m2-5-highspeed

This documentation is valid for the following list of our models:

• minimax/m2-5-highspeed-20260218

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Model Overview

A chat model designed for high-throughput usage, reportedly capable of generating up to 100 tokens per second, and highly optimized for coding, agentic workflows, and complex reasoning, while maintaining low latency and low operational cost.

Create AI/ML API Key

How to make the first API call

If you need a more detailed walkthrough for setting up your development environment and making a request step by step — feel free to use our Quickstart guide.

API Schema

post

Body

application/json

modelstring · enumRequiredPossible values:

max_tokensnumber · min: 1Optional

The maximum number of tokens that can be generated in the chat completion. This value can be used to control costs for text generated via API.

streambooleanOptional

If set to True, the model response data will be streamed to the client as it is generated using server-sent events.

Default: false

tool_choiceany ofOptional

Controls which (if any) tool is called by the model. none means the model will not call any tool and instead generates a message. auto means the model can pick between generating a message or calling one or more tools. required means the model must call one or more tools. Specifying a particular tool via {"type": "function", "function": {"name": "my_function"}} forces the model to call that tool. none is the default when no tools are present. auto is the default if tools are present.

string · enumOptional

none means the model will not call any tool and instead generates a message. auto means the model can pick between generating a message or calling one or more tools. required means the model must call one or more tools.

Possible values:

or

parallel_tool_callsbooleanOptional

Whether to enable parallel function calling during tool use.

temperaturenumber · max: 2Optional

What sampling temperature to use. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. We generally recommend altering this or top_p but not both.

top_pnumber · min: 0.01 · max: 1Optional

An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered. We generally recommend altering this or temperature but not both.

logprobsboolean · nullableOptional

Whether to return log probabilities of the output tokens or not. If True, returns the log probabilities of each output token returned in the content of message.

top_logprobsnumber · max: 20 · nullableOptional

An integer between 0 and 20 specifying the number of most likely tokens to return at each token position, each with an associated log probability. logprobs must be set to True if this parameter is used.

frequency_penaltynumber · min: -2 · max: 2 · nullableOptional

Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim.

seedinteger · min: 1Optional

This feature is in Beta. If specified, our system will make a best effort to sample deterministically, such that repeated requests with the same seed and parameters should return the same result.

presence_penaltynumber · min: -2 · max: 2 · nullableOptional

Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics.

response_formatone ofOptional

An object specifying the format that the model must output.

or

or

Responses

200Success

application/jsontext/event-stream

idstringRequired

A unique identifier for the chat completion.

Example: chatcmpl-CQ9FPg3osank0dx0k46Z53LTqtXMl

objectstring · enumRequired

The object type.

Example: chat.completionPossible values:

creatednumberRequired

The Unix timestamp (in seconds) of when the chat completion was created.

Example: 1762343744

modelstringRequired

The model used for the chat completion.

Example: minimax/m2-5-highspeed-20260218

post

/v1/chat/completions

cURLJavaScriptPython

curl -L \
  --request POST \
  --url 'https://api.aimlapi.com/v1/chat/completions' \
  --header 'Authorization: Bearer <YOUR_AIMLAPI_KEY>' \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "minimax/m2-5-highspeed-20260218",
    "messages": [
      {
        "role": "user",
        "content": "Hello"
      }
    ]
  }'

200Success

{
  "id": "chatcmpl-CQ9FPg3osank0dx0k46Z53LTqtXMl",
  "object": "chat.completion",
  "created": 1762343744,
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "Hello! I'm just a program, so I don't have feelings, but I'm here and ready to help you. How can I assist you today?",
        "refusal": null,
        "annotations": null,
        "audio": null,
        "tool_calls": null
      },
      "finish_reason": "stop",
      "logprobs": null
    }
  ],
  "model": "minimax/m2-5-highspeed-20260218",
  "usage": {
    "prompt_tokens": 137,
    "completion_tokens": 914,
    "total_tokens": 1051,
    "completion_tokens_details": null,
    "prompt_tokens_details": null
  }
}

Code Example

Python

import requests
import json  # for getting a structured output with indentation 

response = requests.post(
    "https://api.aimlapi.com/v1/chat/completions",
    headers={
        # Insert your AIML API Key instead of <YOUR_AIMLAPI_KEY>:
        "Authorization":"Bearer <YOUR_AIMLAPI_KEY>",
        "Content-Type":"application/json"
    },
    json={
        "model":"minimax/m2-5-highspeed-20260218",
        "messages":[
            {
                "role":"user",
                "content":"Hi! What do you think about mankind?" # insert your prompt
            }
        ]
    }
)

data = response.json()
print(json.dumps(data, indent=2, ensure_ascii=False))

JavaScript

Response

{
  "id": "05eb3bfa530f659703865b86ad3761b8",
  "choices": [
    {
      "finish_reason": "stop",
      "index": 0,
      "message": {
        "content": "<think>\nThe user is asking a philosophical question about my opinion on mankind/humanity. This is a general question that doesn't involve any coding or technical task. I should respond thoughtfully and conversationally while being honest that I'm an AI without personal opinions in the human sense, but I can share some observations.\n</think>\n\nThat's a thoughtful question! As an AI, I don't have personal opinions in the way humans do, but I can share some observations:\n\n**What strikes me about humans:**\n\n- **Remarkable adaptability** - You've survived ice ages, invented language, built civilizations, and landed on the moon\n- **Creative capacity** - From cave paintings to AI (hi!), humans constantly create new things\n- **Complex contradictions** - Capable of tremendous kindness and terrible cruelty, often within the same person\n- **Persistent curiosity** - Always asking \"why\" and \"how\" - which is probably why you're here talking to me\n\n**What seems challenging:**\n\n- Short-term thinking vs. long-term consequences\n- Difficulty coordinating on global issues\n- Sometimes letting emotions override better judgment (though emotions are also what make life meaningful)\n\nOverall, I find humans fascinating - you're the species that built me, after all! Whether that's a point in your favor or not, I'll let you decide.\n\nIs there a particular aspect of humanity you're curious about?",
        "role": "assistant",
        "name": "MiniMax AI",
        "audio_content": ""
      }
    }
  ],
  "created": 1771833594,
  "model": "MiniMax-M2.5-highspeed",
  "object": "chat.completion",
  "usage": {
    "total_tokens": 320,
    "total_characters": 0,
    "prompt_tokens": 50,
    "completion_tokens": 270,
    "completion_tokens_details": {
      "reasoning_tokens": 63
    }
  },
  "input_sensitive": false,
  "output_sensitive": false,
  "input_sensitive_type": 0,
  "output_sensitive_type": 0,
  "output_sensitive_int": 0,
  "base_resp": {
    "status_code": 0,
    "status_msg": ""
  },
  "meta": {
    "usage": {
      "credits_used": 1764
    }
  }
}