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xiaomi/mimo-v2.5-pro

xiaomi/mimo-v2.5-pro

Data de lançamento: 2026-04-23

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.

Preços

Pagamento por uso

Sem custo inicial, pague apenas pelo que usar

Entrada
256K $1.00 / M Tokens
> 256K $2.00 / M Tokens
Saída
256K $3.00 / M Tokens
> 256K $6.00 / M Tokens
Cache Read
256K $0.20 / M Tokens
> 256K $0.40 / M Tokens

Experimentar o modelo

xiaomi/mimo-v2.5-pro
Online
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Olá! Sou um assistente de IA útil. Em que posso ajudar?
Pronto para usar este modelo em um coding agent local?Setup do agente

Uso da API

Use os exemplos de código abaixo para integrar com nossa API:

import OpenAI from 'openai';

if (!process.env.WAVESPEED_API_KEY) throw new Error('Set WAVESPEED_API_KEY');
const client = new OpenAI({
  apiKey: process.env.WAVESPEED_API_KEY,
  baseURL: 'https://llm.wavespeed.ai/v1',
  timeout: 120_000,
  maxRetries: 2,
});

try {
  const response = await client.chat.completions.create({
    model: 'xiaomi/mimo-v2.5-pro',
    messages: [{ role: 'user', content: 'Hello!' }],
  });
  console.log(response.choices[0]?.message?.content ?? '');
} catch (error) {
  console.error('LLM request failed:', error);
  process.exitCode = 1;
}

Introdução do modelo

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

Provedorxiaomi
Tipollm

Funcionalidades suportadas

Entrada
Texto
Saída
Texto
Contexto1,048,576
Saída máx.16,384
Vision-
Function Calling✓ Suportado

Guia de acesso à API

Base URLhttps://llm.wavespeed.ai/v1
API Endpointchat/completions
ID do modeloxiaomi/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.

Entrada

$1 /M

Saída

$3 /M

Contexto

1049K

Saída máx.

16K

Uso de ferramentas

Suportado

Experimente Mimo V2.5 Pro no WaveSpeedAI

Acesse Mimo V2.5 Pro através da nossa API unificada — compatível com OpenAI, sem inicializações a frio, preços transparentes.

Perguntas frequentes sobre Mimo V2.5 Pro

Quanto custa Mimo V2.5 Pro via API?+

Preços no WaveSpeedAI: $1.00 por milhão de tokens de entrada e $3.00 por milhão de tokens de saída. Prompt caching e batch processing são cobrados separadamente e reduzem o custo efetivo em cargas longas e repetitivas.

Qual é a janela de contexto do Mimo V2.5 Pro?+

Mimo V2.5 Pro suporta até 1049K tokens de contexto e até 16K tokens de saída por requisição.

Mimo V2.5 Pro é compatível com OpenAI?+

O WaveSpeedAI disponibiliza Mimo V2.5 Pro em https://llm.wavespeed.ai/v1 pela interface Chat Completions compatível com OpenAI. Na maioria dos clientes OpenAI SDK, basta alterar a base URL e a chave API; campos opcionais dependem do modelo.

Como começo a usar o Mimo V2.5 Pro?+

Entre no WaveSpeedAI, crie uma chave API em Access Keys e envie uma requisição para https://llm.wavespeed.ai/v1/chat/completions com o model id mostrado acima. Consulte o catálogo atual para disponibilidade, recursos e preços.

APIs LLM relacionadas

MiMo-V2.5-Pro | Xiaomi LLM API Pricing & Performance | WaveSpeedAI