神秘「牛来」模型果然是智谱！GLM首个原生多模态，还用的国产卡
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TL;DR - Zhipu released and open-sourced GLM-5.3 Flash, its first native multimodal GLM-5 model, previously tested anonymously as Ox Alpha. It targets affordable long-running agentic and visual tasks while serving production traffic on Chinese accelerator hardware.
- The 320B-parameter mixture model activates 18B parameters across 45 layers and was pretrained on 30T multimodal tokens.
- A hybrid linear-and-sparse attention architecture supports 1M-token contexts while reportedly cutting attention computation by 3.01× and KV-cache size by 4.44× versus GLM-5.3.
- Demonstrations covered video understanding and editing, UI generation from design images, interactive 3D webpages, and a 12-hour autonomous Blender workflow.
- Zhipu says its disaggregated encode-prefill-decode serving architecture tripled end-to-end performance on domestic chips; model weights, APIs, and coding integrations are now available.
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神秘「牛来」模型果然是智谱！GLM首个原生多模态，还用的国产卡
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TL;DR - Zhipu released and open-sourced GLM-5.3 Flash, its first native multimodal GLM-5 model, previously tested anonymously as Ox Alpha. It targets affordable long-running agentic and visual tasks while serving production traffic on Chinese accelerator hardware.
- The 320B-parameter mixture model activates 18B parameters across 45 layers and was pretrained on 30T multimodal tokens.
- A hybrid linear-and-sparse attention architecture supports 1M-token contexts while reportedly cutting attention computation by 3.01× and KV-cache size by 4.44× versus GLM-5.3.
- Demonstrations covered video understanding and editing, UI generation from design images, interactive 3D webpages, and a 12-hour autonomous Blender workflow.
- Zhipu says its disaggregated encode-prefill-decode serving architecture tripled end-to-end performance on domestic chips; model weights, APIs, and coding integrations are now available.