New Delhi, Oct. 5 -- DeepSeek has introduced DeepSeek-V3.2-Exp, an experimental model its developers describe as more efficient to train and better at processing long sequences of text. In a post on developer forum Hugging Face, highlights a new DeepSeek Sparse Attention mechanism and a headline API price cut. DeepSeek says the model is an "intermediate step toward our next-generation architecture."
DeepSeek's latest experimental release, DeepSeek-V3.2-Exp, aims to shift the economics of large language models by improving long-text processing and cutting training costs. The update pairs an architectural tweak - DeepSeek Sparse Attention - with a notable API price reduction, a combination that could intensify competition with domestic and...
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