12.2 seconds<\/strong>, standard\u2019s is <strong>25.6 seconds<\/strong>, and GPT-Image-2-Medium\u2019s is <strong>33.6 seconds<\/strong>. See the <a href=\"https:\/\/microsoft.ai\/news\/pushing-the-quality-cost-frontier-with-mai-image-2-6\/\">original test and its conditions<\/a>.<\/p>\n\n\n\n<section aria-label=\"Published response time comparison\" style=\"box-sizing:border-box;margin:28px 0;padding:clamp(18px,4vw,30px);border:1px solid #d6e2dc;border-radius:20px;background:#f2f6f4;color:#18352d;font-family:system-ui,sans-serif;line-height:1.55;overflow-wrap:anywhere\"><p style=\"font-weight:700;font-size:21px;margin:0 0 6px\">Published response time \u00b7 lower is better<\/p><p style=\"font-size:13px;margin:0 0 22px\">Microsoft internal test \u00b7 1024 \u00d7 1024 \u00b7 100 RPM<\/p><div style=\"margin:18px 0\"><div style=\"display:flex;justify-content:space-between;gap:10px;flex-wrap:wrap;font-size:14px\"><strong>MAI-Image-2.6-Flash<\/strong><span>Median 12.2s \u00b7 P90 13.5s<\/span><\/div><div style=\"position:relative;background:#e1e5e2;height:22px;border-radius:5px;margin-top:8px\"><div style=\"width:33.75%;height:22px;position:absolute;top:0;left:0;background:#287555;opacity:.35;border-radius:5px\"><\/div><div style=\"width:30.5%;height:22px;position:absolute;top:0;left:0;background:#287555;border-radius:5px\"><\/div><\/div><\/div><div style=\"margin:18px 0\"><div style=\"display:flex;justify-content:space-between;gap:10px;flex-wrap:wrap;font-size:14px\"><strong>MAI-Image-2.6<\/strong><span>Median 25.6s \u00b7 P90 27.8s<\/span><\/div><div style=\"position:relative;background:#e1e5e2;height:22px;border-radius:5px;margin-top:8px\"><div style=\"width:69.5%;height:22px;position:absolute;top:0;left:0;background:#7381b2;opacity:.35;border-radius:5px\"><\/div><div style=\"width:64%;height:22px;position:absolute;top:0;left:0;background:#7381b2;border-radius:5px\"><\/div><\/div><\/div><div style=\"margin:18px 0\"><div style=\"display:flex;justify-content:space-between;gap:10px;flex-wrap:wrap;font-size:14px\"><strong>GPT-Image-2-Medium<\/strong><span>Median 33.6s \u00b7 P90 37.5s<\/span><\/div><div style=\"position:relative;background:#e1e5e2;height:22px;border-radius:5px;margin-top:8px\"><div style=\"width:93.75%;height:22px;position:absolute;top:0;left:0;background:#9a765b;opacity:.35;border-radius:5px\"><\/div><div style=\"width:84.00000000000001%;height:22px;position:absolute;top:0;left:0;background:#9a765b;border-radius:5px\"><\/div><\/div><\/div><p style=\"margin:18px 0 0;font-size:12px\">0s \u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500\u2500 40s \u00b7 solid: median; pale extension: to P90<\/p><p style=\"font-size:13px;line-height:1.6;margin:18px 0 0\">Source : <a href=\"https:\/\/microsoft.ai\/news\/pushing-the-quality-cost-frontier-with-mai-image-2-6\/\">Microsoft\u2019s published load-test chart<\/a>. Replotted from source values; no new model timing measured. Prompt and load affect latency.<\/p><\/section>\n\n\n\n<figure style=\"margin:28px 0\"><img decoding=\"async\" src=\"https:\/\/static.futureshareai.com\/glb_features\/mcp\/4\/mai-image-2-6-vs-flash-microsoft-speed_cc86464084d64343b9bf71a6d05916bd.webp\" alt=\"Microsoft internal 1024 by 1024 load-test chart comparing Flash, MAI-Image-2.6 and GPT-Image-2-Medium median and P90 response times\" style=\"display:block;width:100%;height:auto;border:1px solid #d9e0dc;border-radius:12px\" loading=\"lazy\"\/><figcaption style=\"font-size:13px;line-height:1.6;margin-top:10px\">Microsoft AI\u2019s published internal load test: 100 RPM at 1024 \u00d7 1024; median response time with a band to P90. Captured October 21, 2026. This is provider-reported testing.<\/figcaption><\/figure>\n\n\n\n<p class=\"wp-block-paragraph\">Within that test, 25.6 \u00f7 12.2 is about <strong>2.1\u00d7<\/strong>: Flash takes roughly 52% less median response time than standard. The headline <strong>\u201c2.8\u00d7 faster\u201d<\/strong> uses GPT-Image-2-Medium as the baseline, because 33.6 \u00f7 12.2 is about 2.8. It should not be presented as Flash\u2019s advantage over MAI-Image-2.6.