Alfred Models
A guide to AI models on Alfred and how each change Alfred's behaviour
Understanding Alfred's AI Models
Alfred leverages advanced AI models from OpenAI, Anthropic and Google, each carefully selected to provide optimal performance for different use cases. Below is a detailed breakdown of each model's capabilities and ideal use scenarios.
Summary
OpenAI
GPT-4: High Intelligence, Medium Costs
GPT-4-MINI: Low Intelligence, Low Costs
Anthropic
Claude-Sonnet: Very High Intelligence, High Costs
Claude-Haiku: Medium Intelligence, Somewhat Low Costs
Google
Gemini-Pro: High Intelligence, Medium-High Costs
Gemini-Flash: Somewhat Low Intelligence, Low Costs
Our recommendation:
Claude-Sonnet for high intelligence tasks (most intelligent model)
Gemini-Pro for higher-medium intelligence tasks
Claude-Haiku for medium intelligence tasks (perfect middleground)
GPT-4 for general and balanced performance
Gemini-Flash for low-cost, high-volume tasks (cheapest model)
Note: a cheaper model means that you can use more of that model before running out of daily/weekly usage for that model
Model Overview
OpenAI Models
GPT-4 (GPT-4.1)
Strong Suits:
Comprehensive multimodal processing
Superior performance in non-English languages
Best For:
Multilingual interactions
Professional applications
Mid-volume interactions
GPT-4-MINI (GPT-4.1-mini)
Strong Suits:
Optimized for speed and efficiency
Cost-efficient operations
Best For:
Quick responses
Routine tasks with low analytical requirements
High-volume interactions
NOTE: Gemini-Flash is more intelligent, faster and lower cost than GPT-4-MINI
Anthropic Models
Claude-Sonnet (Claude 3.7 Sonnet)
Strong Suits:
Advanced coding capabilities
Persistent problem solving
Enhanced reasoning and analysis
Best For:
Programming tasks
Technical queries with high analytical requirements
Highly Intelligent interactions
Claude-Haiku (Claude 3.5 Haiku)
Strong Suits:
Optimized for speed and efficiency
Somewhat Cost-efficient operations
Best For:
Quick responses
Routine tasks with medium analytical requirements
High-volume interactions
Google Gemini Models
Gemini-Pro (Gemini 2.5 Pro)
Strong Suits:
Effecient input processing (good for processing large inputs)
Good cost to performance ratio
Best For:
Complex analytical tasks
Intelligent interactions at a reasonable cost
Gemini-Flash (Gemini 2.0 Flash)
Strong Suits:
Optimized for speed and efficiency with good intelligence
Lazy model, will not over do tasks
Cost-efficient operations
Best For:
Quick responses
Routine tasks with low analytical requirements
High-volume interactions
Choosing Your Model
For maximum capabilities: Claude-Sonnet
For advanced reasoning and thinking: Gemini-Pro
For smart, low-cost, speed-critical tasks: Claude-Haiku
For balanced performance and cost: GPT-4
For extreme-low-cost, speed-critical tasks: Gemini-Flash
Our Recommendation
During our own internal testing, we've found that Claude-Sonnet consitently outperforms other models in terms of accuracy, intelligence and our most important metric - engagement. However, for cost-sensitive applications, GPT-4, Gemini-Pro and Claude-Haiku are a great alternatives. Finally, for high-volume and surface-level operations, Gemini-Flash is the optimal model.
Performance Matrix
Aspect | GPT-4 | GPT-4-MINI | Claude-Sonnet | Claude-Haiku | Gemini-Pro | Gemini-Flash |
---|---|---|---|---|---|---|
Speed | ||||||
Accuracy | ||||||
Features | ||||||
Cost-Efficiency |
Based on internal testing and experiences