- What is the context window size of Kimi K2.5?
- Kimi K2.5 features an industry-leading 2M token context window, allowing it to process entire codebases or libraries while maintaining retrieval accuracy.
- How does Kimi K2.5 handle computational efficiency?
- The model integrates advanced Mixture-of-Experts (MoE) techniques, which reduce latency compared to dense models of similar size while balancing high-performance output.
- What are the primary use cases for Kimi K2.5?
- It is engineered for tasks requiring long-context processing, such as legal discovery, academic research summarization, software engineering refactoring, and financial analysis.
- What are the limitations of Kimi K2.5?
- The model is primarily optimized for Chinese and English, with lower performance in minor languages, and its multimodal features are less mature than some Western competitors.
- How is Kimi K2.5 priced?
- API input and output costs are ¥12.00 per 1M tokens (approx. $1.65 USD), with free access available via the Kimi.ai app subject to daily limits.