TokenMix Team · 2026-03-17

TokenMix API Quickstart: 150+ Models in 5 Minutes (2026)

Getting Started with TokenMix API in 5 Minutes

TokenMix gives you access to all major AI models -- GPT-4o, Claude Sonnet 4, Gemini 2.0 Flash, DeepSeek R1, Llama 4, and more -- through a single OpenAI-compatible API. If you have used the OpenAI SDK before, you already know how to use TokenMix. If you have not, this guide will get you making API calls in under 5 minutes.

Step 1: Get Your API Key

  1. Sign up at tokenmix.ai
  2. Go to Dashboard > API Keys
  3. Click "Create New Key"
  4. Copy and save your key somewhere secure. You will not be able to see it again.

Step 2: Install the SDK

TokenMix is fully OpenAI-compatible, so you use the standard OpenAI SDK:

Python:

pip install openai

Node.js:

npm install openai

Step 3: Make Your First API Call

Python

import openai
import sys

client = openai.OpenAI(
    base_url="https://api.tokenmix.ai/v1",
    api_key="your-tokenmix-api-key"  # Replace with your actual key
)

try:
    response = client.chat.completions.create(
        model="gpt-4o",
        messages=[
            {"role": "system", "content": "You are a helpful assistant."},
            {"role": "user", "content": "Explain what an API gateway is in two sentences."}
        ],
        max_tokens=200,
        temperature=0.7
    )
    print(response.choices[0].message.content)

except openai.AuthenticationError:
    print("Invalid API key. Check your key at tokenmix.ai/dashboard/keys")
    sys.exit(1)
except openai.RateLimitError:
    print("Rate limit reached. Wait a moment and try again.")
    sys.exit(1)
except openai.APIError as e:
    print(f"API error: {e.message}")
    sys.exit(1)

Node.js

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://api.tokenmix.ai/v1",
  apiKey: "your-tokenmix-api-key", // Replace with your actual key
});

async function main() {
  try {
    const response = await client.chat.completions.create({
      model: "gpt-4o",
      messages: [
        { role: "system", content: "You are a helpful assistant." },
        { role: "user", content: "Explain what an API gateway is in two sentences." },
      ],
      max_tokens: 200,
      temperature: 0.7,
    });

    console.log(response.choices[0].message.content);
  } catch (error) {
    if (error instanceof OpenAI.AuthenticationError) {
      console.error("Invalid API key. Check your key at tokenmix.ai/dashboard/keys");
    } else if (error instanceof OpenAI.RateLimitError) {
      console.error("Rate limit reached. Wait a moment and try again.");
    } else {
      console.error("API error:", error.message);
    }
    process.exit(1);
  }
}

main();

cURL

curl https://api.tokenmix.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer your-tokenmix-api-key" \
  -d '{
    "model": "gpt-4o",
    "messages": [
      {"role": "system", "content": "You are a helpful assistant."},
      {"role": "user", "content": "Explain what an API gateway is in two sentences."}
    ],
    "max_tokens": 200
  }'

Step 4: Streaming Responses

For chat applications or any UI that shows text as it is generated, use streaming:

Python Streaming

import openai

client = openai.OpenAI(
    base_url="https://api.tokenmix.ai/v1",
    api_key="your-tokenmix-api-key"
)

try:
    stream = client.chat.completions.create(
        model="claude-sonnet-4",
        messages=[
            {"role": "user", "content": "Write a short guide on Python type hints."}
        ],
        stream=True
    )

    for chunk in stream:
        if chunk.choices[0].delta.content is not None:
            print(chunk.choices[0].delta.content, end="", flush=True)

    print()  # Final newline

except openai.APIError as e:
    print(f"\nStream error: {e.message}")

Node.js Streaming

import OpenAI from "openai";

const client = new OpenAI({
  baseURL: "https://api.tokenmix.ai/v1",
  apiKey: "your-tokenmix-api-key",
});

async function main() {
  const stream = await client.chat.completions.create({
    model: "claude-sonnet-4",
    messages: [
      { role: "user", content: "Write a short guide on Python type hints." },
    ],
    stream: true,
  });

  for await (const chunk of stream) {
    const content = chunk.choices[0]?.delta?.content;
    if (content) {
      process.stdout.write(content);
    }
  }
  console.log();
}

main().catch(console.error);

Step 5: Switch Between Models

The best part of using TokenMix: switching models is a one-line change. Every model uses the same endpoint, same SDK, same API key:

# Just change the model parameter
response = client.chat.completions.create(
    model="claude-sonnet-4",  # Or: gpt-4o, gemini-2.0-flash, deepseek-r1, llama-4
    messages=[{"role": "user", "content": "Hello!"}]
)

No new SDK, no new API key, no new billing account. This makes it trivial to benchmark models against each other on your own data.

Common Patterns

Setting a Timeout

client = openai.OpenAI(
    base_url="https://api.tokenmix.ai/v1",
    api_key="your-tokenmix-api-key",
    timeout=30.0  # 30 second timeout
)

Retry with Exponential Backoff

import time
import openai

def call_with_retry(client, max_retries=3, **kwargs):
    for attempt in range(max_retries):
        try:
            return client.chat.completions.create(**kwargs)
        except openai.RateLimitError:
            if attempt == max_retries - 1:
                raise
            wait = 2 ** attempt  # 1s, 2s, 4s
            time.sleep(wait)
        except openai.APIError:
            if attempt == max_retries - 1:
                raise
            time.sleep(1)

Using Environment Variables (Recommended)

import os
import openai

client = openai.OpenAI(
    base_url="https://api.tokenmix.ai/v1",
    api_key=os.environ["TOKENMIX_API_KEY"]  # Set in your environment
)

# In your .env or shell profile
export TOKENMIX_API_KEY=sk-your-key-here

Next Steps

You now have everything you need to start building with any major AI model through a single API. The entire setup -- from sign-up to working code -- should take less than 5 minutes.