Operational AI Cost Calculator
Estimate your production API run-rate. Dynamic token-based calculations comparing major cloud models side-by-side.
Usage Parameters
Includes system prompt + context / RAG documents.
Expected size of the model's generated response.
Estimated Monthly API Cost
| Model Name | Input Cost | Output Cost | Total / Month |
|---|---|---|---|
| GPT-4o by OpenAI | $0.00 | $0.00 | $0.00 |
| Claude 3.5 Sonnet by Anthropic | $0.00 | $0.00 | $0.00 |
| Gemini 1.5 Pro by Google | $0.00 | $0.00 | $0.00 |
| Llama 3.1 405B (Hosted) by Meta / Providers | $0.00 | $0.00 | $0.00 |
| GPT-4o-mini by OpenAI | $0.00 | $0.00 | $0.00 |
| Gemini 1.5 Flash by Google | $0.00 | $0.00 | $0.00 |
| Claude 3.5 Haiku by Anthropic | $0.00 | $0.00 | $0.00 |
Key Cost Observations
- Input/Output Asymmetry: Output tokens are generally 3x to 5x more expensive to generate than input tokens due to autoregressive decoding cost.
- RAG Impact: Using vector search to retrieve documents typically inflates input tokens by 2,000–8,000 tokens per query, drastically impacting run rate.
- Mini Models Advantage: Switching from premium models (GPT-4o / Claude 3.5 Sonnet) to lightweight models (GPT-4o-mini / Gemini 1.5 Flash) can reduce operational costs by up to 90% while keeping response speeds fast.