DeepSeek Releases V4-Pro, an MIT-Licensed MoE Model

DeepSeek has published DeepSeek-V4-Pro-0813, the high-end entry in its new V4 family, on Hugging Face. The model uses a mixture-of-experts (MoE) architecture and is aimed at demanding reasoning and coding workloads.

The release carries an MIT license, one of the most permissive terms available. That means developers can use, modify, and deploy the weights commercially with minimal restrictions — a notable stance for a frontier-class model and consistent with DeepSeek's earlier open releases.

Why it matters

MoE designs activate only a fraction of their parameters per token, letting labs scale total capacity while holding inference costs down. Pairing that efficiency with a genuinely open license is what has made DeepSeek's models a fixture in the open-weights ecosystem.

Key points from the record:

• Family: V4-Pro, positioned as the flagship tier
• Focus: text generation, reasoning, and code
• Architecture: mixture-of-experts
• License: MIT

DeepSeek has not published detailed specifications such as parameter counts or context length alongside this listing, so builders will want to consult the model card directly as further documentation and benchmarks appear.