AI Pricing Table
Compare API costs across all major AI providers in one comprehensive table
View detailed pricing for OpenAI, Claude, Gemini, and other AI providers in an easy-to-read table format. Compare input (prompts) and output (generated content) per 1 million tokens costs across different models to find the most cost-effective AI solution for your needs.
Prices are shown in USD per 1 million tokens. Token counts vary by model and language, but as a rough guide:
1 token ≈ 4 characters or ¾ of a word in English.
Model PricesPer 1M tokens
Provider | Model | Context Window | Input Price | Output Price | Cached Input Price | Price Range |
|---|---|---|---|---|---|---|
| Gemma 3 | na | $0.000 | $0.000 | $0.000 | Low | |
| Alibaba | Qwen-Turbo | 1M | $0.050 | $0.200 | $0.020 | Low |
| DeepSeek | DeepSeek-Chat | 64K | $0.070 | $1.100 | $0.035 | Low |
| Gemini 2.0 Flash-Lite | 1M | $0.075 | $0.300 | N/A | Low | |
| Gemini 1.5 Flash (>128K) | 1M | $0.075 | $0.300 | $0.019 | Low | |
| Gemini 2.0 Flash | 1M | $0.100 | $0.400 | $0.025 | Low | |
| DeepSeek | DeepSeek-Reasoner | 64K | $0.140 | $2.190 | $0.035 | Mid |
| OpenAI | GPT-4o mini | 128K | $0.150 | $0.600 | $0.075 | Low |
| Gemini 1.5 Flash (>128K) | 1M | $0.150 | $0.600 | $0.037 | Low | |
| Alibaba | Qwen-Plus | 131K | $0.400 | $1.200 | $0.120 | Low |
| Anthropic | Claude Haiku 3.5 | 200K | $0.800 | $4.000 | N/A | Mid |
| OpenAI | o3-mini | 200K | $1.100 | $4.400 | $0.550 | Mid |
| Gemini 1.5 Pro | 1M | $1.250 | $5.000 | N/A | Mid | |
| Alibaba | Qwen-Max | 32K | $1.600 | $6.400 | $0.640 | Mid |
| OpenAI | GPT-4o | 128K | $2.500 | $10.000 | $1.250 | Mid |
| Anthropic | Claude Sonnet 3.7 | 200K | $3.000 | $15.000 | N/A | Mid |
| Anthropic | Claude Opus 3 | 200K | $15.000 | $75.000 | N/A | High |
| OpenAI | o1 Frontier | 200K | $15.000 | $60.000 | $7.500 | High |
| OpenAI | GPT-4.5 | 128K | $75.000 | $150.000 | $37.500 | High |
| OpenAI | GPT-4.1 | 1M | $2.000 | $8.000 | $0.500 | Mid |
| OpenAI | GPT-4.1 mini | 1M | $0.400 | $1.600 | $0.100 | Low |
| OpenAI | GPT-4.1 nano | 1M | $0.100 | $0.400 | $0.025 | Low |
| OpenAI | GPT-4.1 (Fine-tuning) | 1M | $3.000 | $12.000 | $0.750 | Mid |
| OpenAI | GPT-4.1 mini (Fine-tuning) | 1M | $0.800 | $3.200 | $0.200 | Mid |
| OpenAI | GPT-4o (Fine-tuning) | 1M | $3.750 | $15.000 | $1.875 | Mid |
| xAI | Grok 3 | 131K | $3.000 | $15.000 | N/A | Mid |
| xAI | Grok 3 (Fast) | 131K | $5.000 | $25.000 | N/A | High |
| xAI | Grok 3 Mini | 131K | $0.300 | $0.500 | N/A | Low |
| xAI | Grok 3 Mini (Fast) | 131K | $0.600 | $4.000 | N/A | Mid |
| xAI | grok-2-vision-1212 | 131K | $1.500 | $6.000 | $0.750 | Mid |
| Mistral | Mistral Large | 32K | $8.000 | $24.000 | N/A | High |
| Mistral | Mistral Medium | 32K | $2.500 | $7.500 | N/A | Mid |
| Mistral | Mistral Small | 32K | $0.200 | $0.600 | N/A | Low |
| Gemini 2.5 Flash Preview | 1M | $0.150 | $0.600 | $0.037 | Low | |
| Gemini 2.5 Flash Preview (Thinking) | 1M | $0.150 | $3.500 | $0.037 | Low | |
| Gemini 2.5 Pro Preview | 1M | $1.250 | $10.000 | $0.310 | Mid | |
| Vercel | v0-1.0-md | 1M | $3.000 | $15.000 | N/A | Mid |
| Anthropic | Claude Sonnet 3.5 | 200K | $3.000 | $15.000 | N/A | Mid |
| Anthropic | Claude Sonnet 4 | 200K | $3.000 | $15.000 | N/A | Mid |
| Anthropic | Claude Opus 4 | 200K | $15.000 | $75.000 | N/A | High |
Understanding AI Pricing & Terminology
What are Tokens?
