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

Name: Mimo V2.5 Pro API
Brand: xiaomi
Price: 1 USD
Availability: InStock

Uso de API

Usa los siguientes ejemplos de código para integrar con nuestra API:

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["WAVESPEED_API_KEY"],
    base_url="https://llm.wavespeed.ai/v1",
    timeout=120.0,
    max_retries=2,
)

try:
    response = client.chat.completions.create(
        model="xiaomi/mimo-v2.5-pro",
        messages=[{"role": "user", "content": "Hello!"}],
    )
    print(response.choices[0].message.content or "")
except Exception as exc:
    raise SystemExit(f"LLM request failed: {exc}") from exc

Introducción del modelo

Xiaomi: MiMo-V2.5-Pro

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

Specification	Value
Provider	xiaomi
Model Type	Chat Completions model
Architecture	Sparse Mixture-of-Experts
Parameters	1.02T total / 42B active
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
Primary Use Cases	Agentic coding, complex software engineering, long-horizon tasks, tool use

Pricing

Token Type	Cost
Input	$1.00 per million tokens
Output	$3.00 per million tokens
Cached Input	$0.20 per million tokens

How to Use

Write your prompt - describe the task, provide context, and specify the desired output format.
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

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.

Preguntas frecuentes sobre Mimo V2.5 Pro

¿Cuánto cuesta Mimo V2.5 Pro a través de la API?+

Precios en WaveSpeedAI: $1.00 por millón de tokens de entrada y $3.00 por millón de tokens de salida. El prompt caching y el procesamiento por lotes se facturan por separado y reducen el coste efectivo en cargas largas y repetitivas.

¿Cuál es la ventana de contexto de Mimo V2.5 Pro?+

Mimo V2.5 Pro admite hasta 1049K tokens de contexto y hasta 16K tokens de salida por solicitud.

¿Es Mimo V2.5 Pro compatible con OpenAI?+

WaveSpeedAI ofrece Mimo V2.5 Pro en https://llm.wavespeed.ai/v1 mediante la interfaz Chat Completions compatible con OpenAI. En la mayoría de clientes del SDK de OpenAI basta con cambiar la URL base y la clave API; los campos opcionales dependen del modelo.

¿Cómo empiezo con Mimo V2.5 Pro?+

Inicia sesión en WaveSpeedAI, crea una clave API en Access Keys y envía una solicitud a https://llm.wavespeed.ai/v1/chat/completions con el id de modelo mostrado arriba. Consulta el catálogo actual para conocer disponibilidad, capacidades y precios.

Precios

Probar el modelo