Cost formula
Monthly budget = daily requests × 30 × ((input tokens / 1M × input price) + (output tokens / 1M × output price))
Calculator
Monthly usage budget planner
Convert product traffic assumptions into a 30-day AI spend forecast and see whether you stay inside budget.
Budget burn
Within monthly budget
$234.00/ $500.00 budget
225,000 requests · GPT-5 mini
Projected spend$234.00
Monthly budget$500.00
Daily burn$7.80
Runway30.0 days
Utilization46.8%
Max req @ budget480,769
Inputs
Product traffic
DAU × requests × tokens against a hard monthly spend cap.
Runway
Burn gauge & throttle
How fast the month burns, and what to cut if you overshoot.
Budget runway30.0 / 30 days
Daily burn $7.80 · $266.00 still available this month.
Per request$0.00104
Input / cached / output$50.63 / $3.37 / $180.00
Max requests @ budget480,769
Traffic fits the budget with 30.0 days of runway at current burn. Headroom: 255,769 more requests before the cap.
Uses a 30-day month. Updated 2026-07-31. Approximate static list prices for planning only. Always verify against each provider’s official pricing page before production budgeting.
Guide
How to get value from this calculator
Turn product traffic assumptions into a monthly AI budget with room for growth. Define requests per day, tokens per request, and model choice to see projected spend before you set limits or pricing. Essential for finance alignment and for deciding when to optimize vs scale.
Why it matters
Without a traffic-to-dollars model, AI features launch without guardrails and overrun budgets silently. A monthly budget tied to concrete usage assumptions gives product and finance teams a shared number to monitor against.
How to use it
- Estimate daily active users or API requests for your AI feature.
- Set average input tokens per request including system prompt and context.
- Set average output tokens per request based on your max_tokens or observed completions.
- Select the production model and review projected monthly cost.
- Add buffer for staging, internal usage, and growth (10–25% is common).
- Set provider spend caps or alerts based on the projected total.
- Read the runway meter and throttle guidance against your spend assumptions.
Planning tips
- Separate budgets for production, staging, and eval—staging traffic is often underestimated.
- Model peak days at 2–3x average daily requests to avoid month-end surprises.
- If output tokens dominate, prioritize shorter responses or cheaper models before cutting features.
- Revisit the budget when you change models, add RAG context, or enable agent tool loops.
- If runway is short, throttle max tokens or model tier before the month ends.
- Cross-check with provider dashboard usage after two weeks of real traffic.
Frequently asked questions
Should I budget on list price or negotiated rates?
CentsPerToken uses approximate list prices for planning. If you have enterprise discounts or credits, apply your effective rate manually to the projected token volume.
How do I handle variable traffic?
Run scenarios at low, expected, and high daily request counts. Use the high scenario for cap setting and the expected scenario for P and L planning.
Does this include embedding and image costs?
This planner focuses on LLM token workloads. Add embedding, image, and audio costs from their dedicated calculators for a full AI stack budget.
Are these budgets official commitments?
No. All outputs are approximate planning figures. Actual spend depends on real usage patterns and current provider pricing.