Model Marketplace

Kimi

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Overview

Kimi-K3.1-Pro is the first model in Moonshot AI's new K3.1 series and its most capable 3T-class open-weight model to date. It is a post-trained version of Kimi K3 with substantially larger post-training compute, featuring a 1-million-token context window and native visual understanding (text and image input, text output). Through large-scale joint reinforcement learning across hundreds of downstream domains, it delivers significant gains in coding, 3D creation, financial research, and other long-horizon agentic tasks: scoring 65.7% on Terminal-Bench 4.0, achieving a state-of-the-art 64.4 on OfficeQA Pro v2, and reducing claim-level hallucination rate from 23.4% (K3) to 8.3%. Its overall intelligence approaches leading closed-source frontier models.

Input

TextImage

Output

Text

Features

Prefix Completion

Enable Partial Mode when calling the Qwen API to make the model continue strictly from your provided prefix text.View docs

Function Calling

Use function calling to connect large language models with external tools and systems.View docs

Cache

Context Cache stores shared prefixes for long-context requests to reduce repeated computation, improve latency, and lower cost.View docs

Structured Outputs

Structured Outputs help ensure the model returns a JSON string in the expected format.View docs

Batches

Asynchronously process requests in batches to reduce costs.View docs

Web Search

Enable web search so the model can answer with real-time retrieved data.View docs

Fine-tuning

Train models on sample data to better adapt them to specific tasks.View docs

Pricing

  • Input
    $2Per 1M tokens
  • Output
    $10Per 1M tokens
  • Input(Implicit Cache)
    $0.2Per 1M tokens

Rate Limits & Context

  • Max Input
    1M
  • Max Output
    1M
  • Max Input (Thinking)
    1M
  • Max Output (Thinking)
    1M
  • Context
    1M
  • Max Reasoning
    1M
  • TPMTokens Per Minute
    1200000
  • RPMRequests Per Minute
    10000

Built-in Tools

code_interpreterResponses API
web_extractorResponses API
web_searchResponses API

API Reference

Call API
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import os
from openai import OpenAI

client = OpenAI(
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    base_url="https://ap-southeast-1.maas.qwencloudapi.com/compatible-mode/v1",
)

completion = client.chat.completions.create(
    model="kimi-k3.1-pro",
    messages=[
        {
            "role": "user",
            "content": [
                {
                    "type": "image_url",
                    "image_url": {
                        "url": "https://help-static-aliyun-doc.aliyuncs.com/file-manage-files/zh-CN/20241108/ctdzex/biaozhun.jpg"
                    },
                },
                {"type": "text", "text": "Output the text in the image only."},
            ],
        },
    ],
)
print(completion.choices[0].message.content)