Kimi-k2 Thinking – A Reasoning Model Released by Moonshot AI

What is Kimi-k2 Thinking?

Kimi-k2 Thinking is an AI model released by Moonshot AI that features general agentic capabilities and deep reasoning abilities. The model can perform multi-step tool calling, supports up to 256k context length, and is designed for complex tasks requiring step-by-step reasoning and planning. Its reasoning process is displayed through a reasoning_content field, helping users understand the model’s logic. Kimi-k2 Thinking also includes a high-speed variant, Kimi-k2 Thinking-turbo, which reaches inference speeds of up to 100 tokens/s, making it suitable for efficiency-critical scenarios.

Main Features of Kimi-k2 Thinking

Deep reasoning:
Capable of complex logical reasoning and multi-step problem solving, suitable for tasks requiring thorough analysis.

Multi-round tool calling:
Supports calling multiple external tools (e.g., search engines, APIs) during reasoning, dynamically adjusting the next steps based on intermediate results.

Long-context processing:
Handles up to 256k tokens, allowing it to work with long-form content and multi-step task planning.

Transparent reasoning:
Displays its reasoning process in the reasoning_content field, improving interpretability and helping users understand the model’s decision path.

High-efficiency inference:
The turbo version provides inference speeds up to 100 tokens/s, designed for scenarios where speed is essential.

Cost optimization:
Balances reasoning performance with efficiency, making it suitable for high-value complex tasks that must remain cost-effective.

Usage Notes for Kimi-k2 Thinking

Provide full context:
When calling the model, include all relevant content (especially the reasoning_content field) so the model can reason with the complete logical chain.

Set a sufficiently large max_tokens:
A recommended ≥16,000 to ensure the model can output both the reasoning process and final results completely.

Use temperature = 1.0:
Setting temperature = 1.0 yields optimal performance and stable reasoning.

Enable streaming output:
Use stream=True for a smoother experience and to avoid timeouts due to large outputs.

Application Scenarios of Kimi-k2 Thinking

Complex problem solving:
For tasks requiring multi-step reasoning—such as scientific experiment design, engineering optimization, and advanced logic problems.

Automated task planning:
Suitable for workflows requiring dynamic adjustments and multi-round decisions, such as automated pipeline design or resource allocation.

Data analysis and reporting:
Handles large-scale data and complex logic, generating in-depth reports on market trends, financial forecasting, and more.

Intelligent search and information integration:
Uses multi-round tool calling to aggregate information from multiple sources, giving users comprehensive answers.

Education and learning support:
Helps students solve complex academic questions step-by-step, providing reasoning paths and solution logic.