[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$f32o9lb9ublp68":3,"$f2fkkqgda4pqg0":31,"$fc630ienpdhyx":33,"$f31udz24e9li8b":49,"$f12f9c00yrhx38":52,"$f3eexl0gm9y7eg":54},{"id":4,"name":5,"publisher":6,"paramsB":7,"useCase":8,"licenseStatus":9,"licenseUrl":10,"sourceUrl":11,"descriptionZh":12,"descriptionEn":13,"imageUrl":14,"downloadUrls":15,"stats":18,"variants":22,"derivations":23,"measuredHardware":26,"updatedAt":30},11,"Qwen3.8-Flash-Next","Qwen (Alibaba)",180,"CHAT","OPEN_WEIGHTS","https:\u002F\u002Fhuggingface.co\u002FQwen\u002FQwen3.8-Flash-Next\u002Fblob\u002Fmain\u002FLICENSE","https:\u002F\u002Fhuggingface.co\u002FQwen\u002FQwen3.8-Flash-Next","Qwen (Alibaba) 2026-08-24 发布的开权重图文理解模型，180.0B 总参数，自定义开放权重许可。Qwen3.8 世代的 Flash 档，总参数约 180B，面向低成本高吞吐的本地与云端部署。","Open-weight vision-language model from Qwen (Alibaba), released 2026-08-24, 180.0B total, a bespoke open-weights licence. The Flash tier of the Qwen3.8 generation, roughly 180B total parameters, aimed at low-cost high-throughput serving.","\u002Fuploads\u002Fmodels\u002Fm11-6cfa2784bd3f.png",[16],{"url":11,"label":17},"HuggingFace",{"recordCount":19,"variantCount":20,"hardwareCount":19,"unlinkedRecordCount":19,"evidence":21},1,0,{"L0":20,"L1":19,"L2":20},[],{"parents":24,"children":25},[],[],[27],{"name":28,"vramGb":29,"recordCount":19},"4x NVIDIA Tesla P40",96,"2026-09-24T12:55:08.769Z",{"favorited":32},false,{"items":34,"total":19,"page":19,"pageSize":48},[35],{"modelId":4,"modelName":5,"hardwareId":36,"hardwareName":28,"frameworkId":19,"frameworkName":37,"quantization":38,"hardwareVramGb":29,"decodeTps":39,"prefillTps":40,"vramGb":41,"genSeconds":41,"modelUseCase":8,"ttftS":41,"ttfbGb":41,"mtpAcceptanceRate":41,"powerW":41,"sampleCount":19,"reproduceCount":19,"sourceTypes":42,"evidenceLevel":44,"updatedAt":45,"latestFrameworkVersion":46,"latestOs":47,"latestCudaVersion":41,"latestFlashAttention":41,"latestOutputSpec":41},73,"llama.cpp","UD-Q3_K_XL",21.6,330,null,[43],"GITHUB","L1","2026-10-02T04:40:27.327Z","b11058","Linux",50,{"items":50,"total":20,"page":19,"pageSize":51},[],20,{"items":53},[],{"items":55,"total":19,"page":19,"pageSize":67},[56],{"slug":57,"category":58,"publishedAt":59,"titleZh":60,"titleEn":61,"summaryZh":62,"summaryEn":63,"models":64,"hardwares":66},"qwen3-8-omni-flash","NEWS","2026-10-01T05:10:00.000Z","阿里发布 Qwen3.8-Omni-Flash：1M 上下文原生全模态，音频成本降 98%","Alibaba Launches Qwen3.8-Omni-Flash: Native Omni-Modal, 1M Context, Audio Costs Down 98%","阿里千问发布 Qwen3.8-Omni-Flash：基于 Qwen3.8-Flash-Next 架构的原生全模态模型，支持文本\u002F图像\u002F音频\u002F视频输入与 1M 上下文，输入 $0.15\u002F百万 token，每小时音频输入成本较上代降超 98%；仅 API 提供，未开放权重。","Alibaba's Qwen team has released Qwen3.8-Omni-Flash: a natively omni-modal model built on the Qwen3.8-Flash-Next architecture, accepting text\u002Fimage\u002Faudio\u002Fvideo input with a 1M-token context at $0.15 per million input tokens. Hourly audio input cost drops over 98% versus its predecessor. API-only; no open weights.",[65],{"id":4,"name":5},[],3]