Tokens are the basic units of text that AI models process. They represent pieces of words, not entire words. For example, the word "unhappiness" might be broken into the tokens "un", "happiness".
Input Tokens
These are the tokens in your prompt or question to the AI. Input tokens include:
- Your instructions to the AI
- Context information you provide
- Examples you include
- System messages defining AI behavior
Output Tokens
These are the tokens in the AI‘s response. Output tokens usually cost more than input tokens because:
- They require more computational work
- The model must make predictions for each token
- They represent the AI‘s unique "work product"
How Many Tokens in Text?
As a general rule of thumb:
- 1 token ≈ 4 characters in English text
- 1 token ≈ ¾ of a word in English
- 100 tokens ≈ 75 words or ≈ 1 paragraph
- 1,000 tokens ≈ 750 words or ≈ 1 page
- 1M tokens ≈ 750,000 words or ≈ 1,500 pages
Disclaimers
- Prices may vary based on enterprise agreements and volume discounts.
- Prices are subject to change without notice. Always check the official pricing pages of providers.
- Context lengths and capabilities may vary for different use cases and implementations.
- This information is provided for reference only and should not be considered financial advice.
Understanding AI Model Pricing
AI model pricing is typically based on token consumption, where tokens represent chunks of text processed by the model. Understanding how pricing works helps you optimize costs and choose the right model for your specific use case.
Token Basics
- • 1 token ≈ 4 characters or ¾ of a word in English
- • Different languages have varying token densities
- • Code and special characters may use more tokens
- • Tokens include both input (prompts) and output (responses)
Cost Calculation
- • Input tokens: Text you send to the AI
- • Output tokens: Text the AI generates
- • Total cost = (Input tokens × Input rate) + (Output tokens × Output rate)
- • Rates are typically shown per 1 million tokens
Model Complexity
More sophisticated models with larger parameter counts typically cost more per token.
Context Windows
Larger context windows allow more information but may increase costs.
Usage Patterns
Your input/output ratio affects total costs significantly.
Cost Optimization Strategies
Input Optimization
- • Use concise, clear prompts to minimize input tokens
- • Avoid repetitive instructions within conversations
- • Leverage system messages for context setting
- • Consider prompt templates for consistency
- • Use cached inputs when available for repeated queries
Output Management
- • Set maximum token limits for generated responses
- • Request specific formats (bullet points vs paragraphs)
- • Use stop sequences to control output length
- • Consider streaming for better user experience
- • Choose models based on your output quality needs
Key Provider Differences
OpenAI
- • Wide range of models from basic to advanced
- • Strong performance across various tasks
- • Regular model updates and improvements
- • Comprehensive API documentation
Anthropic (Claude)
- • Focus on safety and helpful responses
- • Large context windows (up to 200K tokens)
- • Strong performance on reasoning tasks
- • Constitutional AI approach
Google (Gemini)
- • Multimodal capabilities (text, image, audio)
- • Competitive pricing for high-volume usage
- • Integration with Google Cloud services
- • Strong performance on technical tasks
Current Pricing Trends
Downward Trends
- • Overall token costs decreasing as technology improves
- • More competitive pricing due to market competition
- • Introduction of tiered pricing for different use cases
- • Better price/performance ratios with newer models
Market Dynamics
- • Premium features (larger context, multimodal) command higher prices
- • Volume discounts available for enterprise customers
- • Cached inputs reducing costs for repeated queries
- • Regional pricing variations emerging
Choosing the Right Model for Your Budget
Budget-ConsciousLow-Cost Applications
For high-volume, simple tasks where cost efficiency is paramount.
- • Basic text processing and classification
- • Simple Q&A systems
- • Content moderation
- • Data extraction from structured text
BalancedGeneral Purpose Applications
For most business applications requiring good quality and reasonable costs.
