Kimi K2.7 Code is a coding-focused agentic model built upon Kimi K2.6. With substantial improvements on real-world long-horizon coding tasks, it strengthens end-to-end task completion across complex software engineering workflows while improving token efficiency, reducing thinking-token usage by approximately 30% compared with Kimi K2.6....

Kimi K2.6 is an open-source, native multimodal agentic model by Moonshot AI, achieving open-source state-of-the-art on benchmarks including HLE with tools, SWE-Bench Pro, and BrowseComp. Built on a MoE architecture with 1T total parameters and 32B activated, the model supports a 256K-token context window and multimodal inputs (image and video) via its MoonViT vision encoder. K2.6 is optimized for agentic workloads: it sustains 4,000+ tool calls over 12+ hours of continuous execution, scales to 300 parallel sub-agents × 4,000 steps per run to produce 100+ files from a single prompt, and supports both Thinking and Instant inference modes with function calling and multi-turn Preserve Thinking...

Kimi K2.5 是一种开源、原生 Multimodal 主动模型，通过在 Kimi-K2-Base 上进行大约 15 万亿混合视觉和 Text tokens 的持续预训练构建而成。凭借 1T 参数 MoE 架构（32B 活跃）和 256K 上下文长度，它无缝集成了 Vision 和语言理解与先进的主动功能，支持即时和思考模式，以及对话和主动范式。...