Responses API Compatibility

MiMo provides a calling interface compatible with the OpenAI Responses API format. This document covers request parameters, response schemas and code examples.

Compatibility Notes & Limitations:

This interface aligns with the OpenAI Responses API specification to facilitate quick integration for developers. Only the parameters documented here will be processed normally; undefined parameters will be filtered out and may cause request errors. See below for specific behavioral differences.

Incompatible parameters: Fields such as background, previous_response_id, and context_management are not currently supported. Carrying these parameters in a request will be ignored or trigger an error.
Reasoning level control: reasoning.effort controls model reasoning. none disables thinking; low / medium / high all enable reasoning with identical behavior — fine-grained reasoning intensity differentiation is not yet supported.

Request Address

https://api.xiaomimimo.com/v1/responses

Request Headers

The API supports the following two authentication methods. Please choose one and add it to the request headers:

Method 1: api-key field authentication, format:

api-key: $MIMO_API_KEY
Content-Type: application/json

Method 2: Authorization: Bearer authentication, format:

Authorization: Bearer $MIMO_API_KEY
Content-Type: application/json

Request Body

Response Object (non-streaming output)

Response chunk object (streaming output)

When you create a Response with stream set to true, the server will emit server-sent events to the client as the Response is generated.

response.created

An event that is emitted when a response is created.

response.in_progress

Emitted when the response is in progress.

response.completed

Emitted when the model response is complete.

response.incomplete

An event that is emitted when a response finishes as incomplete.

response.output_item.added

Emitted when a new output item is added.

response.output_item.done

Emitted when an output item is marked done.

response.content_part.added

Emitted when a new content part is added.

response.content_part.done

Emitted when a content part is done.

response.output_text.delta

Emitted when there is an additional text delta.

response.output_text.done

Emitted when text content is finalized.

response.function_call_arguments.delta

Emitted when there is a partial function-call arguments delta.

response.function_call_arguments.done

Emitted when function-call arguments are finalized.

response.reasoning_text.delta

Emitted when a delta is added to a reasoning text.

response.reasoning_text.done

Emitted when a reasoning text is completed.

curl --location --request POST 'https://api.xiaomimimo.com/v1/responses' \
--header "api-key: $MIMO_API_KEY" \
--header 'Content-Type: application/json' \
--data-raw '{
    "model": "mimo-v2.5-pro",
    "instructions": "You are MiMo, an AI assistant developed by Xiaomi. Today is date: Tuesday, December 16, 2025. Your knowledge cutoff date is December 2024.",
    "input": "please introduce yourself",
    "max_output_tokens": 1024,
    "stream": false,
    "reasoning": {
        "effort": "none"
    }
}'

response

{
    "id": "resp_5fcaac1af26a4b449f30e1eeeaa8c48f",
    "object": "response",
    "created_at": 1782215659,
    "status": "completed",
    "error": null,
    "incomplete_details": null,
    "model": "mimo-v2.5-pro",
    "metadata": null,
    "output": [
        {
            "id": "msg_1fa8f5011ebf47adb158ecf13c99d06c",
            "type": "message",
            "status": "completed",
            "role": "assistant",
            "content": [
                {
                    "type": "output_text",
                    "text": "Hello! I am MiMo, a large language model developed by Xiaomi's LLM Core Team. I'm here to help answer your questions, generate text, and assist with various tasks. How can I assist you today?",
                    "annotations": []
                }
            ]
        }
    ],
    "output_text": "Hello! I am MiMo, a large language model developed by Xiaomi's LLM Core Team. I'm here to help answer your questions, generate text, and assist with various tasks. How can I assist you today?",
    "usage": {
        "input_tokens": 57,
        "input_tokens_details": {},
        "output_tokens": 46,
        "output_tokens_details": {
            "reasoning_tokens": 0
        },
        "total_tokens": 103
    }
}

Update Time June 24, 2026

curl --location --request POST 'https://api.xiaomimimo.com/v1/responses' \
--header "api-key: $MIMO_API_KEY" \
--header 'Content-Type: application/json' \
--data-raw '{
    "model": "mimo-v2.5-pro",
    "instructions": "You are MiMo, an AI assistant developed by Xiaomi. Today is date: Tuesday, December 16, 2025. Your knowledge cutoff date is December 2024.",
    "input": "please introduce yourself",
    "max_output_tokens": 1024,
    "stream": false,
    "reasoning": {
        "effort": "none"
    }
}'

response

{
    "id": "resp_5fcaac1af26a4b449f30e1eeeaa8c48f",
    "object": "response",
    "created_at": 1782215659,
    "status": "completed",
    "error": null,
    "incomplete_details": null,
    "model": "mimo-v2.5-pro",
    "metadata": null,
    "output": [
        {
            "id": "msg_1fa8f5011ebf47adb158ecf13c99d06c",
            "type": "message",
            "status": "completed",
            "role": "assistant",
            "content": [
                {
                    "type": "output_text",
                    "text": "Hello! I am MiMo, a large language model developed by Xiaomi's LLM Core Team. I'm here to help answer your questions, generate text, and assist with various tasks. How can I assist you today?",
                    "annotations": []
                }
            ]
        }
    ],
    "output_text": "Hello! I am MiMo, a large language model developed by Xiaomi's LLM Core Team. I'm here to help answer your questions, generate text, and assist with various tasks. How can I assist you today?",
    "usage": {
        "input_tokens": 57,
        "input_tokens_details": {},
        "output_tokens": 46,
        "output_tokens_details": {
            "reasoning_tokens": 0
        },
        "total_tokens": 103
    }
}