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
- Use appropriate models: Choose the right model for your task
- Optimize prompts: Shorter, clearer prompts use fewer tokens
- Manage context: Remove unnecessary conversation history
- 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