Deepseek V4 Pro vs MiniMax M3

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.

MiniMax-M3 is a multimodal foundation model from MiniMax. It supports text, image, and video inputs with text output, a 1M-token context window, and is suited for long-horizon agentic work, coding, and tool use. It is built on MiniMax Sparse Attention (MSA), which replaces full attention with KV-block selection to cut per-token compute at long context — roughly 1/20 the cost of the previous generation at 1M tokens, with substantially faster prefill and decode while retaining quality across most tasks. Trained as a native multimodal model on interleaved data and tuned for multi-turn, production-like collaboration via an interactive user-simulator framework, the model is oriented toward sustained, multi-step tasks rather than single-turn execution.