GPT-5 Series Complete Guide: 5.2, 5.1, 5, mini, and nano
Comprehensive guide to OpenAI's GPT-5 model family. Compare capabilities, pricing, and use cases for all GPT-5 variants.
GPT-5 Series Complete Guide: 5.2, 5.1, 5, mini, and nano
OpenAI's GPT-5 series represents a major leap forward in AI capabilities. This comprehensive guide covers all five models in the GPT-5 family, helping you choose the right one for your needs.
GPT-5 Model Lineup Overview
| Model | Input Cost | Output Cost | Context | Best For |
|---|---|---|---|---|
| GPT-5.2 | $1.75 | $14.00 | 200K | Flagship performance |
| GPT-5.1 | $1.25 | $10.00 | 200K | Balanced premium |
| GPT-5 | $1.25 | $10.00 | 200K | General flagship |
| GPT-5 mini | $0.25 | $2.00 | 128K | High-volume tasks |
| GPT-5 nano | $0.05 | $0.40 | 64K | Ultra-efficient |
GPT-5.2: The Flagship Model
GPT-5.2 represents OpenAI's most advanced model with enhanced reasoning, improved accuracy, and superior multimodal capabilities.
- Advanced reasoning and problem-solving capabilities
- Enhanced multimodal understanding (text, images, audio)
- 200K token context window for complex tasks
- Improved accuracy on mathematical and logical problems
- Best-in-class performance on coding benchmarks
GPT-5 mini: The Efficiency Champion
GPT-5 mini offers remarkable performance at a fraction of the cost, making it ideal for high-volume applications.
- 10x cheaper than GPT-5.2 for input tokens
- Maintains strong performance on most tasks
- 128K context window for substantial conversations
- Optimized for speed and efficiency
- Perfect for chatbots and content generation
GPT-5 nano: Ultra-Low Cost AI
GPT-5 nano provides AI capabilities at unprecedented low cost, enabling new use cases and applications.
- 35x cheaper than GPT-5.2 for input tokens
- 64K context window for focused tasks
- Ideal for edge computing and IoT applications
- Enables AI in cost-sensitive environments
- Perfect for simple automation and classification
Start with GPT-5 mini for most applications, then upgrade to GPT-5.1 or 5.2 if you need enhanced capabilities, or downgrade to nano for ultra-high-volume use cases.
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