How to Add Multi-Model AI to Your App in 5 Minutes (OpenAI-Compatible)

Want to support DeepSeek, Kimi and Qwen in your app — without managing multiple API integrations?

Here's the fastest way.

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Step 1: Get an AIBridge API Key

Sign up at aibridge-api.com — you'll get 5M free tokens instantly (no credit card).

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Step 2: Swap Your Base URL

from openai import OpenAI

# Before (single provider)
client = OpenAI(api_key="sk-...")

# After (14+ models, one endpoint)
client = OpenAI(
    api_key="mb_your_key",
    base_url="https://aibridge-api.com/v1"
)

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Step 3: Use Any Model

# DeepSeek V4 Pro for reasoning
response = client.chat.completions.create(
    model="deepseek-v4-pro",
    messages=[{"role": "user", "content": "Explain quantum computing"}]
)

# Qwen3 for multilingual tasks
response = client.chat.completions.create(
    model="qwen3-235b-a22b",
    messages=[{"role": "user", "content": "写一个Python排序函数"}]
)

# GLM-4 for complex tasks
response = client.chat.completions.create(
    model="glm-4-plus",
    messages=[{"role": "user", "content": "Analyze this data..."}]
)

Supported Models
DeepSeek (5 models): deepseek-chat, deepseek-reasoner, deepseek-coder, deepseek-v4-pro, deepseek-v4-flash

Qwen (3 models): qwen-max, qwen-plus, qwen3-235b-a22b

GLM (3 models): glm-4-plus, glm-4-air, glm-4-flash

Moonshot (3 models): moonshot-v1-8k, moonshot-v1-32k, moonshot-v1-128k

That's It
✅ Same code, different models
✅ Zero migrations
✅ 90% cost savings vs direct API
✅ Built-in usage analytics

Try it: https://aibridge-api.com

Happy building! 🚀