MiniMax

MiniMax M2.5

minimax/minimax-m2.5
/v1/chat/completions/v1/messages/v1/responses/v1beta/models/*/v1/models/*

在 MiniMax 真实业务场景中,整体任务的 30% 由 M2.5 自主完成,覆盖研发、产品、销售、HR、财务等职能,且渗透率仍在持续上升。其中,在编程场景表现尤为突出,M2.5 生成的代码已占新提交代码的 80%。

Input / output modalities
Not provided to Not provided
Reference input / output price
Input¥2.1Output¥8.4per 1M tokens
Context window
200K
Added to catalog
Feb 13, 2026

Providers and pricing

ProviderInput /MOutput /MCached /MContextMax outputDetails
Other-A¥2.1¥8.4¥0.21200K131K
MiniMax¥2.1¥8.4¥0.21200K131K

Other-A

Latency
9.38s
Throughput
22 tokens/s
Context
200K

Pricing

Input
¥2.1/M tokens
Output
¥8.4/M tokens
Cached
¥0.21/M tokens

Additional pricing

Cache write
¥2.63
Cache read
¥0.21

Specifications

Context
200K
Max output
131K
Supported APIs
/v1/chat/completions/v1/messages/v1/responses/v1beta/models/*/v1/models/*

MiniMax

Latency
3.6s
Throughput
157 tokens/s
Context
200K

Pricing

Input
¥2.1/M tokens
Output
¥8.4/M tokens
Cached
¥0.21/M tokens

Additional pricing

Cache write
¥2.63
Cache read
¥0.21

Specifications

Context
200K
Max output
131K
Supported APIs
/v1/chat/completions/v1/messages/v1/responses/v1beta/models/*/v1/models/*

MiniMax M2.5 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/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-m2.5", 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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