Kimi-K2 API: High-Performance Agentic Intelligence
Execute tools, write code, and automate workflows with Agent‑First Design.
Kimi-K2: Scale tool-use, automation, and code generation
Moonshot AI’s Kimi-K2 is a 1T‑parameter Mixture‑of‑Experts model with 32B active experts per inference. Trained on 15.5T tokens using the MuonClip optimizer, it’s built for deep agent behavior — tool-calling, API integration, and real-world code execution. Inspired by DeepSeek V3, it natively supports tool-use via RL and multi-domain pipelines — including real APIs and synthetic environments — without additional fine-tuning.
Modular MoE Architecture
Using MuonClip, Kimi-K2 achieves stable training on 15.5T tokens. MoE routing enables efficient inference with only 32B active experts, offering unmatched performance per cost.
SOTA in Tool Use
Top performer on SWE‑bench Verified (65.8%) and LiveCodeBench (53.7%), exceeding GPT‑4.1, Claude Sonnet 4, Gemini 2.5 Flash, and DeepSeek V3.
Agentic Intelligence Built-In
Trained via RL pipelines that simulate hundreds of tool-based environments using checker-style rewards, the model “acts” as much as “thinks,” enabling autonomous API calling and multi-step workflows.
Kimi AI Enterprise Use Cases
Kimi-K2 enables scalable deployment of agents that can reason, act via tools, and handle complex domain-specific workflows.
Software Development
Automate code generation, bug fixing, CI/CD pipelines, and code reviews with tool-aware agents that reason across files.
Customer Support Agents
Build bots that can fetch data, call APIs, submit tickets, and coordinate services programmatically.
Process Automation
Execute domain-specific tasks like document parsing, form filling, or API-driven workflows with agent reliability.
Kimi-K2 Delivers State-of-the-Art Coding and Tool Use
While not optimized for abstract reasoning, Kimi-K2 consistently outperforms top models in coding and agent-based tasks.
Kimi-K2 vs GPT-4.1
GPT-4.1 remains strong in general reasoning, but Kimi-K2 delivers better accuracy on code tasks with a 65.8% SWE-bench score. Its open MoE architecture (1T total / 32B active) enables faster inference and more efficient API-driven workflows.
Learn more about GPT-4.1 API.
Kimi-K2 vs Claude 4 Sonnet
Kimi-K2 achieves 65.8% on SWE-bench and 53.7% on LiveCodeBench, outperforming Claude 4 Sonnet in zero-shot code generation and tool-use scenarios. While Sonnet excels in multilingual reasoning, Kimi-K2 provides higher coding accuracy and agentic flexibility for real-world automation.
Learn more about Claude 4 API.
Kimi-K2 vs Gemini 2.5 Flash
Gemini 2.5 Flash prioritizes speed, often sacrificing reasoning depth. Kimi-K2 surpasses it in structured programming tasks — 53.7% on LiveCodeBench — and is better suited for complex pipeline orchestration with native tool execution.
Learn more about Gemini 2.5 Flash API.
Why Choose AI/ML API solution?
AI/ML API provides scalability, faster deployment, and access to 200+ advanced machine learning models without the need for extensive in-house expertise or infrastructure.
Easy To Use
Our API allows seamless integration of powerful AI capabilities into your applications, regardless of your coding experience. Simply swap your API key to begin using the AI/ML API.
Scalable
AI/ML API provides flexibility for business growth since you can scale resources by purchasing more tokens as needed, ensuring optimal performance and cost efficiency
Affordable
We offer flat, predictable pricing, payable by card or cryptocurrency, keeping it the lowest on the market and affordable for everyone.
Kimi-K2 API
Coming Soon
While we’re adding Kimi-K2, you can check out our other models and try them in AI Playground.