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Model Choice

ToothFairyAI provides a comprehensive selection of AI models optimised for different use cases and complexity levels. Each model is designed to excel in specific scenarios, from lightweight assistant tasks to complex reasoning and code generation.

Understanding Model Categories

Our models are organised into three main categories based on computational power and capabilities:

  • Large Models: High-performance models for complex reasoning, advanced coding, and demanding tasks
  • Medium Models: Balanced performance models suitable for most business applications
  • Small Models: Efficient models optimised for speed and cost-effectiveness

Model Selection by Use Case

Code Generation & Reasoning

For Complex Development Tasks:

  • Deepseek R1 05/28 (Large) - Advanced reasoning capabilities for complex problem-solving
  • Deepseek V3 03-24 (Large) - High-performance code generation and architectural design

For Standard Development:

  • Qwen2.5-32B-Coder (Medium) - Reliable code generation with good performance balance

Code Completion & Bug Fixing

For Production Code:

  • Qwen2.5-32B-Coder (Medium) - Excellent at understanding context and fixing issues

General Reasoning & Planning

For Smart Assistant Applications:

  • Sorcerer 1.5 Thinking (Medium) - Optimised for low-medium effort reasoning tasks with enhanced thinking capabilities
  • DeepSeek R1 05/28 (Large) - Superior analytical thinking for complex planning
  • Deepseek V3 03-24 (Large) - Advanced strategic planning and decision-making

For Business Applications:

  • Qwen2.5-72B-Instruct (Medium) - Strong reasoning for business logic
  • Llama 3.3 70B (Medium) - Reliable planning and analysis capabilities

Function Calling & Tool Use

For Agentic Workflows:

  • Mystica (Medium) - Specialised for low thinking agentic tasks with excellent tool integration
  • Mystica 1.5 Thinking (Medium) - Enhanced reasoning for the hardest agentic problems
  • Qwen3 235B A22B (Large) - Maximum capability for complex tool orchestration

For Standard Integration:

  • Qwen 3 Family Models (Large/Medium/Small) - Consistent function calling across different scales

Long Context & Summarization

For Document Processing:

  • Llama 4 Maverick (Large) - Exceptional long-context understanding for comprehensive analysis

For Standard Tasks:

  • Llama 4 Scout (Medium) - Efficient summarisation with good context retention

Vision & Document Understanding

For Advanced Visual Tasks:

  • Llama 4 Maverick (Large) - Superior image analysis and document comprehension

For Standard Visual Processing:

  • Qwen2.5-VL 32B Instruct (Medium) - Reliable visual understanding
  • Qwen2.5-VL 72B Instruct (Medium) - Enhanced visual reasoning
  • Llama 4 Scout (Medium) - Balanced visual processing capabilities

For Quick Visual Tasks:

  • Qwen2.5-VL 3-7B (Small) - Fast image processing with reduced computational requirements

Low-Latency NLU & Extraction

For Real-Time Applications:

  • Llama 3.1 8B (Small) - Ultra-fast natural language understanding
  • Llama 3.2 3B (Small) - Efficient entity extraction
  • Llama 3.2 1B (Small) - Minimal latency for simple extraction tasks
  • Qwen3 8B (Small) - Quick processing with good accuracy

Model Recommendations by Agent Type

Assistant Agents

Recommended Models:

  • Sorcerer 1.5 Thinking (Medium) - Ideal for everyday smart assistance with enhanced reasoning
  • Mystica (Medium) - Excellent for general-purpose interactions requiring minimal thinking overhead

Operator Agents

Recommended Models:

  • Mystica 1.5 Thinking (Medium) - Perfect for complex retrieval and analysis tasks
  • Llama 4 Maverick (Large) - Superior for document-heavy knowledge work
  • DeepSeek R1 05/28 (Large) - Excellent analytical reasoning for research tasks

Programmer Agents

Recommended Models:

  • Deepseek R1 05/28 (Large) - Advanced code reasoning and architecture
  • Qwen2.5-32B-Coder (Medium) - Balanced performance for most coding tasks
  • Qwen3 14B (Small) - Quick coding assistance and simple tasks

Orchestrator Agents

Recommended Models:

  • Mystica 1.5 Thinking (Medium) - Optimal for complex multi-step task planning
  • Qwen3 235B A22B (Large) - Maximum capability for intricate workflow orchestration
  • DeepSeek R1 05/28 (Large) - Superior reasoning for task breakdown and delegation

Performance Considerations

When selecting a model, consider these factors:

  1. Task Complexity: Match model size to task requirements
  2. Response Speed: Smaller models provide faster responses
  3. Cost Efficiency: Balance performance needs with resource usage
  4. Use Case Specificity: Choose models optimised for your primary use case

Best Practices

  1. Start Medium: Begin with medium-sized models for most applications
  2. Scale as Needed: Upgrade to larger models when complexity demands it
  3. Test Performance: Evaluate different models with your specific use cases
  4. Monitor Usage: Track model performance and adjust selections accordingly
  5. Consider Context: Factor in the agent type and intended workflow when choosing

Special Model Features

Sorcerer Series

  • Enhanced Thinking: Built-in reasoning capabilities for better decision-making
  • Efficiency Focus: Optimised for common assistant use cases
  • Balanced Performance: Good reasoning with reasonable computational requirements

Mystica Series

  • Agentic Optimisation: Designed specifically for multi-agent workflows
  • Tool Integration: Superior function calling and API interaction capabilities
  • Thinking Variants: Available with enhanced reasoning for complex scenarios

Deepseek Series

  • Code Excellence: Industry-leading code generation and understanding
  • Advanced Reasoning: Superior analytical thinking for complex problems
  • Latest Architecture: Cutting-edge model design for optimal performance

By selecting the appropriate model for your specific needs, you can optimise both performance and efficiency in your ToothFairyAI agent implementations.