Compare Gemini 4 Argon vs. MiMo-V2-Pro in 2026

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Description

Gemini 4 Argon is a frontier AI model from Google DeepMind built to sustain deep reasoning across complex, long-running professional workflows. Google designed the model for demanding work spanning software engineering, finance, legal tasks, enterprise knowledge work, cybersecurity defense, and creative writing. Argon supports coding, reasoning, multimodality, and multi-step task execution, allowing it to work across workflows that require information gathering, analysis, tool use, and extended problem solving. Its output token limit has been increased from 64,000 to 1 million tokens, giving the model additional capacity for lengthy reasoning and generation within a single trajectory. On DeepSWE v1.1, Google reports a score of 77.9% for real-world long-horizon software engineering, while its AutomationBench score of 51.3% measures performance on end-to-end business workflows. Google also reports strong results on evaluations covering finance, legal work, visual analysis, and long-video understanding, including a 91.7% score on LVBench. For cybersecurity teams, Argon can autonomously discover, validate, and patch software vulnerabilities and achieved a reported 68% score on CWE-bench v1. Google is initially providing the model to selected cyber defenders through its Fairwind Program while strengthening safeguards before expanding access to developers, enterprises, and consumers. Argon is planned to launch at an introductory price of $2 per million input tokens and $10 per million output tokens, with cached input tokens receiving a 95% discount from the standard input price.

Description

Xiaomi MiMo-V2-Pro is an advanced AI foundation model engineered to support real-world agentic workloads and complex workflow orchestration. It serves as the central intelligence for agent systems, enabling seamless coordination of coding, search, and multi-step task execution. The model is built on a large-scale architecture with over a trillion parameters, supporting extended context lengths for handling complex scenarios. It demonstrates strong benchmark performance, particularly in coding and agent-based evaluations, placing it among top-tier global models. MiMo-V2-Pro is optimized for real-world usability, focusing on reliability, efficiency, and practical task completion rather than just theoretical performance. It features improved tool-calling accuracy and stability, making it suitable for integration into production environments. The model also excels in software engineering tasks, offering structured reasoning and high-quality code generation. With its ability to handle long-context interactions, it supports advanced workflows across development and automation use cases. Its API accessibility and competitive pricing make it attractive for developers and enterprises. Overall, MiMo-V2-Pro delivers a balance of scale, intelligence, and real-world performance for modern AI applications.