AI API Pricing Calculator
compare 28 models across 7 providers, no signup
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What is AI API Pricing Calculator?
The AI API Pricing Calculator from QuickFix.tools is a free browser-based tool that helps developers, startups, and teams estimate their monthly AI API costs across every major provider including OpenAI, Anthropic, Google, DeepSeek, Perplexity, xAI, and Mistral. The calculator compares 28+ models side by side, allowing users to input their usage patterns (requests per day, average input tokens, average output tokens) to see daily and monthly cost estimates for each model.
Key features include batch processing discounts at 50% off standard rates, prompt caching support showing ~90% savings on cached input tokens for Anthropic, OpenAI, and Google, and detailed breakdown of input vs output token pricing where output tokens cost 3-6x more. The tool also educates users on hidden costs like reasoning tokens, long context surcharges, tool use fees, and retry billing. All calculations run entirely in the browser with no signup, no account, and no data sent to servers.
This tool is specifically designed for developers building AI applications, SaaS founders forecasting unit economics, CTOs planning infrastructure budgets, and product managers evaluating model costs. It's ideal for anyone choosing between models for production pipelines, optimizing AI spend, or understanding how token usage translates to real dollar costs before building.
AI API Pricing Calculator pricing
Pricing model: Freemium
The AI API Pricing Calculator is 100% free to use with no signup, no account, and no credit card required. There are no paid tiers or premium features - all functionality including batch processing discounts, prompt caching calculations, and comparison across all 28+ models is available for free. The calculator uses public pay-as-you-go API pricing from providers and does not charge users anything to access or use the tool.
AI API Pricing Calculator pros
- Completely free with no signup required
- No account or credit card needed
- Compares 28+ models across 7 major providers
- All calculations run in browser - no data sent anywhere
- Shows daily and monthly cost estimates side by side
- Includes batch processing discount calculations at 50% off
- Supports prompt caching savings showing ~90% input token discounts
- Covers OpenAI, Anthropic, Google, DeepSeek, Perplexity, xAI, and Mistral
- Explains hidden costs like reasoning tokens and long context surcharges
- Shows output tokens are 3-6x more expensive than input tokens
- Provides usage examples for requests per day (chatbot vs batch pipeline)
- Includes token size examples (simple question ~50 tokens, RAG 2000-8000+)
- Single page tool with fast loading and instant results
- Pricing verified and updated regularly (March 2026)
- Helps identify cost optimization opportunities before building
AI API Pricing Calculator cons
- Uses base token tier pricing only - excludes some fees
- Excludes request/search/reasoning/citation query fees from calculations
- Does not include flex, priority, and time-window discounts
- Some providers apply higher rates for long-context requests not shown
- Token count is estimate based on 1 token ≈ 4 characters heuristic
- No API access to integrate calculator into other tools
- Cannot save or export usage scenarios for later reference
- Does not model actual user behavior patterns like enterprise tools
Frequently asked questions about AI API Pricing Calculator
What is the AI API Pricing Calculator?
The AI API Pricing Calculator is a free browser-based tool that estimates your monthly API costs across every major AI provider. You input your usage pattern (requests per day, average input tokens, average output tokens) and it multiplies against every major model's pricing to show daily and monthly costs side by side for 28+ models across OpenAI, Anthropic, Google, DeepSeek, Perplexity, xAI, and Mistral.
Is this calculator free to use?
Yes, the AI API Pricing Calculator is completely free with no signup, no account, and no credit card required. All features including batch processing discounts, prompt caching calculations, and side-by-side model comparison are available at no cost.
Do I need to create an account?
No account is needed. The tool runs entirely in your browser with no signup required. No data is sent anywhere and no personal information is collected.
Which AI providers and models are included?
The calculator covers 7 major providers: OpenAI (GPT-5, GPT-4o, o1, o3, o4-mini, GPT-4.1 mini, GPT-5 nano), Anthropic (Claude Opus, Sonnet, Haiku), Google (Gemini 3 Pro, Gemini 2.5 Pro, Gemini 2.5 Flash), DeepSeek (deepseek-chat, deepseek-reasoner), Perplexity (Sonar, Sonar Pro, Sonar Reasoning Pro), xAI (grok-3, grok-4, grok-3-mini), and Mistral (Mistral Large 3, Mistral Small, Ministral, Codestral).
How do I calculate my AI API costs?
Enter three inputs: (1) Requests per day - how many API calls your application makes daily (500-5,000 for chatbots, 10,000-100,000 for batch pipelines), (2) Average input tokens - typical prompt size (50 tokens for simple questions, 200-500 for prompts with context, 2,000-8,000+ for RAG), (3) Average output tokens - how much the model generates (50 tokens for short answers, 100-200 for paragraphs, 500-2,000+ for articles/code). The calculator shows daily and monthly costs for all models.
What are batch processing discounts?
Most providers offer batch processing at 50% off standard rates. Instead of real-time responses, you submit requests in bulk and get results within 24 hours. This is ideal for data labeling, content generation, document processing, and workflows where latency doesn't matter.
How does prompt caching save money?
Prompt caching (available on Anthropic, OpenAI, and Google) stores your system prompt and reuses it across requests. Cached input tokens cost approximately 90% less than uncached tokens. This is most effective when you have a large, static system prompt with instructions, examples, or documents that stays the same across many requests.
Why are output tokens more expensive than input tokens?
Output tokens are typically 3-6x more expensive than input tokens because generating text requires more compute than reading it. When optimizing costs, reducing output length through shorter responses or structured output formats often has more impact than reducing input length.
What hidden costs should I watch for?
Key hidden costs include: Reasoning tokens (OpenAI's o-series bills internal 'thinking' tokens at output rates, multiplying costs 3-10x), Long context surcharges (Google Gemini charges 2x for prompts over 200K tokens), Tool use/function calls (tool definitions count as input tokens and add up), and Retries/errors (failed requests with partial responses may still be billed).
How accurate is the token count estimate?
The token count uses the standard heuristic of 1 token ≈ 4 characters in English, which is accurate enough for budgeting purposes. As reference: 100 tokens ≈ 75 words, 1 page of text ≈ 750 words ≈ 1000 tokens. For exact token counts, the tool references tiktokenizer.vercel.app as the model-specific tokenizer.