DeepSeek-V4: Towards Highly Efficient Million-Token Context Intelligence
We present a preview version of DeepSeek-V4 series, including two strong Mixture-of-Experts (MoE) language models -- DeepSeek-V4-Pro with 1.6T parameters (49B activated) and DeepSeek-V4-Flash with 284B parameters (13B activated) -- both supporting a context length of one million tokens. DeepSeek-V4 series incorporate several key upgrades in architecture and optimization: (1) a hybrid attention architecture that combines Compressed Sparse Attention (CSA) and Heavily Compressed Attention (HCA) to improve long-context efficiency; (2) Manifold-Constrained Hyper-Connections (mHC) that enhance conventional residual connections; (3) and the Muon optimizer for faster convergence and greater train...
| Authors | DeepSeek-AI, Anyi Xu, Bangcai Lin et al. |
|---|---|
| Primary category | cs.CL |
| Published | 26 April 2026 |
| Last updated at source | 26 April 2026 |
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