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DeepSeek releases v4.1-Flash with 763B-P8B-D16B architecture for efficient inference

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DeepSeek has launched DeepSeek v4.1-Flash, a new open-weight flagship model featuring a novel causal encoder-decoder architecture designed to maximize inference efficiency and reduce costs.

The model utilizes a mixture-of-experts structure with 763 billion total parameters, but only activates 8B parameters for input processing and 16B for output generation. This design achieves a sparsity of 1-2% and reduces the KV cache footprint to one-eighth that of the previous V4 Flash model. It supports a 1M-token context window with text and image inputs under an MIT license.

Independent benchmarks from Artificial Analysis and Vals rank v4.1-Flash as the top open-weight model, citing its superior cost-performance ratio with pricing at $0.30 per million input tokens.

Importance 3/3 Latent Space DeepSeek Inference efficiency Open weights

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media MarkTechPost · 2d ago · 15 views

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