- • Customer support chatbots
- • Content generation and editing
- • Code assistance and debugging
- • Educational applications
PremiumHigh-Quality Applications
For critical applications where quality justifies higher costs.
- • Complex reasoning and analysis
- • Creative writing and content creation
- • Research and technical documentation
- • Multi-step problem solving
Estimating Your Costs
Use these guidelines to estimate your monthly AI costs based on usage patterns:
Light Usage
- ~100K tokens/month
- Personal projects
- Small applications
- Testing and development
Moderate Usage
- ~1M tokens/month
- Small business applications
- Customer support bots
- Content generation
Heavy Usage
- 10M+ tokens/month
- Enterprise applications
- High-volume processing
- 24/7 production systems
Real-World Cost Examples
Customer Support Chatbot
A moderate-volume customer support bot handling 1,000 conversations per day
Usage Pattern:
- • Avg Input: 150 tokens
- • Avg Output: 100 tokens
- • Volume: 1000 interactions/day
- • Model: GPT-4o
Cost Breakdown:
Monthly Input: 4.50M tokens
Monthly Output: 3.00M tokens
Total: $105
Content Generation Tool
A content creation tool generating 50 blog posts per month
Usage Pattern:
- • Avg Input: 300 tokens
- • Avg Output: 1500 tokens
- • Volume: 50 interactions/day
- • Model: Claude Sonnet
Cost Breakdown:
Monthly Input: 0.01M tokens
Monthly Output: 0.07M tokens
Total: $1,170
Code Assistant
A development team using AI for code review and suggestions
Usage Pattern:
- • Avg Input: 500 tokens
- • Avg Output: 200 tokens
- • Volume: 200 interactions/day
- • Model: GPT-4o mini
Cost Breakdown:
Monthly Input: 2.20M tokens
Monthly Output: 0.88M tokens
Total: $5.94
Best Models by Use Case
High Input, Low Output
Document analysis and summarization
Recommended Models:
Tip: Focus on models with low input pricing
Low Input, High Output
Creative writing and content generation
Recommended Models:
Tip: Prioritize models with good output pricing and quality
Balanced Usage
Interactive conversations and Q&A
Recommended Models:
Tip: Consider overall cost per conversation
Monthly Budget Planning Guide
Monthly Budget: $50
Recommended Strategy:
- • GPT-4o mini for most tasks (~300K tokens)
- • Claude Haiku for document processing
- • Perfect for personal projects and prototyping
What You Can Achieve:
- • 50 detailed conversations
- • 100 code reviews
- • 25 document summaries
Monthly Budget: $200
Recommended Strategy:
- • Mix of GPT-4o and GPT-4o mini (~100K quality tokens)
- • Claude Sonnet for complex reasoning
- • Good for small business applications
What You Can Achieve:
- • 500 customer interactions
- • 100 content pieces
- • 1,000 code assists
Monthly Budget: $1,000
Recommended Strategy:
- • GPT-4o for critical tasks (~100K tokens)
- • Claude Sonnet for reasoning (~200K tokens)
- • GPT-4o mini for high-volume tasks (~5M tokens)
What You Can Achieve:
- • 5,000 support tickets
- • 200 articles
- • 10,000 code reviews
Advanced Cost Optimization Tips
Cost-Saving Strategies
- Model Switching: Use cheaper models for simple tasks, premium for complex ones
- Batch Processing: Group similar requests to reduce overhead
- Caching: Store and reuse responses for common queries
- Prompt Engineering: Optimize prompts to reduce token usage
- Output Limits: Set max_tokens to control response length
Monitoring and Optimization
- Usage Analytics: Track token consumption patterns
- A/B Testing: Compare model performance vs cost
- Regular Reviews: Reassess model choices quarterly
- Alert Systems: Set up budget alerts for cost control
- ROI Analysis: Measure value generated per dollar spent
Industry-Specific Cost Examples
E-commerce
- Product descriptions: $200-500/month
- Customer service: $300-800/month
- Review analysis: $100-300/month
Focus on Claude Haiku for descriptions, GPT-4o mini for support
Software Development
- Code generation: $400-1000/month
- Documentation: $200-500/month
- Code review: $100-400/month
Mix GPT-4o for complex logic, GPT-4o mini for routine tasks
Content & Marketing
- Blog writing: $500-1500/month
- Social media: $200-600/month
- Ad copy: $300-800/month
Claude Sonnet for long-form, GPT-4o for creative campaigns