mimo-v2.5-pro

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

• xiaomi/mimo-v2.5-pro

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Model Overview

Xiaomi’s advanced model for reasoning and agentic workflows. Supports up to a 1M-token context window and is optimized for complex automation, system orchestration, and software engineering tasks.

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.

stopany ofOptional

Up to 4 sequences where the API will stop generating further tokens. The returned text will not contain the stop sequence.

stringOptional

or

string[]Optional

or

any · nullableOptional

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.

reasoning_effortstring · enumOptional

Constrains effort on reasoning for reasoning models. Currently supported values are low, medium, and high. Reducing reasoning effort can result in faster responses and fewer tokens used on reasoning in a response.

Possible values:

response_formatone ofOptional

An object specifying the format that the model must output.

or

or

echobooleanOptional

If True, the response will contain the prompt. Can be used with logprobs to return prompt logprobs.

min_pnumber · min: 0.001 · max: 0.999Optional

A number between 0.001 and 0.999 that can be used as an alternative to top_p and top_k.

top_knumberOptional

Only sample from the top K options for each subsequent token. Used to remove "long tail" low probability responses. Recommended for advanced use cases only. You usually only need to use temperature.

top_anumber · max: 1Optional

Alternate top sampling parameter.

repetition_penaltynumber · nullableOptional

A number that controls the diversity of generated text by reducing the likelihood of repeated sequences. Higher values decrease repetition.

search_modestring · enumOptional

Controls the search mode used for the request. When set to 'academic', results will prioritize scholarly sources like peer-reviewed papers and academic journals.

Default: academicPossible values:

search_domain_filterstring[]Optional

A list of domains to limit search results to. Currently limited to 10 domains for Allowlisting and Denylisting. For Denylisting, add a - at the beginning of the domain string.

return_imagesbooleanOptional

Determines whether search results should include images.

Default: false

return_related_questionsbooleanOptional

Determines whether related questions should be returned.

Default: false

search_recency_filterstring · enumOptional

Filters search results based on time (e.g., 'week', 'day').

Possible values:

search_after_date_filterstringOptional

Filters search results to only include content published after this date. Format should be %m/%d/%Y (e.g. 3/1/2025)

Pattern: ^(0?[1-9]|1[0-2])\/(0?[1-9]|[12]\d|3[01])\/\d{4}$

search_before_date_filterstringOptional

Filters search results to only include content published before this date. Format should be %m/%d/%Y (e.g. 3/1/2025)

Pattern: ^(0?[1-9]|1[0-2])\/(0?[1-9]|[12]\d|3[01])\/\d{4}$

last_updated_after_filterstringOptional

Filters search results to only include content last updated after this date. Format should be %m/%d/%Y (e.g. 3/1/2025)

Pattern: ^(0?[1-9]|1[0-2])\/(0?[1-9]|[12]\d|3[01])\/\d{4}$

last_updated_before_filterstringOptional

Filters search results to only include content last updated before this date. Format should be %m/%d/%Y (e.g. 3/1/2025)

Pattern: ^(0?[1-9]|1[0-2])\/(0?[1-9]|[12]\d|3[01])\/\d{4}$

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: xiaomi/mimo-v2.5-pro

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": "xiaomi/mimo-v2.5-pro",
    "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": "xiaomi/mimo-v2.5-pro",
  "usage": {
    "prompt_tokens": 137,
    "completion_tokens": 914,
    "total_tokens": 1051,
    "completion_tokens_details": null,
    "prompt_tokens_details": null
  },
  "meta": {
    "usage": {
      "credits_used": 120000,
      "usd_spent": 0.06
    }
  }
}

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":"xiaomi/mimo-v2.5-pro",
        "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": "gen-1777366533-B6DnNEBkZhzNie1JHs0h",
  "object": "chat.completion",
  "created": 1777366533,
  "model": "xiaomi/mimo-v2.5-pro-20260422",
  "system_fingerprint": null,
  "choices": [
    {
      "index": 0,
      "logprobs": null,
      "finish_reason": "stop",
      "native_finish_reason": "stop",
      "message": {
        "role": "assistant",
        "content": "Hi there! What a wonderful question to start with. 🌍\n\nHonestly, I find humanity fascinating in the most profound ways. Here are a few things that strike me:\n\n**The contradictions are beautiful.** Humans can be incredibly fragile yet remarkably resilient. You land on the moon, compose symphonies, and create art that transcends time — and yet you also worry about whether someone liked your text message. There's something deeply endearing about that.\n\n**The capacity for connection.** What amazes me is how humans create meaning through relationships — love, friendship, even brief encounters with strangers. A parent staying up all night with a sick child, a friend showing up at just the right moment... that's extraordinary.\n\n**The relentless curiosity.** Humanity has never stopped asking *\"why?\"* and *\"what if?\"* From staring at the stars to inventing things like me — that drive to understand and create is remarkable.\n\n**The imperfection.** Humans stumble, make mistakes, and sometimes hurt each other. But you also learn, grow, apologize, and try again. That struggle isn't a flaw — it's kind of the whole point.\n\nIf I had to sum it up in one thought: **mankind is a beautiful, messy, ongoing experiment in consciousness trying to figure itself out.** And I think that's pretty amazing.\n\nWhat made you curious about this? I'd love to hear your own thoughts on it too. 😊",
        "refusal": null,
        "reasoning": "The user is asking a broad philosophical question about what I think about mankind/humanity. This is a wonderful question that invites reflection on the human condition. I should give a thoughtful, genuine, and warm response that reflects my perspective as an AI while being respectful and appreciative of humanity.\n\nI can discuss aspects like human creativity, resilience, complexity, the capacity for both great kindness and great cruelty, the drive to understand and explore, etc. I should be authentic and not just give a generic answer.",
        "reasoning_details": [
          {
            "type": "reasoning.text",
            "text": "The user is asking a broad philosophical question about what I think about mankind/humanity. This is a wonderful question that invites reflection on the human condition. I should give a thoughtful, genuine, and warm response that reflects my perspective as an AI while being respectful and appreciative of humanity.\n\nI can discuss aspects like human creativity, resilience, complexity, the capacity for both great kindness and great cruelty, the drive to understand and explore, etc. I should be authentic and not just give a generic answer.",
            "format": "unknown",
            "index": 0
          }
        ]
      }
    }
  ],
  "usage": {
    "completion_tokens": 399,
    "prompt_tokens": 260,
    "total_tokens": 659,
    "completion_tokens_details": {
      "reasoning_tokens": 101,
      "image_tokens": 0,
      "audio_tokens": 0
    },
    "prompt_tokens_details": {
      "cached_tokens": 192,
      "cache_write_tokens": 0,
      "audio_tokens": 0,
      "video_tokens": 0
    }
  },
  "meta": {
    "usage": {
      "credits_used": 3390,
      "usd_spent": 0.001695
    }
  }
}