arXiv:2606.19348v1 Announce Type: new Abstract: 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-Constr
The continuous development and release of increasingly capable large language models with extended context windows is an ongoing trend aimed at improving AI utility.
Highly efficient million-token context intelligence expands the practical applications of AI, enabling more complex reasoning and processing of vast amounts of information.
AI models can now process significantly larger documents, codebases, or conversations in a single pass, enhancing their ability to understand and generate highly coherent and context-rich outputs.
- · AI developers
- · Enterprises adopting AI
- · Cloud providers
- · Data analysis platforms
- · Tasks requiring manual long-form analysis
- · Incumbent AI models with smaller context windows
DeepSeek-V4-Pro and DeepSeek-V4-Flash offer advanced long-context capabilities to the AI ecosystem.
This capability facilitates the creation of more sophisticated AI agents capable of handling complex, multi-turn interactions or analyzing extensive datasets.
Improved long-context processing could accelerate research and development in fields requiring extensive information synthesis, potentially leading to novel scientific discoveries or technological breakthroughs.
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