Earlier this year, Chinese startup DeepSeek made headlines by offering a free AI model, DeepSeek-R1, which it claims can match ChatGPT-level performance. Now, another Chinese startup, Moonshot AI, has announced its Kim K2 Reasoning model, which it claims outperforms OpenAI’s GPT-5 and Anthropic’s Claude Sonnet 4.5 on key benchmarks. Kimi K2 outperforms both GPT-5 and Claude 4.5 in BrowseComp and Seal-O. These benchmarks are used to evaluate the reasoning and browsing abilities of AI agents. However, when testing the coding on some benchmarks, the Kimi K2 falls short of the two. The open source model is free to users. ChatGPT Plus and Claude, on the other hand, cost around $20 per month for their premium tiers.
Kim K2 is a large language model (LLM) trained with approximately 1 trillion parameters, but designed to use them efficiently. This is an expert mix design, meaning that only a certain number of parameters are used to process and respond to prompts. Kimi K2 uses only 32 billion activation parameters at a time, making it fast and cheap to run. On the other hand, dense models such as GPT‑5 and Claude Sonnet 4.5 use far more parameters to process prompts, which provides better peak performance but typically increases computation, latency, and cost.
Next to DeepSeek, Alibaba-backed Moonshot is another China-based AI startup that develops language models at scale at a much lower cost than its U.S. competitors. According to CNBC, Moonshot trained Kimi K2 for about $4.6 million. Unlike other popular large-scale language models, Kimi K2 is not yet mainstream, but there are multiple ways to access it.
Here’s how to use the Kim K2 AI model:
For regular users, the easiest way to access Kimi K2 is through the official chat interface at Kimi.com. You must be logged in to access the model. Unlimited usage with no tokens or time limits. Apart from the official website, the models are accessible through the Hugging Face platform, which allows users to try out new open source AI models and applications. The Kimi K2 Instruct space allows users to try out prompts and receive responses directly in the browser. You can create a Hugging Face account or sign in using your existing account to get started. Because the platform runs on a shared infrastructure, it may feel slow to respond. There are also some advanced options. If you are comfortable with coding, OpenRouter provides a way for developers to access this model. You need to sign up for openrouter.ai and create an API key from your dashboard.
If you want more control, self-hosting, which allows you to run models on your own hardware, is also an option. To do this, download Kim K2’s model file from Hugging Face and run it on your own hardware using an inference tool such as vLLM or SGLang. The benefits of self-hosting are faster response times, better model performance, and data privacy. However, this is a demanding and costly process. Handling heavy models such as Kimi K2 requires a powerful GPU, large amount of RAM, and sufficient storage. This makes the free web interface a much more practical and affordable option for casual users who want to test Moonshot’s Kim K2 model without investing in expensive hardware or spending time and effort on complicated processes.
