{"id":2243,"date":"2026-08-06T13:09:22","date_gmt":"2026-08-06T13:09:22","guid":{"rendered":"https:\/\/techvisor.pro\/?p=2243"},"modified":"2026-08-06T13:09:22","modified_gmt":"2026-08-06T13:09:22","slug":"qwen3-8-max-alibabas-new-model-with-2-4-trillion-parameters","status":"publish","type":"post","link":"https:\/\/techvisor.pro\/en\/qwen3-8-max-alibabas-new-model-with-2-4-trillion-parameters\/","title":{"rendered":"Qwen3.8-Max: Alibaba&#8217;s new model with 2.4 trillion parameters"},"content":{"rendered":"<p>On August 3, 2026, Alibaba released Qwen3.8-Max \u2014 the most powerful model in its Qwen lineup to date. We break down its specifications, benchmarks and why this is another step in the fast-moving race of large Chinese AI models.<\/p>\n<h2>What Is Qwen3.8-Max<\/h2>\n<p>Qwen3.8-Max is Alibaba Cloud\u2019s flagship model with 2.4 trillion parameters, slightly smaller than Kimi K3 from Moonshot AI (2.8 trillion), which still remains the largest open model in the world. The model\u2019s context window is up to 1 million tokens, allowing it to process huge amounts of text, images and video in a single request.<\/p>\n<h2>Architecture: Efficiency Through MoE<\/h2>\n<p><img fetchpriority=\"high\" decoding=\"async\" class=\"alignnone size-full wp-image-2235\" src=\"https:\/\/techvisor.pro\/wp-content\/uploads\/2026\/08\/arhitektura-efektyvnist-cherez-moe.webp\" alt=\"Architecture: efficiency through MoE\" width=\"1672\" height=\"941\" title=\"\" srcset=\"https:\/\/techvisor.pro\/wp-content\/uploads\/2026\/08\/arhitektura-efektyvnist-cherez-moe.webp 1672w, https:\/\/techvisor.pro\/wp-content\/uploads\/2026\/08\/arhitektura-efektyvnist-cherez-moe-300x169.webp 300w, https:\/\/techvisor.pro\/wp-content\/uploads\/2026\/08\/arhitektura-efektyvnist-cherez-moe-1024x576.webp 1024w, https:\/\/techvisor.pro\/wp-content\/uploads\/2026\/08\/arhitektura-efektyvnist-cherez-moe-768x432.webp 768w, https:\/\/techvisor.pro\/wp-content\/uploads\/2026\/08\/arhitektura-efektyvnist-cherez-moe-1536x864.webp 1536w\" sizes=\"(max-width: 1672px) 100vw, 1672px\" \/><\/p>\n<p>The model is built on a sparse Mixture-of-Experts architecture \u2014 instead of activating all 2.4 trillion parameters at once, only about 95 billion are used for each request. This significantly reduces compute cost and response latency, allowing the model to process text, images and video without a proportional increase in expenses.<\/p>\n<h2>Capabilities and Benchmarks<\/h2>\n<p><img decoding=\"async\" class=\"alignnone size-full wp-image-2236\" src=\"https:\/\/techvisor.pro\/wp-content\/uploads\/2026\/08\/mozhlyvosti-ta-benchmarky.webp\" alt=\"Capabilities and benchmarks\" width=\"1672\" height=\"941\" title=\"\" srcset=\"https:\/\/techvisor.pro\/wp-content\/uploads\/2026\/08\/mozhlyvosti-ta-benchmarky.webp 1672w, https:\/\/techvisor.pro\/wp-content\/uploads\/2026\/08\/mozhlyvosti-ta-benchmarky-300x169.webp 300w, https:\/\/techvisor.pro\/wp-content\/uploads\/2026\/08\/mozhlyvosti-ta-benchmarky-1024x576.webp 1024w, https:\/\/techvisor.pro\/wp-content\/uploads\/2026\/08\/mozhlyvosti-ta-benchmarky-768x432.webp 768w, https:\/\/techvisor.pro\/wp-content\/uploads\/2026\/08\/mozhlyvosti-ta-benchmarky-1536x864.webp 1536w\" sizes=\"(max-width: 1672px) 100vw, 1672px\" \/><\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"ltr\" data-sourcepos=\"46:1-46:231;2001-2231\">According to Alibaba, Qwen3.8-Max delivers results comparable to Anthropic\u2019s Claude Fable 5, and in some cases better. The model ranked fifth in Text Arena and second in Vision Arena, trailing only Fable 5 in that category.