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xiaomi/mimo-v2.5-pro

xiaomi/mimo-v2.5-pro

發布時間: 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.

定價

按用量付費

無需預付費用,僅按實際使用量付費

輸入
256K $1.00 / M Tokens
> 256K $2.00 / M Tokens
輸出
256K $3.00 / M Tokens
> 256K $6.00 / M Tokens
Cache Read
256K $0.20 / M Tokens
> 256K $0.40 / M Tokens

試用模型

xiaomi/mimo-v2.5-pro
線上
X
嗨!我是樂於助人的 AI 助理。有什麼可以幫你的嗎?
準備在本機編碼 Agent 中使用這個模型嗎?Agent 設定

API 使用

使用以下程式碼範例整合我們的 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

模型介紹

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

資訊

提供商xiaomi
類型llm

支援功能

輸入
文字
輸出
文字
上下文1,048,576
最大輸出16,384
視覺-
函式呼叫✓ 支援

API 存取指南

Base URLhttps://llm.wavespeed.ai/v1
API 端點chat/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.

輸入

$1 /M

輸出

$3 /M

上下文

1049K

最大輸出

16K

工具調用

支援

在 WaveSpeedAI 試用 Mimo V2.5 Pro

透過我們的統一 API 接入 Mimo V2.5 Pro — 相容 OpenAI、無冷啟動、透明計費。

關於 Mimo V2.5 Pro 的常見問題

Mimo V2.5 Pro API 多少錢?+

WaveSpeedAI 定價:輸入每百萬 token $1.00,輸出每百萬 token $3.00。Prompt 快取與批次處理分別計費,可顯著降低長上下文、高重複任務的實際成本。

Mimo V2.5 Pro 的上下文視窗有多大?+

Mimo V2.5 Pro 每次請求最多支援 1049K 上下文 token,輸出最多 16K token。

Mimo V2.5 Pro 是否相容 OpenAI?+

WaveSpeedAI 透過 https://llm.wavespeed.ai/v1 的 OpenAI 相容 Chat Completions 介面提供 Mimo V2.5 Pro。大多數 OpenAI SDK 用戶端只需更換 base URL 和 API Key;選用欄位取決於具體模型。

如何開始使用 Mimo V2.5 Pro?+

登入 WaveSpeedAI,在 Access Keys 中建立 API Key,然後使用上方顯示的 model id 向 https://llm.wavespeed.ai/v1/chat/completions 發送請求。模型可用性、能力和價格請以目前模型目錄為準。

相關 LLM API

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