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DeepSeek #1 on US App Store, Nvidia stock tanks -17%

DeepSeek's R1 model reaches the top of the US App Store charts while its reported cost efficiency triggers a 17% drop in Nvidia's stock price.

Jan 28 · · primary fetch1 sourceupdated Jan 28 ·

DeepSeek has made a significant cultural impact by hitting mainstream news unexpectedly in 2025. The DeepSeek-R1 model features a massive 671B parameter MoE architecture and demonstrates chain-of-thought (CoT) capabilities comparable to OpenAI's o1 at a lower cost. The DeepSeek V3 model trains a 236B parameter model 42% faster than its predecessor using fp8 precision. The Qwen2.5 multimodal models support images and videos with sizes ranging from 3B to 72B parameters, featuring strong vision and agentic capabilities.

LangChain and LangGraph integration enable AI chatbots with memory and tool use, including applications like the DeFi Agent. Discussions highlight NVIDIA's role in hardware acceleration, with concerns about stock drops due to DeepSeek's efficiency and market fears. The compute demand is expected to rise despite efficiency gains, driven by inference scaling and MoE design improvements.

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