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Kimi

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Text GenerationVisual UnderstandingReasoning

Overview

Text GenerationVisual UnderstandingReasoning

kimi-k2.7-code is Kimi's most intelligent coding model to date. It follows instructions more reliably over long contexts and completes programming tasks with higher success rates. It supports text, image, and video inputs, along with thinking mode, conversation, and agent tasks.

Input

TextImageVideo

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

Web Search

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

feature.funeTuning

Pricing

  • Input
    $0.95Per 1M tokens
  • Output
    $4Per 1M tokens
  • Input(Implicit Cache)
    $0.19Per 1M tokens

toc.rateLimitsAndContext

  • Max Input
    229.37K
  • Max Output
    16.38K
  • RPMRequests Per Minute
    500
  • TPMTokens Per Minute
    1M
  • Context
    262.14K

API Reference

Get API Key
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import os
import dashscope
dashscope.base_http_api_url = 'https://dashscope-intl.aliyuncs.comapi/v1'
messages = [
{
    "role": "user",
    "content": [
    {"text": "Who are you?"}]
}]
response = dashscope.MultiModalConversation.call(
    # If the environment variable is not set, replace it with your Model Studio API key: api_key = "sk-xxx",
    api_key = os.getenv('DASHSCOPE_API_KEY'),
    model = 'kimi-k2.7-code',
    messages = messages
)
print(response.output.choices[0].message.content[0]["text"])