New Chinese Model Outperforms DeepSeek v3.1

Kimi AI: The New Chinese Model Outshining DeepSeek V3.1In the rapidly evolving landscape of artificial intelligence, Chinese AI startups are making waves with groundbreaking models that challenge global leaders. Among them, Moonshot AI’s Kimi AI, particularly its Kimi K2 and Kimi 1.5 iterations, has emerged as a formidable contender, reportedly outperforming DeepSeek V3.1 and even rivaling top proprietary models like OpenAI’s GPT-4.1 and Anthropic’s Claude Sonnet 4. With its open-source accessibility, massive context window, and superior performance across benchmarks, Kimi AI is redefining the global AI race. This article explores Kimi’s rise, its technical prowess, and its implications for the future of AI development.The Rise of Kimi AI and Moonshot AIFounded in March 2023 by Yang Zhilin, Zhou Xinyu, and Wu Yuxin, Moonshot AI is a Beijing-based startup named after Pink Floyd’s iconic album The Dark Side of the Moon. Despite its youth, the company has quickly ascended to prominence, earning a $3 billion valuation with backing from giants like Alibaba, Tencent, and Sequoia Capital China. Led by CEO Yang Zhilin, a former Meta AI and Google Brain researcher with a PhD from Carnegie Mellon, Moonshot AI focuses on building large language models (LLMs) optimized for long-form text processing and multimodal capabilities.

Kimi AI, Moonshot’s flagship model, first gained attention with its October 2023 release, boasting the ability to process 200,000 Chinese characters in a single prompt—a feat unmatched by many competitors at the time. The subsequent Kimi 1.5 and Kimi K2 releases have further solidified its reputation, with Kimi K2 being hailed as a “DeepSeek moment” for its disruptive impact.

Kimi’s Technical SuperiorityKimi AI, particularly Kimi K2, is a sparse Mixture-of-Experts (MoE) model with 1 trillion total parameters, activating 32 billion per inference—surpassing DeepSeek V3’s 671 billion parameters (37 billion active). Trained on 15.5 trillion tokens using a novel MuonClip optimizer, Kimi K2 achieves remarkable stability and efficiency, outperforming the industry-standard AdamW optimizer. This model is designed for agentic workflows, excelling in tasks like coding, math, and multimodal reasoning without relying on extensive chain-of-thought (CoT) processes, unlike DeepSeek’s reasoning-focused R1 model.

Try Kimi v2 Now