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xiaomi/mimo-v2.5-pro

xiaomi/mimo-v2.5-pro

1,048,576 context · $1.00/M input tokens · $3.00/M output tokens

MiMo-V2.5-Pro is Xiaomi’s flagship open model for advanced agentic workflows, complex software engineering, and long-horizon task execution. Built on a sparse Mixture-of-Experts architecture with 1.02T total parameters and 42B active parameters, it supports a 1M-token context window and is optimized for autonomous coding agents, large codebase reasoning, tool-use workflows, and multi-step problem solving. It delivers strong performance on agentic and software engineering benchmarks such as ClawEval, GDPVal, and SWE-bench Pro, with an emphasis on token-efficient long-context execution.

Pricing

Pay-per-use

No upfront costs, pay only for what you use

Input
256K $1.00 / M Tokens
> 256K $2.00 / M Tokens
Output
256K $3.00 / M Tokens
> 256K $6.00 / M Tokens
Cache Read
256K $0.20 / M Tokens
> 256K $0.40 / M Tokens

Try the model

xiaomi/mimo-v2.5-pro
Online
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Hi! I am a helpful AI assistant. What can I do for you?

API Usage

Use the following code examples to integrate with our API:

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://llm.wavespeed.ai/v1"
)

response = client.chat.completions.create(
    model="xiaomi/mimo-v2.5-pro",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

print(response.choices[0].message.content)

Model Introduction

Xiaomi: MiMo-V2.5-Pro

MiMo-V2.5-Pro is Xiaomi’s flagship open model for advanced agentic workflows, complex software engineering, and long-horizon task execution. Built on a sparse Mixture-of-Experts architecture with 1.02T total parameters and 42B active parameters, it is optimized for autonomous coding agents, large codebase reasoning, tool use, and multi-step problem solving.


Why It Looks Great

  • Flagship Xiaomi MiMo model for complex agentic and software engineering workloads
  • Sparse Mixture-of-Experts architecture with 1.02T total parameters and 42B active parameters
  • 1M-token context window for long prompts, large codebases, documents, and multi-turn workflows
  • Strong fit for autonomous coding agents, long-horizon task execution, and tool-heavy workflows
  • Competitive performance on benchmarks such as ClawEval, GDPVal, and SWE-bench Pro
  • Designed for token-efficient agent trajectories and extended multi-step execution
  • Function calling and tool-use support for agentic application workflows
  • Structured output support for JSON responses and schema-constrained generation
  • Reasoning controls for tuning latency, quality, and cost per request

Key Features

  • Architecture: Sparse Mixture-of-Experts
  • Total Parameters: 1.02T
  • Active Parameters: 42B
  • Context Window: 1,048,576 tokens
  • Max Input: 1,032,192 tokens
  • Max Output: 16,384 tokens
  • Input: Text
  • Output: Text
  • Vision: Not listed
  • Function Calling: Supported
  • Structured Outputs: Supported
  • Thinking Mode: Supported
  • Image Generation: Not listed
  • Audio Input: Not listed
  • Supported Parameters: frequency_penalty, include_reasoning, logit_bias, max_tokens, min_p, presence_penalty, reasoning, repetition_penalty, response_format, seed, stop, structured_outputs, temperature, tool_choice, tools, top_k, top_p

Specifications

SpecificationValue
Providerxiaomi
Model TypeChat Completions model
ArchitectureSparse Mixture-of-Experts
Parameters1.02T total / 42B active
Context Window1,048,576 tokens
Max Input1,032,192 tokens
Max Output16,384 tokens
InputText
OutputText
VisionNot listed
Function CallingSupported
Structured OutputsSupported
Primary Use CasesAgentic coding, complex software engineering, long-horizon tasks, tool use

Pricing

Token TypeCost
Input$1.00 per million tokens
Output$3.00 per million tokens
Cached Input$0.20 per million tokens

How to Use

  1. Write your prompt - describe the task, provide context, and specify the desired output format.
  2. Submit - the model processes your request and returns the response.

API Integration

Base URL: https://llm.wavespeed.ai/v1
API Endpoint: chat/completions
Model ID: xiaomi/mimo-v2.5-pro


API Usage

Python SDK

from openai import OpenAI

client = OpenAI(
    api_key="YOUR_API_KEY",
    base_url="https://llm.wavespeed.ai/v1"
)

response = client.chat.completions.create(
    model="xiaomi/mimo-v2.5-pro",
    messages=[{"role": "user", "content": "Hello!"}]
)

print(response.choices[0].message.content)

cURL

curl https://llm.wavespeed.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "xiaomi/mimo-v2.5-pro",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Notes

  • Model: xiaomi/mimo-v2.5-pro
  • Provider: xiaomi
  • Best suited for autonomous coding, complex software engineering, long-horizon reasoning, tool-heavy agent workflows, and large-context text tasks

Info

Providerxiaomi
Typellm

Supported Functionality

Input
Text
Output
Text
Context1,048,576
Max Output16,384
Vision-
Function Calling✓ Supported

API Access Guide

Base URLhttps://llm.wavespeed.ai/v1
API Endpointchat/completions
Model IDxiaomi/mimo-v2.5-pro

Mimo V2.5 Pro API

xiaomi/mimo-v2.5-pro

MiMo-V2.5-Pro is Xiaomi’s flagship open model for advanced agentic workflows, complex software engineering, and long-horizon task execution. Built on a sparse Mixture-of-Experts architecture with 1.02T total parameters and 42B active parameters, it supports a 1M-token context window and is optimized for autonomous coding agents, large codebase reasoning, tool-use workflows, and multi-step problem solving. It delivers strong performance on agentic and software engineering benchmarks such as ClawEval, GDPVal, and SWE-bench Pro, with an emphasis on token-efficient long-context execution.

Input

$1 /M

Output

$3 /M

Context

1049K

Max Output

16K

Tool Use

Supported

Try Mimo V2.5 Pro on WaveSpeedAI

Access Mimo V2.5 Pro through our unified API — OpenAI-compatible, no cold starts, transparent pricing.

Frequently Asked Questions about Mimo V2.5 Pro

How much does Mimo V2.5 Pro cost via the API?+

Pricing on WaveSpeedAI: $1.00 per million input tokens and $3.00 per million output tokens. Prompt caching and batch processing are billed separately and reduce effective cost on long, repetitive workloads.

What is the context window of Mimo V2.5 Pro?+

Mimo V2.5 Pro supports up to 1049K tokens of context with up to 16K tokens of output per request.

Is Mimo V2.5 Pro OpenAI-compatible?+

Yes. WaveSpeedAI exposes Mimo V2.5 Pro through an OpenAI-compatible endpoint at https://llm.wavespeed.ai/v1. Point the official OpenAI SDK at this base URL with your WaveSpeedAI API key — no other code changes required.

How do I get started with Mimo V2.5 Pro?+

Sign in to WaveSpeedAI, create an API key in Access Keys, then send a request to https://llm.wavespeed.ai/v1/chat/completions with model id set to the value shown above. New accounts receive free credits to evaluate Mimo V2.5 Pro before paying per token.

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