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"ltr\" data-sourcepos=\"48:1-48:295;2233-2527\">Among the stated capabilities are application development, research work, legal document review, sports analytics, financial research and even architectural 3D modeling. Alibaba also claims that the model is capable of autonomously writing code for weeks with minimal human intervention.<\/p>\n<h2 dir=\"ltr\" data-sourcepos=\"48:1-48:295;2233-2527\">Open Weights \u2014 Next Week<\/h2>\n<p><img decoding=\"async\" class=\"alignnone size-full wp-image-2237\" src=\"https:\/\/techvisor.pro\/wp-content\/uploads\/2026\/08\/vidkryti-vagy-\u2014-nastupnogo-tyzhnya.webp\" alt=\"Open weights \u2014 next week\" width=\"1672\" height=\"941\" title=\"\" srcset=\"https:\/\/techvisor.pro\/wp-content\/uploads\/2026\/08\/vidkryti-vagy-\u2014-nastupnogo-tyzhnya.webp 1672w, https:\/\/techvisor.pro\/wp-content\/uploads\/2026\/08\/vidkryti-vagy-\u2014-nastupnogo-tyzhnya-300x169.webp 300w, https:\/\/techvisor.pro\/wp-content\/uploads\/2026\/08\/vidkryti-vagy-\u2014-nastupnogo-tyzhnya-1024x576.webp 1024w, https:\/\/techvisor.pro\/wp-content\/uploads\/2026\/08\/vidkryti-vagy-\u2014-nastupnogo-tyzhnya-768x432.webp 768w, https:\/\/techvisor.pro\/wp-content\/uploads\/2026\/08\/vidkryti-vagy-\u2014-nastupnogo-tyzhnya-1536x864.webp 1536w\" sizes=\"(max-width: 1672px) 100vw, 1672px\" \/><\/p>\n<p>Alibaba plans to publish the model\u2019s full weights within the week following release \u2014 this will be the company\u2019s first \u201cMax\u201d-class model to become fully open. For now, Qwen3.8-Max is available through the API on Alibaba Cloud Model Studio for developers worldwide.<\/p>\n<h2>Context: The Race of Chinese Open Models Is Accelerating<\/h2>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"ltr\" data-sourcepos=\"60:1-60:331;2905-3235\">The release of Qwen3.8-Max happened less than a month after Moonshot AI released Kimi K3 \u2014 a model the company called the world\u2019s first open \u201c3-trillion-class\u201d model. That same week, China\u2019s DeepSeek released the V4-Flash model, which researchers estimate could turn out to be one of the cheapest models in the world to run.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"ltr\" data-sourcepos=\"62:1-62:188;3237-3424\">Together, these releases show how quickly Chinese technology companies are increasing the pace of launching powerful open models, competing not only on size but also on deployment cost.<\/p>\n<h2 dir=\"ltr\" data-sourcepos=\"62:1-62:188;3237-3424\">In Brief: The Key Points<\/h2>\n<ul>\n<li class=\"font-claude-response-body whitespace-normal break-words pl-2\" data-sourcepos=\"68:1-68:78;3454-3531\"><strong>August 3, 2026<\/strong> \u2014 Alibaba released Qwen3.8-Max, with 2.4 trillion parameters<\/li>\n<li class=\"font-claude-response-body whitespace-normal break-words pl-2\" data-sourcepos=\"69:1-69:43;3532-3574\">Context window \u2014 up to 1 million tokens<\/li>\n<li class=\"font-claude-response-body whitespace-normal break-words pl-2\" data-sourcepos=\"70:1-70:77;3575-3651\">MoE architecture activates only ~95 billion parameters at a time, reducing cost<\/li>\n<li class=\"font-claude-response-body whitespace-normal break-words pl-2\" data-sourcepos=\"71:1-71:87;3652-3738\">Results comparable to Claude Fable 5, 5th place in Text Arena, 2nd place in Vision Arena<\/li>\n<li class=\"font-claude-response-body whitespace-normal break-words pl-2\" data-sourcepos=\"72:1-72:63;3739-3801\">Full open weights \u2014 within the week following release<\/li>\n<li class=\"font-claude-response-body whitespace-normal break-words pl-2\" data-sourcepos=\"73:1-73:72;3802-3873\">Released less than a month after Kimi K3 (2.8T) from Moonshot AI<\/li>\n<\/ul>\n<h2 class=\"mt-3 -mb-1 text-[1.125rem] font-bold\" dir=\"ltr\" data-sourcepos=\"77:1-77:7;3880-3886\">FAQ<\/h2>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"ltr\" data-sourcepos=\"79:1-80:129;3888-4041\"><strong>What is Qwen3.8-Max?