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Models/Language/DeepSeek V4 Pro (Reasoning, High Effort)
DeepSeek logoDeepSeek·Language ModelsOpen weights

DeepSeek V4 Pro (Reasoning, High Effort)

View rankingsHugging Facedeepseek.com
Context1M
Parameters1.6T
ReleasedApr 2026

DeepSeek V4 Pro is a large-scale Mixture-of-Experts (MoE) language model released by DeepSeek in April 2026. It features a massive architecture with 1.6 trillion total parameters, of which 49 billion are active during any single forward pass. The model is specifically optimized for high-intensity reasoning, complex coding, and agentic tasks, and is designed to rival the capabilities of leading proprietary models while remaining open-source under an MIT license.

The architecture introduces several key innovations, including Engram Conditional Memory, which decouples static factual knowledge from dynamic reasoning through a specialized hash-lookup system. It also utilizes Manifold-Constrained Hyper-Connections (mHC) to ensure training stability and signal propagation across its deep layers. To handle its native 1 million token context window, the model employs DeepSeek Sparse Attention (DSA) and a hybrid attention mechanism (combining Compressed and Heavily Compressed Attention) that significantly reduces KV cache requirements and computational overhead compared to previous generations.

The "Reasoning, High Effort" configuration (often accessed via a "Thinking Mode") allows the model to allocate an extended compute budget to internal chain-of-thought processing before generating a final response. This mode is particularly effective for advanced mathematics, competitive programming, and multi-step agentic workflows where logical consistency is critical. In benchmarks, the model has demonstrated top-tier performance in STEM and coding, effectively bridging the performance gap between open-weights and closed-source frontier models.

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How DeepSeek V4 Pro (Reasoning, High Effort) ranks

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