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Kakao has released Kanana-2, a high-performance open-source language model specifically engineered to power Agentic AI by enhancing tool-calling and instruction-following capabilities. Surpassing its predecessors and rivaling global frontier models like Qwen3, Kanana-2 offers a versatile suite of variants designed for practical, high-efficiency application in complex service environments.

Optimized Model Lineup: Base, Instruct, and Thinking

  • Kanana-2-30b-a3b-base: Provided as a foundational model with pre-training weights, allowing researchers to fine-tune the model using their own datasets.
  • Kanana-2-30b-a3b-instruct: A version optimized through post-training to maximize the model's ability to follow complex user instructions accurately.
  • Kanana-2-30b-a3b-thinking: Kakao’s first reasoning-specialized model, designed for tasks requiring high-level logical thinking, such as mathematics and coding.

Strengthening Agentic AI Capabilities

  • Tool Calling: Multi-turn tool-calling performance has improved more than threefold compared to Kanana-1.5, significantly enhancing its utility with the Model Context Protocol (MCP).
  • Instruction Following: The model's ability to understand and execute multi-step, complex user requirements has been refined to ensure reliable task completion.
  • Reasoning-Tool Integration: Unlike many reasoning models that lose instruction-following quality during deep thought, the "Thinking" variant maintains high performance in both logical deduction and tool use.

High-Efficiency Architecture for Scale

  • MLA (Multi-head Latent Attention): Compresses memory usage to handle long contexts more efficiently, reducing the resources needed for extensive data processing.
  • MoE (Mixture of Experts): Activates only the necessary parameters during inference, maintaining high performance while drastically reducing computational costs and response times.
  • Improved Tokenization: A newly trained tokenizer has improved Korean language token efficiency by 30%, enabling faster throughput and lower latency in high-traffic environments like KakaoTalk.

Expanded Multilingual Support

  • Broad Linguistic Reach: The model has expanded its support from just Korean and English to include six languages: Korean, English, Japanese, Chinese, Thai, and Vietnamese.

By open-sourcing Kanana-2, Kakao provides a robust foundation for developers seeking to build responsive, tool-integrated AI services. Its focus on practical efficiency and advanced reasoning makes it an ideal choice for implementing agentic workflows in real-world applications where speed and accuracy are critical.