Kimi K2.7 Code: 1T MoE Model Cuts Tokens 30% and Beats Claude Opus on MCP Calls
The newly released Kimi K2.7 Code, a 1‑trillion‑parameter mixture‑of‑experts model that activates only 32 B parameters per inference, offers a 256 K context window, supports multimodal input, improves benchmark scores by up to 31.5 % over K2.6, reduces inference token usage by about 30 %, and achieves an 81.1 MCP tool‑call score surpassing Claude Opus 4.8, while providing a CLI installation command and usage guidelines.
