Kimi杨植麟称“训练成本很难量化”，仍将坚持开源策略

Core Insights - Kimi, an AI startup, has released its latest open-source model, Kimi K2 Thinking, with a reported training cost of $4.6 million, significantly lower than competitors like DeepSeek V3 at $5.6 million and OpenAI's GPT-3, which costs billions to train [1][2] - The company emphasizes ongoing model updates and improvements, focusing on absolute performance while addressing user concerns regarding inference length and performance discrepancies [1] - Kimi's strategy includes maintaining an open-source approach and advancing the Kimi K2 Thinking model while avoiding direct competition with major players like OpenAI through innovative architecture and cost control [2][4] Model Performance and Market Position - In the latest OpenRouter model usage rankings, five Chinese open-source models, including Kimi's, are among the top twenty, indicating a growing presence in the international market [2] - Kimi's current model can only be accessed via API due to platform limitations, but the team is utilizing H800 GPUs with InfiniBand technology for training, despite having fewer resources compared to U.S. high-end GPUs [2] - The company plans to balance text model development with multi-modal model advancements, aiming to establish a differentiated advantage in the AI landscape [4]