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">The tail matters too: Flash\u2019s P90 is 13.5 seconds versus 27.8 seconds for standard. That makes Flash appealing for an interactive workflow where users repeatedly wait for an edit. These figures are response times under the published load, not a promised Playground wait time, a per-account rate limit, or a measured maximum throughput.<\/p>\n\n\n\n<h2 id=\"capabilities\" class=\"wp-block-heading\">What both models can do\u2014and where the work still needs review<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">Les deux soutiennent <strong>multi-reference editing, web grounding, and dynamic aspect ratios<\/strong>, selon <a href=\"https:\/\/microsoft.ai\/news\/pushing-the-quality-cost-frontier-with-mai-image-2-6\/\">Microsoft\u2019s family announcement<\/a>. A faster model does not automatically lose reference-image editing. You can compare the same kind of creative workflow across both, provided you keep the input files, dimensions, and relevant controls consistent.<\/p>\n\n\n\n<section aria-label=\"Creative workflow map\" style=\"box-sizing:border-box;margin:28px 0;padding:clamp(18px,4vw,30px);border:1px solid #d6e2dc;border-radius:20px;background:#f2f6f4;color:#18352d;font-family:system-ui,sans-serif;line-height:1.55;overflow-wrap:anywhere\"><div style=\"display:flex;gap:14px;flex-wrap:wrap\"><div style=\"flex:1 1 190px;min-width:0;border-top:4px solid #4e8b70;padding:16px;background:#fff;border-radius:10px\"><strong style=\"color:#6d7c9c;font-size:26px\">01<\/strong><p style=\"font-weight:700;margin:8px 0\">Bring references<\/p><p style=\"font-size:14px;margin:0\">Product \u00b7 person \u00b7 style<\/p><\/div><div style=\"flex:1 1 190px;min-width:0;border-top:4px solid #4e8b70;padding:16px;background:#fff;border-radius:10px\"><strong style=\"color:#6d7c9c;font-size:26px\">02<\/strong><p style=\"font-weight:700;margin:8px 0\">Fix the brief<\/p><p style=\"font-size:14px;margin:0\">Text \u00b7 layout \u00b7 dimensions<\/p><\/div><div style=\"flex:1 1 190px;min-width:0;border-top:4px solid #4e8b70;padding:16px;background:#fff;border-radius:10px\"><strong style=\"color:#6d7c9c;font-size:26px\">03<\/strong><p style=\"font-weight:700;margin:8px 0\">Compare outputs<\/p><p style=\"font-size:14px;margin:0\">Preservation \u00b7 accuracy \u00b7 time<\/p><\/div><\/div><p style=\"font-size:13px;line-height:1.6;margin:18px 0 0\">Workflow guidance. This diagram is an editorial explanation, not a model-generated result or measured performance score.<\/p><\/section>\n\n\n\n<p class=\"wp-block-paragraph\">For product work, inspect the bottle shape, label spelling, material, and shadow after every change. For portraits, compare identity and small facial details. For web-grounded images, verify factual labels and depicted details independently: grounding adds context, but a generated picture is not documentary evidence.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Le <a href=\"https:\/\/www.glbgpt.com\/hub\/globalgpt-image-edit\/\">GlobalGPT image-editing workflow examples<\/a> can help you separate a targeted edit from a complete restyle. That distinction matters when you judge whether an image model preserved the parts of the source you wanted to keep.<\/p>\n\n\n\n<h2 id=\"comparison-prompts\" class=\"wp-block-heading\">Two prompts for a useful side-by-side comparison<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\">A leaderboard narrows the shortlist; your brief decides the purchase. Use identical prompts for the two models and record every attempt, including failed or rejected outputs. The prompts below are <strong>suggested evaluation inputs<\/strong>. They are not accompanied by new MAI-generated results in this comparison.