MiniMax

MiniMax-M1

minimax/minimax-m1
/v1/chat/completions/v1/messages/v1/responses/v1beta/models/*/v1/models/*

MiniMax-M1,世界上第一个开源的大规模混合架构的推理模型,适合在复杂场景中使用。

Input / output modalities
文本 to 文本
Reference input / output price
Input¥0.8Output¥8per 1M tokens
Context window
1M
Added to catalog
Jul 15, 2025

Providers and pricing

ProviderInput lengthInput /MOutput /MCached /MContextMax outputDetails
MiniMax≤ 32K¥0.8¥8¥01M80K
32K – 128K¥1.2¥16¥0
≥ 128K¥2.4¥24¥0

MiniMax

Latency
1.62s
Throughput
101 tokens/s
Context
1M

Pricing

Input
¥0.8/M tokens
Output
¥8/M tokens
Cached
¥0/M tokens

Tiered pricing

Pricing varies by input token range.

0–32K Token

Input tier
¥0.8/M tokens
Output tier
¥8/M tokens

32K–128K Token

Input tier
¥1.2/M tokens
Output tier
¥16/M tokens

128K–∞ Token

Input tier
¥2.4/M tokens
Output tier
¥24/M tokens

Specifications

Context
1M
Max output
80K
Supported APIs
/v1/chat/completions/v1/messages/v1/responses/v1beta/models/*/v1/models/*

MiniMax-M1 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="minimax/minimax-m1", 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}")
                
              

Related Models