Kimi K2.5: Multimodal Agentic Intelligence

Kimi K2.5, developed by Moonshot AI, is an open-source, native multimodal agentic model built on a Mixture-of-Experts (MoE) architecture. It features 1 trillion total parameters with 32 billion activated parameters and an extensive 256K context length. The model was continually pre-trained on approximately 15 trillion mixed visual and text tokens, enabling seamless integration of vision and language understanding with advanced agentic capabilities.

Key Capabilities

• Native Multimodality: Excels in visual knowledge, cross-modal reasoning, and agentic tool use grounded in visual inputs, including image and video processing.
• Coding with Vision: Generates code from visual specifications (e.g., UI designs, video workflows) and autonomously orchestrates tools for visual data processing.
• Agent Swarm: Decomposes complex tasks into parallel sub-tasks executed by dynamically instantiated, domain-specific agents, moving beyond single-agent scaling.
• Dual Modes: Supports both 'Thinking' and 'Instant' modes for varied response behaviors, with recommended temperature settings for each.

Good For

• Applications requiring advanced visual understanding and reasoning.
• Automated code generation from visual inputs.
• Complex, multi-step tasks benefiting from coordinated agentic execution.
• Long-context multimodal interactions, demonstrated by strong performance on benchmarks like Longbench v2 and AA-LCR.