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">1. Check exact text and the overall composition<\/h3>\n\n\n\n<section aria-label=\"Typography + composition prompt\" style=\"box-sizing:border-box;margin:28px 0;padding:24px;border-radius:18px;background:#17362e;color:#f3f8f5;font-family:system-ui,sans-serif;overflow-wrap:anywhere\"><p style=\"margin:0 0 10px;font-size:12px;letter-spacing:.08em;color:#badacb\">COMPARISON PROMPT \u00b7 TYPOGRAPHY + COMPOSITION<\/p><pre id=\"typography-prompt\" data-value contenteditable=\"true\" role=\"textbox\" aria-label=\"Typography + composition prompt text\" tabindex=\"0\" style=\"margin:0;white-space:pre-wrap;overflow-wrap:anywhere;font:15px\/1.7 ui-monospace,Consolas,monospace;color:inherit;outline-offset:6px\">Create a square studio product photograph of a matte cobalt-blue water bottle.\nPlace the bottle on a warm ivory pedestal, with soft light from the left and a natural shadow to the right.\nPrint exactly these three lines on the bottle:\nNORTHLINE\n750 ml\nTAKE THE LONG WAY\nKeep the lettering straight, legible, and spelled exactly. No extra words, logos, or watermarks.<\/pre><div style=\"display:flex;gap:12px;align-items:center;flex-wrap:wrap;margin-top:16px\"><button type=\"button\" data-copy style=\"padding:10px 16px;border:1px solid #a6ccba;border-radius:9px;background:#d6ecdf;color:#12362b;cursor:pointer;font:600 14px system-ui\">Copier l'invite<\/button><span role=\"status\" style=\"font-size:13px\">Select the text to copy manually.<\/span><\/div><\/section><script>(function(){const root=document.currentScript.previousElementSibling;root.querySelector('[data-copy]').addEventListener('click',async()=>{const field=root.querySelector('[data-value]'),status=root.querySelector('[role=\"status\"]'),value=field.textContent;try{if(!navigator.clipboard)throw Error();await Promise.race([navigator.clipboard.writeText(value),new Promise((_,r)=>setTimeout(()=>r(Error()),800))]);status.textContent='Copied.';}catch(e){field.focus();const range=document.createRange();range.selectNodeContents(field);const s=window.getSelection();s.removeAllRanges();s.addRange(range);status.textContent='Selected. Press Ctrl\/Cmd+C.';}});})();<\/script>\n\n\n\n<p class=\"wp-block-paragraph\">Compare all three lines character by character, then inspect alignment, reflections, and whether the requested shadow survived. Do not award a pass just because the image looks attractive at thumbnail size. The <a href=\"https:\/\/www.glbgpt.com\/hub\/how-to-improve-ai-image-generation-accuracy\/\">image-generation accuracy checklist<\/a> gives you a broader way to inspect instruction following.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">2. Test a small edit without rebuilding the whole image<\/h3>\n\n\n\n<section aria-label=\"Edit + preserve the original prompt\" style=\"box-sizing:border-box;margin:28px 0;padding:24px;border-radius:18px;background:#17362e;color:#f3f8f5;font-family:system-ui,sans-serif;overflow-wrap:anywhere\"><p style=\"margin:0 0 10px;font-size:12px;letter-spacing:.08em;color:#badacb\">COMPARISON PROMPT \u00b7 EDIT + PRESERVE THE ORIGINAL<\/p><pre id=\"edit-preservation-prompt\" data-value contenteditable=\"true\" role=\"textbox\" aria-label=\"Edit + preserve the original prompt text\" tabindex=\"0\" style=\"margin:0;white-space:pre-wrap;overflow-wrap:anywhere;font:15px\/1.7 ui-monospace,Consolas,monospace;color:inherit;outline-offset:6px\">Use the attached product image as the source.\nChange only the bottle body from cobalt blue to forest green.\nPreserve the cap, label text, bottle proportions, camera angle, pedestal, background, lighting, and shadow.\nDo not add or remove objects. Do not rewrite any text.<\/pre><div style=\"display:flex;gap:12px;align-items:center;flex-wrap:wrap;margin-top:16px\"><button type=\"button\" data-copy style=\"padding:10px 16px;border:1px solid #a6ccba;border-radius:9px;background:#d6ecdf;color:#12362b;cursor:pointer;font:600 14px system-ui\">Copier l'invite<\/button><span role=\"status\" style=\"font-size:13px\">Select the text to copy manually.