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Resources & Tools

KIMI-K2.5 TECH REPORT

Kimi K2.5 is an open-source multimodal agentic model designed to advance general intelligence. It features a self-directed parallel agent orchestration framework that dynamically decomposes complex tasks into heterogeneous sub-problems and executes them concurrently. The model achieves state-of-the-art results across various domains, including coding, vision, reasoning, and agentic tasks. Kimi K2.5 shows that scalable and general agentic intelligence can be achieved through joint optimization of text and vision together with parallel agent execution.

DASH

Dash is a self-learning data agent that grounds its answers in six layers of context and continuously improves with every use. It addresses the common shortcomings of raw LLMs in generating SQL, which often fail due to missing context, lack of tribal knowledge, and inability to learn from errors. Dash achieves this by integrating context layers and a unique self-learning loop, which stores both curated "Knowledge" and discovered "Learnings" from past interactions.

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