Deepseek v3.2 vs Deepseek V4 Pro

DeepSeek-V3.2 is a large language model optimized for high computational efficiency and strong tool-use reasoning. It features DeepSeek Sparse Attention (DSA), a mechanism that lowers training and inference costs while maintaining quality in long-context tasks. A scalable reinforcement learning post-training framework further enhances reasoning, achieving performance comparable to GPT-5 and earning top results on the 2025 IMO and IOI. V3.2 also leverages large-scale agentic task synthesis to improve reasoning in practical tool-use scenarios, boosting its generalization and compliance in interactive environments.

DeepSeek V4 Pro is a large-scale Mixture-of-Experts model from DeepSeek with 1.6T total parameters and 49B active parameters, supporting a 1M-token context window. It is designed for advanced reasoning, coding, and long-horizon agent workflows, delivering strong results across knowledge, mathematics, and software engineering benchmarks. Built on the same architecture as DeepSeek V4 Flash, it adds a hybrid attention system for efficient long-context processing and supports multiple reasoning modes to balance speed and depth based on the task. It is well suited for demanding workloads such as full-codebase analysis, multi-step automation, and large-scale information synthesis, where both performance and efficiency are essential.