Deepseek V4 Flash vs MiniMax M2.7

DeepSeek V4 Flash is an efficiency-focused Mixture-of-Experts model from DeepSeek with 284B total parameters and 13B active parameters, supporting a 1M-token context window. It is built for fast inference and high-throughput workloads while preserving strong reasoning and coding capabilities. The model features hybrid attention for efficient long-context processing and offers configurable reasoning modes. It is a strong fit for use cases such as coding assistants, chat applications, and agent workflows where responsiveness and cost efficiency matter.

MiniMax-M2.7 is a next-generation large language model built for autonomous, real-world productivity and continuous improvement. Designed to take an active role in its own development, M2.7 incorporates advanced agent capabilities through multi-agent collaboration, allowing it to plan, execute, and improve complex tasks across dynamic environments. Trained for production-level performance, M2.7 supports workflows such as live debugging, root cause analysis, financial modeling, and full document creation across Word, Excel, and PowerPoint. It delivers strong benchmark results, including 56.2% on SWE-Pro and 57.0% on Terminal Bench 2, while reaching 1495 ELO on GDPval-AA, setting a new benchmark for multi-agent systems in real-world digital workflows.