DeepSeek has released its V4.1 Flash model, claiming it outperforms its previous flagship while cutting inference costs and boosting speeds – the latest salvo in China's aggressive price-and-performance war. While built on a massive 552 billion-parameter framework, it relies on a Mixture-of-Experts (MoE) design.
DeepSeek has released its V4.1 Flash model, claiming it outperforms its previous flagship while cutting inference costs and boosting speeds – the latest salvo in China's aggressive price-and-performance war.
While built on a massive 552 billion-parameter framework, it relies on a Mixture-of-Experts (MoE) design.
Thursday that V4.1 Flash used a new "Causal-Encoder-Decoder" architecture.
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DeepSeek has released its V4.1 Flash model, claiming it outperforms its previous flagship while cutting inference costs and boosting speeds – the latest salvo in China's aggressive price-and-performance war. While built on a massive 552 billion-parameter framework, it relies on a Mixture-of-Experts (MoE) design. Thursday that V4.1 Flash used a new "Causal-Encoder-Decoder" architecture.
Thursday that V4.1 Flash used a new "Causal-Encoder-Decoder" architecture. In traditional AI, every query runs through the entire...
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