> ## Documentation Index
> Fetch the complete documentation index at: https://docs.mixus.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Tokens & Billing Overview

> Understanding token usage and billing in mixus

Understanding how tokens work and how billing is calculated in mixus.

## What Are Tokens?

Tokens are the fundamental unit of measurement for AI model usage in mixus. Every interaction with an AI model consumes tokens based on:

* **Input tokens**: The text you send to the model
* **Output tokens**: The response generated by the model
* **Processing complexity**: Some operations require additional computational resources

## Key Concepts

### Token Counting

* Tokens are roughly equivalent to words, but vary by language and model
* English text averages \~1.3 tokens per word
* Code and structured data may have different token ratios
* Each model has its own tokenization method

### Billing Structure

mixus uses a transparent, usage-based billing model:

* **Pay-per-token**: Only pay for what you use
* **No hidden fees**: Clear pricing for all features
* **Monthly billing**: Consolidated invoices
* **Usage tracking**: Real-time monitoring

## Token Types

### Input Tokens

Tokens from your prompts, uploaded files, and context:

* Chat messages
* File content
* System prompts
* Memory context

### Output Tokens

Tokens generated by the AI model:

* Chat responses
* Generated code
* Analysis results
* Tool outputs

### Processing Tokens

Additional tokens for special operations:

* Web search queries
* Document analysis
* Image processing
* Agent execution

## Pricing Tiers

### Free Tier

* 1,000 tokens per month
* Access to basic models
* Standard support

### Pro Tier

* \$20/month base
* 100,000 included tokens
* Premium model access
* Priority support

### Team Tier

* \$50/month base
* 500,000 included tokens
* Advanced collaboration features
* Team management tools

### Enterprise

* Custom pricing
* Unlimited tokens
* Dedicated support
* Custom integrations

## Cost Optimization

### Best Practices

1. **Use appropriate models**: Choose the right model for your task
2. **Optimize prompts**: Shorter, clearer prompts use fewer tokens
3. **Manage context**: Remove unnecessary conversation history
4. **Batch operations**: Group similar tasks together

### Model Efficiency

* **GPT-4o mini**: Most cost-effective for simple tasks
* **GPT-4o**: Best balance of capability and cost
* **Claude 3.5 Sonnet**: Excellent for analysis and reasoning
* **o1-preview**: Use for complex problem-solving only

## Next Steps

* [Learn how tokens work](/tokens/how-it-works)
* [Track your usage](/tokens/tracking)
* [Understand billing](/tokens/billing)

## Related Resources

* [Model Limits](/ai-models/limits)
* [Rate Limits](/limits/rate-limits)
* [Usage Tracking](/tokens/tracking)