Name: Kimi K2 Thinking API
Brand: Moonshot AI

Overview

What is Kimi K2 Thinking API?

Kimi K2 Thinking is available through AIMLAPI.

Technical Specifications
- Supported inputs: Image, Text
- Output: Text
- Context window: 262,144 tokens / Max output: 100,352 tokens
- Endpoint: /chat/completions

Performance Benchmarks
[embed]

Kimi K2 Thinking API Pricing
- Input: $0.78 / 1M tokens
- Output: $3.25 / 1M tokens

Where to Use Kimi K2 Thinking

Coding and code review
Generate, debug, and review code across languages, reading whole files or repos in a single prompt.

Agentic and multi-step workflows
Reliable tool-calling and instruction-following suit agent loops that plan, call tools, and iterate.

Complex reasoning
Extended reasoning improves reliability on multi-step math, logic, and technical analysis.

Long-document analysis
Summarize and extract from contracts, papers, and reports without aggressive chunking.

Code Sample
[embed]

Uptime and performance

Uptime (7d): 93.0%

Measured on the AI/ML API gateway across live traffic. Figures are medians unless stated. Last updated 2026-10-12.

Use cases

Autonomous research workflows are a documented use case for Kimi K2 Thinking, including long-horizon research tasks and web browsing with information synthesis.

Complex coding projects are another documented use case, including coding workflows that can span hundreds of steps and autonomous execution.

Mathematical problem-solving is documented as a use case, with emphasis on extended reasoning for complex math tasks.

Tool-orchestrated task execution is also documented, where the model dynamically invokes tools to carry out multi-step actions.

How to use Kimi K2 Thinking API

Install any OpenAI-compatible SDK, point it at api.aimlapi.com/v1, and set the model to moonshotai/kimi-k2-thinking.

import requests

r = requests.post(
    "https://api.aimlapi.com/v1/chat/completions",
    headers={"Authorization": "Bearer " + AIMLAPI_KEY},
    json={
      "model": "moonshotai/kimi-k2-thinking",
      "messages": [
        {
          "role": "user",
          "content": "Hello!"
        }
      ]
    },
)
print(r.json())

const r = await fetch("https://api.aimlapi.com/v1/chat/completions", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${process.env.AIMLAPI_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    "model": "moonshotai/kimi-k2-thinking",
    "messages": [
      {
        "role": "user",
        "content": "Hello!"
      }
    ]
  }),
});
console.log(await r.json());

curl -X POST https://api.aimlapi.com/v1/chat/completions \
  -H "Authorization: Bearer $AIMLAPI_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"moonshotai/kimi-k2-thinking","messages":[{"role":"user","content":"Hello!"}]}'

OpenAI-compatible — swap the base URL and it works with your existing SDK.