<\/strong> Alibaba Cloud\u2019s most powerful model in the Qwen lineup to date \u2014 2.4 trillion parameters, with a context window of up to 1 million tokens.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"ltr\" data-sourcepos=\"82:1-83:200;4043-4289\"><strong>How is Qwen3.8-Max different from Kimi K3?<\/strong> Kimi K3 from Moonshot AI is slightly larger (2.8T parameters versus 2.4T) and still remains the world\u2019s largest open model. Both are Chinese open models released less than a month apart.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"ltr\" data-sourcepos=\"85:1-86:80;4291-4413\"><strong>Will Qwen3.8-Max be an open model?<\/strong> Yes, Alibaba plans to publish the model\u2019s full weights within a week after release.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"ltr\" data-sourcepos=\"88:1-89:164;4415-4628\"><strong>How does Qwen3.8-Max compare with Claude Fable 5?<\/strong> According to Alibaba, the model shows comparable and in some cases better results on benchmarks, although in the Vision Arena category it trails Fable 5, taking second place.<\/p>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"ltr\" data-sourcepos=\"91:1-92:169;4630-4842\"><strong>What is Mixture-of-Experts architecture?<\/strong> An approach in which the model activates only part of its parameters for each specific request, rather than all of them at once \u2014 reducing compute costs and response latency.<\/p>\n<hr class=\"border-border-200 border-t-0.5 my-3 mx-1.5\" \/>\n<p class=\"font-claude-response-body break-words whitespace-normal\" dir=\"ltr\" data-sourcepos=\"96:1-96:79;4849-4927\"><em>The article was prepared by the TechVisor team \u2014 practical IT media for people.<\/em><\/p>\n","protected":false},"excerpt":{"rendered":"<p>On August 3, 2026, Alibaba released Qwen3.8-Max \u2014 the most powerful model in its Qwen lineup to date. We break down its specifications, benchmarks and why this is another step in the fast-moving race of large Chinese AI models. What Is Qwen3.8-Max Qwen3.8-Max is Alibaba Cloud\u2019s flagship model with 2.4 trillion parameters, slightly smaller than [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":2242,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[25,21],"tags":[],"class_list":["post-2243","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-ai-hub","category-news"],"blocksy_meta":{"styles_descriptor":{"styles":{"desktop":"","tablet":"","mobile":""},"google_fonts":[],"version":8}},"_links":{"self":[{"href":"https:\/\/techvisor.pro\/en\/wp-json\/wp\/v2\/posts\/2243","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/techvisor.pro\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/techvisor.pro\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/techvisor.pro\/en\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/techvisor.pro\/en\/wp-json\/wp\/v2\/comments?post=2243"}],"version-history":[{"count":1,"href":"https:\/\/techvisor.pro\/en\/wp-json\/wp\/v2\/posts\/2243\/revisions"}],"predecessor-version":[{"id":2249,"href":"https:\/\/techvisor.pro\/en\/wp-json\/wp\/v2\/posts\/2243\/revisions\/2249"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/techvisor.pro\/en\/wp-json\/wp\/v2\/media\/2242"}],"wp:attachment":[{"href":"https:\/\/techvisor.pro\/en\/wp-json\/wp\/v2\/media?parent=2243"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/techvisor.pro\/en\/wp-json\/wp\/v2\/categories?post=2243"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/techvisor.pro\/en\/wp-json\/wp\/v2\/tags?post=2243"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}