Moonshot

Kimi-latest

moonshot/kimi-latest
/v1/chat/completions/v1/messages/v1/responses/v1beta/models/*/v1/models/*

Kimi-latest是一个最长支持128k上下文的视觉模型,支持图片理解。同时,kimi-latest 模型总是使用Kimi智能助手产品使用最新的Kimi 大模型版本,可能包含尚未稳定的特性。

Input / output modalities
文本 · 图像 to 文本
Reference input / output price
Input¥2Output¥10per 1M tokens
Context window
128K
Added to catalog
Jul 15, 2025

Providers and pricing

ProviderInput lengthInput /MOutput /MCached /MContextMax outputDetails
Moonshot AI≤ 8K¥2¥10¥0128K128K
8K – 32K¥5¥20¥0
≥ 32K¥10¥30¥0

Moonshot AI

Latency
0.59s
Throughput
434 tokens/s
Context
128K

Pricing

Input
¥2/M tokens
Output
¥10/M tokens
Cached
¥0/M tokens

Tiered pricing

Pricing varies by input token range.

0–8K Token

Input tier
¥2/M tokens
Output tier
¥10/M tokens
Cached tier
¥0/M tokens

8K–32K Token

Input tier
¥5/M tokens
Output tier
¥20/M tokens
Cached tier
¥0/M tokens

32K–∞ Token

Input tier
¥10/M tokens
Output tier
¥30/M tokens
Cached tier
¥0/M tokens

Specifications

Context
128K
Max output
128K
Supported APIs
/v1/chat/completions/v1/messages/v1/responses/v1beta/models/*/v1/models/*

Kimi-latest code examples and API guide

Modelmesh normalizes requests and responses across service providers behind one consistent API.

Modelmesh provides an OpenAI-compatible Completion API for more than 300 models and service providers. Call it directly, through the OpenAI SDK, or with supported third-party SDKs.

Modelmesh-specific request headers in these examples are optional. When supplied, your application can appear on the Modelmesh rankings.

Supported endpointsSelect an endpoint to switch the example below.
/v1/chat/completions
from openai import OpenAI API_KEY = "$SSY_API_KEY" client = OpenAI( base_url="https://router.shengsuanyun.com/api/v1", api_key=API_KEY, ) try: completion = client.chat.completions.create( model="moonshot/kimi-latest", messages=[{"role": "user", "content": "Which number is larger, 9.11 or 9.8?"}], temperature=0.6, top_p=0.7, stream=True, ) response_text = "" for chunk in completion: if chunk.choices and chunk.choices[0].delta.content is not None: content = chunk.choices[0].delta.content print(content, end="", flush=True) response_text += content except Exception as error: print(f"Request failed: {error}")
                
              

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