MoonshotAI: Kimi K2.7 Code

Name: Kimi K2.7 Code API
Brand: moonshotai
Price: 0.71 USD
Availability: OnlineOnly

API Usage

Use the following code examples to integrate with our API:

import OpenAI from 'openai';

if (!process.env.WAVESPEED_API_KEY) throw new Error('Set WAVESPEED_API_KEY');
const client = new OpenAI({
  apiKey: process.env.WAVESPEED_API_KEY,
  baseURL: 'https://llm.wavespeed.ai/v1',
  timeout: 120_000,
  maxRetries: 2,
});

try {
  const response = await client.chat.completions.create({
    model: 'moonshotai/kimi-k2.7-code',
    messages: [{ role: 'user', content: 'Hello!' }],
  });
  console.log(response.choices[0]?.message?.content ?? '');
} catch (error) {
  console.error('LLM request failed:', error);
  process.exitCode = 1;
}

import OpenAI from 'openai';

if (!process.env.WAVESPEED_API_KEY) throw new Error('Set WAVESPEED_API_KEY');
const client = new OpenAI({
  apiKey: process.env.WAVESPEED_API_KEY,
  baseURL: 'https://llm.wavespeed.ai/v1',
  timeout: 120_000,
  maxRetries: 2,
});

try {
  const response = await client.chat.completions.create({
    model: 'moonshotai/kimi-k2.7-code',
    messages: [{ role: 'user', content: 'Hello!' }],
  });
  console.log(response.choices[0]?.message?.content ?? '');
} catch (error) {
  console.error('LLM request failed:', error);
  process.exitCode = 1;
}

Model Introduction

MoonshotAI: Kimi K2.7 Code is a coding-focused model in Moonshot AI's Kimi K2 family, built to complete end-to-end programming tasks reliably over long contexts. It uses a native multimodal mixture-of-experts...

This model is imported from OpenRouter metadata and exposed through the WaveSpeed AI OpenAI-compatible API for chat completions and compatible application workflows.

Why It Looks Great

text+image->text architecture for Text, Image to Text workloads
262144 context window for long prompts, document analysis, and multi-turn workflows
Competitive pricing at $0.71/$3.5 per million tokens
Vision input support for image understanding and multimodal tasks
Function calling and tool-use support for agentic application workflows
Structured output support for JSON responses and schema-constrained generation
Reasoning controls available through supported OpenRouter parameters

Key Features

Context Window: 262144 tokens
Max Input: Not listed
Max Output: 262144 tokens
Vision: Supported
Function Calling: Supported
Structured Outputs: Supported
Image Generation: Not listed
Audio Input: Not listed
Supported Parameters: frequency_penalty, include_reasoning, logit_bias, logprobs, max_tokens, min_p, parallel_tool_calls, presence_penalty, reasoning, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_k, top_logprobs, top_p

Specifications

Specification	Value
Provider	moonshot
Model Type	Chat Completions model
Architecture	text+image->text
Context Window	262144 tokens
Max Input	Not listed
Max Output	262144 tokens
Input	Text, Image
Output	Text
Vision	Supported
Function Calling	Supported
Structured Outputs	Supported
OpenRouter Created	June 12, 2026

Pricing

Token Type	Cost
Input	$0.71 per million tokens
Output	$3.5 per million tokens
Cached Input	$0.15 per million tokens

Note: Pricing is generated from OpenRouter model metadata. If multiple upstream providers expose different endpoint prices, review and adjust the price before publishing.

How to Use

Write your prompt - describe the task, provide context, and specify the desired output format.
Submit - the model processes your request and returns the response.

API Integration

Base URL: https://llm.wavespeed.ai/v1 API Endpoint: chat/completions Model ID: moonshotai/kimi-k2.7-code

API Usage

Python SDK

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://llm.wavespeed.ai/v1"
)

response = client.chat.completions.create(
    model="moonshotai/kimi-k2.7-code",
    messages=[{"role": "user", "content": "Hello!"}]
)

print(response.choices[0].message.content)

cURL

curl https://llm.wavespeed.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "moonshotai/kimi-k2.7-code",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Notes

Model: moonshotai/kimi-k2.7-code
Provider: moonshot
Endpoint availability and provider-specific routing may change on OpenRouter

Sources: OpenRouter model metadata.

Frequently Asked Questions about Kimi K2.7 Code

How much does Kimi K2.7 Code cost via the API?+

Pricing on WaveSpeedAI: $0.71 per million input tokens and $3.50 per million output tokens. Prompt caching and batch processing are billed separately and reduce effective cost on long, repetitive workloads.

What is the context window of Kimi K2.7 Code?+

Kimi K2.7 Code supports up to 262K tokens of context with up to 262K tokens of output per request.

Is Kimi K2.7 Code OpenAI-compatible?+

WaveSpeedAI exposes Kimi K2.7 Code at https://llm.wavespeed.ai/v1 through the OpenAI-compatible Chat Completions interface. Most OpenAI SDK clients work by changing the base URL and API key; optional fields depend on the selected model.

How do I get started with Kimi K2.7 Code?+

Sign in to WaveSpeedAI, create an API key in Access Keys, then send a request to https://llm.wavespeed.ai/v1/chat/completions with the model id shown above. Check the current model catalog for availability, capabilities, and pricing.

Pricing

Try the model

API Usage

Model Introduction