<\/span><\/div><\/section><script>(function(){const root=document.currentScript.previousElementSibling;root.querySelector('[data-copy]').addEventListener('click',async()=>{const field=root.querySelector('[data-value]'),status=root.querySelector('[role=\"status\"]'),value=field.textContent;try{if(!navigator.clipboard)throw Error();await Promise.race([navigator.clipboard.writeText(value),new Promise((_,r)=>setTimeout(()=>r(Error()),800))]);status.textContent='Copied.';}catch(e){field.focus();const range=document.createRange();range.selectNodeContents(field);const s=window.getSelection();s.removeAllRanges();s.addRange(range);status.textContent='Selected. Press Ctrl\/Cmd+C.';}});})();<\/script>\n\n\n\n<p class=\"wp-block-paragraph\">Give both models the <strong>same original source file<\/strong>. To isolate editing ability, do not feed one model its own generated bottle and the other a different bottle. Save the original and edited images, then inspect unchanged areas as well as the requested color change. Repeat the same brief if you want to assess consistency; one result only establishes what happened on that attempt.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">For prompt construction, the <a href=\"https:\/\/www.glbgpt.com\/hub\/ultimate-nano-banana-prompt-guide-master-image-generation-and-editing\/\">Guide d'utilisation de Nano Banana<\/a> shows how to describe composition and specify what must stay fixed. Treat that as prompt-writing guidance; model-specific controls do not automatically transfer to MAI.<\/p>\n\n\n\n<h2 id=\"access\" class=\"wp-block-heading\">Where to use the models: Playground, Foundry, and comparison workflows<\/h2>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>For a quick trial:<\/strong> open <a href=\"https:\/\/playground.microsoft.ai\/chat?model=mai-image-2-6-flash\">MAI-Image-2.6-Flash in Microsoft Playground<\/a>, then compare it with the standard model using the same brief. Microsoft\u2019s announcement links both models to Playground. Access conditions and any available allowance belong to that product; the API cost examples above do not establish a free or unlimited Playground quota.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>For an application:<\/strong> use the <a href=\"https:\/\/ai.azure.com\/catalog\/models\/MAI-Image-2.6\">MAI-Image-2.6 Foundry model card<\/a> or the separate Flash card, select the deployment that fits your account and supported region, and confirm billing before running a batch. Microsoft\u2019s documentation lists the generation and edit APIs, authentication options, and deployment prerequisites. Both models are listed in preview, which deserves attention when you are choosing a production dependency.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>For a broader creative workflow:<\/strong> <a href=\"https:\/\/www.glbgpt.com\/home?inviter=hub_popup&amp;login=1\">GlobalGPT<\/a> is another place to explore available image tools and compare creative approaches in one workspace. Use the actual catalog entry for any model you intend to run. A multi-model subscription and direct Microsoft API billing solve different needs; no MAI-specific GlobalGPT price or verified MAI entry is established here.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">Notre <a href=\"https:\/\/www.glbgpt.com\/hub\/all-in-one-ai-models\/\">flux de travail de mod\u00e8le d'IA tout-en-un<\/a> explains how to combine tools across planning, generation, and revision. The benefit is less switching between separate products when your task needs more than a single image model.<\/p>\n\n\n\n<h2 id=\"which-to-choose\" class=\"wp-block-heading\">Lequel choisir ?