Just saw the news—KIMI K3 is now fully open-source globally . What does this mean? 'Fully open-source' for Kimi K3 means that MoonDark has released everything they’ve been keeping under wraps: complete model weights, technical reports, and even the underlying infrastructure technology that supports model training. Anyone in the world can download it for free, deploy it locally, modify it, or even use it commercially. MoonDark is absolutely insane, right? Are they trying to go head-to-head with DeepSeek? How is this different from the usual 'open-source'? In the past, many models claimed to be open-source but only provided an API or a stripped-down version of the weights, keeping the real core stuff tightly locked away. But this time, Kimi K3 has laid everything bare. Specifically, it includes three major components: 1. Complete model weights. 2.8 trillion parameters, compressed to about 1.4TB, available on Hugging Face. If you’ve got the hardware, you can download this entire brain. 2. A 47-page technical report detailing the KDA hybrid attention mechanism, the sparse MoE architecture (896 selects 16), and the visual encoder training methods—these are all top-secret-level details. 3. Three foundational training infrastructure technologies: MoonEP (high-performance communication library), FlashKDA (attention operator), and AgentEnv (distributed agent sandbox). It’s like they’re not just giving you the 'recipe,' but also the 'pots' and 'stove.' What’s the cost? The entry ticket for full local deployment is roughly 1.7 to 2.4 million RMB (the cost of an 8×AMD MI355X server). To truly run it, you’d need 64 accelerator cards and hardware investments in the tens of millions. For regular users and small-to-medium businesses, it’s still a 'luxury item.' However, API calls are super cheap, and Kimi’s smart assistant is already integrated—daily use for regular users is completely free. Why do this? The logic of open-source is entirely different from closed-source. OpenAI treats AI as a premium product to sell, while MoonDark treats AI as infrastructure to build. When the whole world can freely access a 'digital brain' close to GPT-5.6 level, those closed-source giants in the U.S. who rely on selling API access will face a real pricing challenge. This reflects two completely different approaches: U.S. closed-source giants guard their high walls and charge entry fees, while China’s open-source ecosystem builds roads and bridges, lowering the threshold for cutting-edge intelligence to the ground. So, in the AI large model competition between China and the U.S., who will come out on top? Who will have the last laugh? Personally, I think the U.S. AI large models will ultimately lose! In terms of cost-effectiveness and global application scenarios, China’s AI large models have already completely outperformed their U.S. counterparts. What do you guys think?