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AI Cost Calculator

Calculate and optimize your LLM API costs. Compare GPT-4, Claude, Gemini and get expert tips to reduce spending by 60-80%.

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Optimization Tips

📊 Calculate Your AI Costs

Faster, cheaper version of GPT-5 for well-defined tasks

How many API calls per month?

Average input length (1 token ≈ 4 characters)

Average response length

💰 Your Costs

Per Request
$0.0005
Monthly Cost
$5.25
Annual Cost
$63.00
Input tokens/mo: 5.0M
Output tokens/mo: 2.0M
Input cost: $1.25/mo
Output cost: $4.00/mo

💡 Optimization Tips

💡 Switch to Apertus for 100% cost savings ($0.00/mo vs $5.25/mo).

💡 Switch to Gemini 2.5 Flash for 88% cost savings ($0.65/mo vs $5.25/mo).

📖 How to Use This Calculator

Get accurate cost estimates in 3 simple steps.

1

Select Your Model

Choose from GPT-4, Claude, Gemini, Llama and other popular models. Recommended models are marked with ⭐.

2

Enter Your Usage

Input your monthly API calls, average prompt length, and response length. The calculator updates in real-time.

3

Get Insights & Optimize

See your costs, compare all models, and get personalized optimization suggestions to reduce spending.

Spending $10k+/Month on AI?

I've helped companies reduce their LLM costs by 60-80% while improving performance. Let me analyze your usage and show you exactly where to optimize.

Real example: Reduced a client's costs from $50k/month to $8k/month through caching, prompt optimization, and smart model selection. Same quality, 84% cost savings.

Free 30-min consultation
Custom optimization plan
ROI guarantee

Frequently Asked Questions

How accurate is this calculator?

Prices are updated regularly from official provider pricing pages (OpenAI, Anthropic, Google). Actual costs may vary based on your specific usage patterns, but this provides a reliable estimate within 5-10% accuracy.

What's the easiest way to reduce AI costs?

Implement prompt caching (40-60% savings), optimize prompt length (20-30% savings), and use cheaper models for simple tasks (50-80% savings). Most companies can reduce costs by 60%+ with these three strategies.

When should I consider fine-tuning vs API calls?

If you're spending $10k+/month on API calls for similar tasks, fine-tuning can reduce costs by 80%+. Fine-tuning works best for specialized, repetitive tasks. For diverse use cases, smart API usage is usually better.

Which model should I use?

GPT-4 Turbo or Claude 3.5 Sonnet for complex tasks, GPT-3.5 Turbo or Claude Haiku for simple tasks, Gemini Flash for very high volume with tight budgets. Use this calculator to compare costs for your specific usage.