Kimi K2.5 is an open-source, native multimodal agentic model built through continual pretraining on approximately 15 trillion mixed visual and text tokens atop Kimi-K2-Base. With a 1T-parameter MoE architecture (32B active) and 256K context length, it seamlessly integrates vision and language understanding with advanced agentic capabilities, supporting both instant and thinking modes, as well as conversational and agentic paradigms...

Kimi K2 Thinking is the latest, most capable version of open-source thinking model. Starting with Kimi K2, we built it as a thinking agent that reasons step-by-step while dynamically invoking tools. It sets a new state-of-the-art on Humanity's Last Exam (HLE), BrowseComp, and other benchmarks by dramatically scaling multi-step reasoning depth and maintaining stable tool-use across 200–300 sequential calls. At the same time, K2 Thinking is a native INT4 quantization model with 262k context window, achieving lossless reductions in inference latency and GPU memory usage...

Kimi K2-Instruct-0905, a state-of-the-art mixture-of-experts (MoE) language model, is the latest, most capable version of Kimi K2. Key Features include enhanced coding capabilities, esp. front-end & tool-calling, context length extended to 256k tokens, and improved integration with various agent scaffolds....

Kimi K2 is a Mixture-of-Experts (MoE) foundation model with exceptional coding and agent capabilities, featuring 1 trillion total parameters and 32 billion activated parameters. In benchmark evaluations covering general knowledge reasoning, programming, mathematics, and agent-related tasks, the K2 model outperforms other leading open-source models...