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Step 3.7 Flash by Lianjie Xingchen: 198B Parameter MoE Model, Focused on Production-Grade Agents
Lianjie Xingchen has officially launched and open-sourced the new generation Flash model, Step 3.7 Flash, under the Apache 2.0 license. This model features a sparse MoE architecture composed of a 196B language backbone and a 1.8B visual Transformer, totaling 198B parameters with only 11B activated. It supports 256K context and 3-tier inference, optimized for production-grade agents, coding, online search, and multimodal workflows.
Why it matters: The Chinese AI team has made significant breakthroughs in the open-source multimodal MoE model field, with a low activation parameter and high capability density architecture design representing the direction for efficient inference in the industry.
#AI #开源 #大模型 #MoE #ArtificialIntelligence
Lianjie Xingchen has officially launched and open-sourced the new generation Flash model, Step 3.7 Flash, under the Apache 2.0 license. This model features a sparse MoE architecture composed of a 196B language backbone and a 1.8B visual Transformer, totaling 198B parameters with only 11B activated. It supports 256K context and 3-tier inference, optimized for production-grade agents, coding, online search, and multimodal workflows.
Why it matters: The Chinese AI team has made significant breakthroughs in the open-source multimodal MoE model field, with a low activation parameter and high capability density architecture design representing the direction for efficient inference in the industry.
#AI #开源 #大模型 #MoE #ArtificialIntelligence
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