AI Cost Calculator
Project monthly LLM spend across models before you ship.
Cheapest / month
$90
Most expensive / month
$756
| Model | Per request | Per day | Per month |
|---|---|---|---|
| OpenAI GPT-5 mini | $0.001500 | $3 | $90 |
| Google Gemini 2.5 Flash | $0.001860 | $3.72 | $111.6 |
| Anthropic Claude Haiku | $0.003360 | $6.72 | $201.6 |
| OpenAI GPT-5 | $0.007500 | $15 | $450 |
| Google Gemini 2.5 Pro | $0.007500 | $15 | $450 |
| Anthropic Claude Sonnet | $0.0126 | $25.2 | $756 |
Prices are per million tokens from published list pricing and are a planning estimate.
Cutting LLM Cost and Latency
Seven levers ranked by payoff, model-routing patterns, and a realistic 100% → 11% cost walkthrough.
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About this tool
Token pricing is quoted per million tokens, which makes it hard to reason about real monthly bills. Enter your request volume and average input and output token counts, and this calculator shows per-request, daily and monthly cost across the major model families side by side.
How LLM pricing works
You pay separately for input tokens (your prompt, system message and any retrieved context) and output tokens (the completion). Output is typically three to five times more expensive, so verbose responses dominate the bill.
How to reduce AI API costs
Trim system prompts, cap max output tokens, cache repeated context, and route simple requests to a smaller model. Reserving the flagship model for the requests that genuinely need it usually cuts spend by more than half.
How to use AI Cost Calculator
- 1
Estimate tokens
Roughly 1 token ≈ 4 characters of English. Paste a representative prompt into the token counter if you want a tighter number.
- 2
Enter volume
Add requests per day or per month, including retries and background jobs.
- 3
Compare models
The table shows projected monthly cost side by side so you can see what a model swap is actually worth.
- 4
Budget with headroom
Add 20–30% for retries, evaluation runs and traffic spikes.
Example input
1,200 input + 400 output tokens · 50,000 requests/month
Expected output
≈ $X/month per model, compared across GPT, Claude and Gemini tiers
Best practices
- Model cost per request, then multiply by realistic monthly volume — averages hide the tail where cost actually lives.
- Separate input and output tokens: output is typically 3–5× more expensive, so trimming verbose responses beats trimming prompts.
- Cache system prompts and retrieved context where the provider supports it; repeated prefixes are the single biggest avoidable spend.
- Route by difficulty — use a small model as the default and escalate only when confidence is low.
- Re-check pricing quarterly and set a hard monthly spend cap at the provider before you scale traffic.
Why AI Cost Calculator matters
LLM spend scales with usage, not with headcount, so a successful launch can multiply your bill overnight if nobody modelled it first.
Knowing cost per request lets you price your own product with a real gross margin instead of a guess.
Related free & paid tools
| Tool name | Type | Key features | Link |
|---|---|---|---|
| OpenAI pricing | Free | Current per-token rates for every model | Visit |
| HeliconeOffer | Freemium | Per-request LLM cost and latency observability | Visit |
| LangfuseOffer | Freemium | Open-source tracing with cost attribution | Visit |
| OpenRouterOffer | Freemium | One API across providers with live price comparison | Visit |
Links marked Offer may be partner links. They cost you nothing extra and never affect which tools we recommend.