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LongCat

LongCat-2.5

longcat/longcat-2.5
/v1/completions/v1/chat/completions/v1/messages/v1/responses/v1beta/models/*/v1/models/*

LongCat-2.5 是美团龙猫团队发布的原生多模态大模型,采用 MoE 架构,总参数约 1.6 万亿、每次推理激活约 480 亿参数,原生支持 100 万 token 上下文,面向终端、浏览器、GUI、电子表格和设计工具等真实操作场景,通过大规模长程强化学习强化长程智能体任务与智能体编程能力。

Input / output modalities
文本 · 图像 to 文本
Reference input / output price
Input¥2Output¥8per 1M tokens
Context window
1M
Added to catalog
Nov 2, 2026

Providers and pricing

ProviderInput /MOutput /MCached /MContextMax outputDetails
LongCat¥2¥8¥0.041M256K

LongCat

Latency
3.76s
Throughput
82 tokens/s
Context
1M

Pricing

Input
¥2/M tokens
Output
¥8/M tokens
Cached
¥0.04/M tokens

Specifications

Context
1M
Max output
256K
Supported APIs
/v1/completions/v1/chat/completions/v1/messages/v1/responses/v1beta/models/*/v1/models/*

LongCat-2.5 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/completions
from openai import OpenAI API_KEY = "$SSY_API_KEY" client = OpenAI( base_url="https://router.shengsuanyun.com/api/v1", api_key=API_KEY, ) response = client.completions.create( model="longcat/longcat-2.5", prompt="Enter your request here", max_tokens=1024, ) print(response.choices[0].text)
                
              

Related Models

No related models are currently available.