<\/h2>\n\n\n\n<section aria-label=\"Choix du mod\u00e8le\" style=\"box-sizing:border-box;margin:28px 0;padding:clamp(18px,4vw,30px);border:1px solid #d6e2dc;border-radius:20px;background:#f2f6f4;color:#18352d;font-family:system-ui,sans-serif;line-height:1.55;overflow-wrap:anywhere\"><div style=\"display:flex;flex-wrap:wrap;gap:16px\"><div style=\"box-sizing:border-box;flex:1 1 220px;min-width:0;padding:22px;border-radius:14px;background:#dfeee5\"><div style=\"font-size:14px;font-weight:700\">Choose Flash for<\/div><div style=\"font-size:clamp(26px,4vw,38px);font-weight:750;margin:8px 0;line-height:1.2\">It\u00e9ration rapide<\/div><div style=\"font-size:14px\">Draft concepts \u00b7 repeated edits \u00b7 larger output volumes<\/div><\/div><div style=\"box-sizing:border-box;flex:1 1 220px;min-width:0;padding:22px;border-radius:14px;background:#e8eaf7\"><div style=\"font-size:14px;font-weight:700\">Choose standard for<\/div><div style=\"font-size:clamp(26px,4vw,38px);font-weight:750;margin:8px 0;line-height:1.2\">Final-image quality<\/div><div style=\"font-size:14px\">Text-heavy layouts \u00b7 polished hero assets \u00b7 demanding compositions<\/div><\/div><\/div><p style=\"font-size:13px;line-height:1.6;margin:18px 0 0\">These are recommendations from the cited price, preference, and latency evidence. They are not a guarantee of a particular output.<\/p><\/section>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Start with Flash when you expect to iterate.<\/strong> Its representative per-image cost is about half as much, and Microsoft\u2019s published response times are substantially shorter. The current editing scores are close enough that Flash deserves a fair trial on your real assets before you pay more for every attempt.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\"><strong>Start with MAI-Image-2.6 when a stronger first image has more value than the time saved.<\/strong> Its current text-to-image score is higher. For a campaign visual, a poster with exact text, or a final product image, compare it directly with Flash and count the retouching and retry time as part of the cost.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">A practical compromise is to explore briefs with Flash, then run the strongest brief through standard before choosing the final asset. Keep model choice separate from licensing: our <a href=\"https:\/\/www.glbgpt.com\/hub\/can-i-use-ai-images-for-commercial-use\/\">Guide d'utilisation commerciale des images g\u00e9n\u00e9r\u00e9es par l'IA<\/a> covers the questions to ask about provider terms, reference-image rights, trademarks, and people shown in the output.<\/p>\n\n\n\n<p class=\"wp-block-paragraph\">For most iterative creative work, <strong>Flash is the sensible first trial<\/strong>. The standard model earns its premium when its stronger generation result saves a retry or produces a final image you prefer. Compare usable outputs for your brief, rather than treating the cheapest attempt or the highest Elo as the whole decision.<\/p>\n\n\n\n<h2 id=\"faq\" class=\"wp-block-heading\">Foire aux questions<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">What is MAI-Image-2.6-Flash?<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">MAI-Image-2.6-Flash is Microsoft\u2019s faster, lower-cost variant of MAI-Image-2.6. Both support text-to-image generation and image editing. It is separate from Gemini Flash and the older MAI-Image-2.5-Flash.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">How much does MAI-Image-2.6 cost compared with Flash?<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Artificial Analysis lists representative API costs of $38.90 per 1,000 images for MAI-Image-2.6 and $19.50 for Flash, checked October 21, 2026. These equivalents are not a universal fixed rate for every Azure request.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">How much faster is Flash than MAI-Image-2.6?<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Microsoft\u2019s internal 1024 \u00d7 1024 test at 100 RPM reports median response times of 12.2 seconds for Flash and 25.6 seconds for standard. That is about a 2.1\u00d7 speed ratio under those test conditions.