在这个开源「从夯到拉」榜单，我终于明白中国 AI 为什么能逆袭

Core Insights - The recent ranking of open-source AI models highlights the dominance of Chinese models, with DeepSeek, Qwen, Kimi, Zhipu, and MiniMax leading the global landscape, while OpenAI and Meta's models lag behind [3][5][25]. Group 1: Performance and Market Position - Chinese open-source models are rapidly closing the performance gap with closed-source giants, excelling in dimensions such as performance, pricing, ecosystem, and usability [5][25]. - Kimi's K2 Thinking model, featuring a trillion parameters, has outperformed OpenAI's GPT-5 and Anthropic's Claude 4.5 in various benchmarks [11][14]. - MiniMax M2 has also shown strong performance, ranking fifth in comprehensive lists, surpassing competitors like Gemini 2.5 Pro and Claude Opus 4.1 [14][79]. Group 2: Technological Advancements - The introduction of interleaved thinking in models like MiniMax M2 and Kimi K2 Thinking allows for more efficient task execution by alternating between action and reflection [34][36]. - MiniMax M2 employs a full attention mechanism, which, despite increasing training and inference demands, has proven to deliver better performance compared to sparse attention models [75][78]. Group 3: Cost and Accessibility - MiniMax's API offers competitive pricing at $0.3/$1.2 per million input/output tokens, although its verbose nature leads to high token usage, which can offset cost advantages [79]. - The open-source movement in China is gaining momentum, with MiniMax's release reinforcing the leadership established by DeepSeek and other Chinese AI labs in the open-source domain [80][84]. Group 4: Community and Developer Adoption - There is a growing recognition among developers for the practicality and affordability of Chinese open-source models, with many citing them as preferable alternatives to established closed-source options like OpenAI [25][84]. - The rapid updates and releases from various Chinese companies indicate a robust and collaborative open-source ecosystem that is continuously evolving [11][14].