DeepSeek V4 Pro is a large open-weight Mixture-of-Experts language model built around a hybrid attention design that pairs Compressed Sparse Attention with Heavily Compressed Attention, allowing it to process very long inputs while spending only a fraction of the inference compute that earlier generations required. Across its 1.6 trillion total parameters, only about 49 billion are activated per token, keeping single-token cost low relative to its overall capacity. The model's preparation pipeline first cultivates separate domain experts through supervised fine-tuning and group-relative policy optimization, then merges them into a unified system via on-policy distillation, a strategy that aims to preserve specialist strengths while delivering coherent, general-purpose reasoning.

On the UnoRouter unified API, DeepSeek V4 Pro is exposed as a free text-in, text-out endpoint, sitting alongside a broad catalog of paid and complimentary models that developers can route through a single key. Its Mixture-of-Experts backbone and compressed-attention design make it well suited to long-context analytical workloads, code and reasoning chains, and tool-augmented agents that benefit from deep parameter counts without paying the full inference price of dense models. Because the weights are openly available under an MIT-style license, teams can also self-host the same architecture for production or research, while UnoRouter offers a convenient hosted path for quick experimentation and integration into applications.