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Does the 2.8\u00d7 speed claim compare Flash with standard MAI-Image-2.6?<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">No. Microsoft\u2019s 2.8\u00d7 claim compares Flash with GPT-Image-2-Medium. Its published median response times are 12.2 seconds for Flash and 33.6 seconds for that GPT baseline.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Which model has the better image-generation benchmark?<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">On October 21, 2026, AA-Image-T2I v2.1 lists MAI-Image-2.6 at 1166 \u00b112 Elo and Flash at 1119 \u00b112. These are human-preference scores, not accuracy percentages or a guarantee for every prompt.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Is Flash worse at image editing?<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">The October 21 AA-Image-Editing v2.1 scores are 1151 \u00b112 for standard and 1143 \u00b113 for Flash. Their 95% intervals overlap, so test your actual edit before assuming a large quality difference.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Can both models use reference images?<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Yes. Microsoft documents image editing with up to five JPEG or PNG reference images for both models. The family announcement also describes web grounding and dynamic aspect ratios.<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Where can I try the two MAI models?<\/h3>\n\n\n\n<p class=\"wp-block-paragraph\">Microsoft links both models from MAI Playground and lists them in Microsoft Foundry as preview models. Playground access and allowances are separate from API deployment, billing, and region requirements.<\/p>\n\n\n\n<script type=\"application\/ld+json\">{\n    \"@context\": \"https:\\\/\\\/schema.org\",\n    \"@type\": \"FAQPage\",\n    \"mainEntity\": [\n        {\n            \"@type\": \"Question\",\n            \"name\": \"What is MAI-Image-2.6-Flash?\",\n            \"acceptedAnswer\": {\n                \"@type\": \"Answer\",\n                \"text\": \"MAI-Image-2.6-Flash is Microsoft\\u2019s faster, lower-cost variant of MAI-Image-2.6. Both support text-to-image generation and image editing. It is separate from Gemini Flash and the older MAI-Image-2.5-Flash.\"\n            }\n        },\n        {\n            \"@type\": \"Question\",\n            \"name\": \"How much does MAI-Image-2.6 cost compared with Flash?\",\n            \"acceptedAnswer\": {\n                \"@type\": \"Answer\",\n                \"text\": \"Artificial Analysis lists representative API costs of $38.90 per 1,000 images for MAI-Image-2.6 and $19.50 for Flash, checked October 21, 2026. These equivalents are not a universal fixed rate for every Azure request.\"\n            }\n        },\n        {\n            \"@type\": \"Question\",\n            \"name\": \"How much faster is Flash than MAI-Image-2.6?\",\n            \"acceptedAnswer\": {\n                \"@type\": \"Answer\",\n                \"text\": \"Microsoft\\u2019s internal 1024 \\u00d7 1024 test at 100 RPM reports median response times of 12.2 seconds for Flash and 25.6 seconds for standard. That is about a 2.1\\u00d7 speed ratio under those test conditions.\"\n            }\n        },\n        {\n            \"@type\": \"Question\",\n            \"name\": \"Does the 2.8\\u00d7 speed claim compare Flash with standard MAI-Image-2.6?\",\n            \"acceptedAnswer\": {\n                \"@type\": \"Answer\",\n                \"text\": \"No. Microsoft\\u2019s 2.8\\u00d7 claim compares Flash with GPT-Image-2-Medium. Its published median response times are 12.2 seconds for Flash and 33.6 seconds for that GPT baseline.\"\n            }\n        },\n        {\n            \"@type\": \"Question\",\n            \"name\": \"Which model has the better image-generation benchmark?