[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$fVZgUAmUlD0GH9kMyQytydtsBxg0ZBu6i7k8HdQ4wLz8":3},{"model":4,"providerPool":48},{"id":5,"name":6,"slug":7,"provider":8,"family":8,"variant":9,"description":10,"url":11,"openWeights":12,"license":13,"parameters":14,"contextWindow":15,"modalities":16,"modalitiesOut":20,"announcedAt":21,"releasedAt":24,"status":25,"reasoning":12,"reasoningControl":26,"toolCall":12,"attachment":12,"hf":29,"articles":46,"createdAt":47},"entity_01m0zh950xe0191qeaxg0kq33v","Qwen3.8 Flash Next","qwen3-8-flash-next","Qwen","3.8 Flash Next","An open-weights multimodal MoE model that doubles as an early preview of the Qwen4 architecture, the same role Qwen3-Next played for Qwen3.5. It pairs Gated DeltaNet with Qwen Sparse Attention, widens the residual stream into four gated branches, and adds 51B N-gram embedding parameters that cost almost nothing per token. Natively 262K context, extensible to 1M with YaRN.","https:\u002F\u002Fqwen.ai\u002Fblog?id=qwen3.8-flash-next",true,"Qwen Community License 1.0","125B total, 6B active, plus 51B N-gram embeddings",262144,[17,18,19],"text","image","video",[17],{"value":22,"precision":23},"2026-08-24","day",{"value":22,"precision":23},"ga",[27,28],"toggle","effort",{"fullName":30,"url":31,"downloads":32,"likes":33,"license":34,"pipelineTag":35,"tags":36,"lastModified":45},"Qwen\u002FQwen3.8-Flash-Next","https:\u002F\u002Fhuggingface.co\u002FQwen\u002FQwen3.8-Flash-Next",2551,3443,"other","image-text-to-text",[37,38,39,35,40,41,42,43,44],"transformers","safetensors","qwen4_exp","conversational","license:other","eval-results","endpoints_compatible","region:us","2026-08-26T12:29:54.000Z",[],1787764708,[49,58],{"id":5,"name":6,"slug":7,"provider":8,"family":8,"variant":9,"description":10,"url":11,"openWeights":12,"license":13,"parameters":14,"contextWindow":15,"modalities":50,"modalitiesOut":51,"announcedAt":52,"releasedAt":53,"status":25,"reasoning":12,"reasoningControl":54,"toolCall":12,"attachment":12,"hf":55,"articles":57,"createdAt":47},[17,18,19],[17],{"value":22,"precision":23},{"value":22,"precision":23},[27,28],{"fullName":30,"url":31,"downloads":32,"likes":33,"license":34,"pipelineTag":35,"tags":56,"lastModified":45},[37,38,39,35,40,41,42,43,44],[],{"id":59,"name":60,"slug":61,"provider":8,"family":8,"variant":62,"description":63,"url":64,"openWeights":12,"license":65,"parameters":66,"contextWindow":15,"outputLimit":67,"modalities":68,"modalitiesOut":69,"releasedAt":70,"status":25,"reasoning":12,"reasoningControl":72,"toolCall":12,"aiSdkId":73,"openrouterUrl":74,"hf":75,"articles":85,"createdAt":123},"entity_01m04qe6hre8gs49wbdhj39a2n","Qwen3.8 27B","qwen3-8-27b","3.8 27B","Built on the architectural foundation of Qwen3.5, Qwen3.8 delivers substantial gains across coding, professional work, research, and long-horizon agentic tasks. Qwen3.8-27B brings these advances to a compact, deployment-friendly dense model: a native vision-language model that understands images and videos, with flexible thinking control, designed to carry complex, multi-step tasks through to completion with greater reliability.","https:\u002F\u002Fhuggingface.co\u002FQwen\u002FQwen3.8-27B","Apache-2.0","27B dense",131072,[17,18,19],[17],{"value":71,"precision":23},"2026-08-14",[27,28],"qwen3.8-27b","https:\u002F\u002Fopenrouter.ai\u002Fqwen\u002Fqwen3.8-27b",{"fullName":76,"url":64,"downloads":77,"likes":78,"license":79,"pipelineTag":35,"tags":80,"lastModified":84},"Qwen\u002FQwen3.8-27B",91917,9921,"apache-2.0",[37,38,81,35,40,82,42,43,83,44],"qwen3_5","license:apache-2.0","deploy:azure","2026-08-14T15:00:01.000Z",[86,98,110],{"id":87,"name":88,"slug":89,"summary":90,"url":91,"kind":92,"platform":93,"author":94,"publisher":94,"publishedAt":95,"about":96,"writtenBy":97},"entity_01m0bhhtcae03ah9vbyhmk5xem","DFlash 2: Keep Drafting Parallel","dflash-2-keep-drafting-parallel","DFlash 2 is the successor to our widely deployed parallel drafter: close to 3× the speed of autoregressive decoding, with the same output. Drafters for Qwen3.8-27B and Meta's Muse Glimmer are out today.","https:\u002F\u002Finco.ai\u002Fblog\u002Fdflash2\u002F","announcement","web","Inco AI","2026-08-18",[],[],{"id":99,"name":100,"slug":101,"summary":102,"url":103,"kind":104,"platform":93,"author":105,"publisher":106,"publishedAt":107,"about":108,"writtenBy":109},"entity_01m06bprpafaj98sc2azyjnbk0","Qwen 3.8 27B is excellent, but it defaults to wildly overthinking things","qwen-3-8-27b-is-excellent-but-it-defaults-to-wildly-overthinking-things","Friday’s big release was Qwen 3.8 27B, an Apache 2 licensed 27B parameter vision-capable LLM from Alibaba’s Qwen research lab. I’ve been looking forward to this one: 27B is an …","https:\u002F\u002Fsimonwillison.net\u002F2026\u002FAug\u002F16\u002Fqwen-38-27b\u002F","article","Simon Willison","Simon Willison’s Weblog","2026-08-16",[],[],{"id":111,"name":112,"slug":113,"summary":114,"url":115,"kind":104,"platform":116,"author":117,"authorHandle":118,"publisher":119,"publishedAt":120,"about":121,"writtenBy":122},"entity_01m04q74nne8gs49w523h2mrej","Qwen 27B 3.8: Non-Thinking vs XHigh Thinking","qwen-27b-3-8-non-thinking-vs-xhigh-thinking","Qwen 27B 3.8 was given the same CRUDbench task in non-thinking mode and XHigh thinking mode.","https:\u002F\u002Fx.com\u002FLottoLabs\u002Fstatus\u002F2088504974405951912","x","Lotto","LottoLabs","X","2026-08-15",[],[],1786865195]