\",\n            \"acceptedAnswer\": {\n                \"@type\": \"Answer\",\n                \"text\": \"On October 21, 2026, AA-Image-T2I v2.1 lists MAI-Image-2.6 at 1166 \\u00b112 Elo and Flash at 1119 \\u00b112. These are human-preference scores, not accuracy percentages or a guarantee for every prompt.\"\n            }\n        },\n        {\n            \"@type\": \"Question\",\n            \"name\": \"Is Flash worse at image editing?\",\n            \"acceptedAnswer\": {\n                \"@type\": \"Answer\",\n                \"text\": \"The October 21 AA-Image-Editing v2.1 scores are 1151 \\u00b112 for standard and 1143 \\u00b113 for Flash. Their 95% intervals overlap, so test your actual edit before assuming a large quality difference.\"\n            }\n        },\n        {\n            \"@type\": \"Question\",\n            \"name\": \"Can both models use reference images?\",\n            \"acceptedAnswer\": {\n                \"@type\": \"Answer\",\n                \"text\": \"Yes. Microsoft documents image editing with up to five JPEG or PNG reference images for both models. The family announcement also describes web grounding and dynamic aspect ratios.\"\n            }\n        },\n        {\n            \"@type\": \"Question\",\n            \"name\": \"Where can I try the two MAI models?\",\n            \"acceptedAnswer\": {\n                \"@type\": \"Answer\",\n                \"text\": \"Microsoft links both models from MAI Playground and lists them in Microsoft Foundry as preview models. Playground access and allowances are separate from API deployment, billing, and region requirements.\"\n            }\n        }\n    ]\n}<\/script>","protected":false},"excerpt":{"rendered":"<p>MAI-Image-2.6 vs Flash comes down to how much you value a stronger first result over cheaper, faster iteration. MAI-Image-2.6-Flash has a representative API price of $19.50 per 1,000 images, compared with $38.90 for MAI-Image-2.6 on Artificial Analysis\u2019s image-editing leaderboard. In Microsoft\u2019s internal 1024 \u00d7 1024 load test, Flash\u2019s median response was 12.2 seconds, versus 25.6 [&hellip;]<\/p>","protected":false},"author":16,"featured_media":20955,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_seopress_robots_primary_cat":"","_seopress_titles_title":"MAI-Image-2.6 vs Flash: Pricing, Benchmarks & Speed","_seopress_titles_desc":"MAI-Image-2.6 vs Flash: compare image costs, current benchmark scores, and published speed tests. See which model fits your creative project before you pay.","_seopress_robots_index":"","footnotes":""},"categories":[7],"tags":[],"class_list":["post-20952","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai-chat"],"acf":[],"_links":{"self":[{"href":"https:\/\/wp.glbgpt.com\/fr\/wp-json\/wp\/v2\/posts\/20952","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/wp.glbgpt.com\/fr\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/wp.glbgpt.com\/fr\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/wp.glbgpt.com\/fr\/wp-json\/wp\/v2\/users\/16"}],"replies":[{"embeddable":true,"href":"https:\/\/wp.glbgpt.com\/fr\/wp-json\/wp\/v2\/comments?post=20952"}],"version-history":[{"count":3,"href":"https:\/\/wp.glbgpt.com\/fr\/wp-json\/wp\/v2\/posts\/20952\/revisions"}],"predecessor-version":[{"id":20957,"href":"https:\/\/wp.glbgpt.com\/fr\/wp-json\/wp\/v2\/posts\/20952\/revisions\/20957"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/wp.glbgpt.com\/fr\/wp-json\/wp\/v2\/media\/20955"}],"wp:attachment":[{"href":"https:\/\/wp.glbgpt.com\/fr\/wp-json\/wp\/v2\/media?parent=20952"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/wp.glbgpt.com\/fr\/wp-json\/wp\/v2\/categories?post=20952"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/wp.glbgpt.com\/fr\/wp-json\/wp\/v2\/tags?post=20952"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}