Calculator Inputs
Use the form below to simulate request economics, context pressure, and monthly affordability for AI workloads.
Example Data Table
| Scenario | Prompt Tokens | Completion Tokens | Cached % | Requests / Day | Monthly Budget |
|---|---|---|---|---|---|
| Support Copilot | 1800 | 650 | 40% | 900 | $180 |
| RAG Analyst | 3200 | 1100 | 25% | 600 | $260 |
| Code Assistant | 2500 | 1400 | 30% | 1200 | $420 |
| Agent Workflow | 4200 | 1800 | 55% | 750 | $520 |
Formula Used
The simulator estimates request economics by separating compressed input, cached input, uncached input, and completion output.
1) Compressed prompt tokens Compressed Prompt = Average Prompt Tokens × (1 − Compression Ratio) 2) Cached and uncached input split Cached Input = Compressed Prompt × Cached Ratio Uncached Input = (Compressed Prompt × (1 − Cached Ratio)) + System Tokens 3) Cost per request Base Cost = (Uncached Input ÷ 1,000,000 × Input Price) + (Cached Input ÷ 1,000,000 × Cached Input Price) + (Output Tokens ÷ 1,000,000 × Output Price) Cost per Request = Base Cost × (1 + Retry Rate) 4) Planned monthly demand Planned Requests per Day = Base Requests per Day × (1 + Growth Rate) Planned Requests per Month = Planned Requests per Day × Billing Days 5) Budget and context tests Budget Utilization % = Planned Monthly Cost ÷ Monthly Budget × 100 Usable Context = Context Window × (1 − Reserved Context Ratio) Context Utilization % = (Input Tokens + Output Tokens) ÷ Usable Context × 100How to Use This Calculator
- Enter your monthly spending limit and the token pricing for input, output, and cached input.
- Add average prompt tokens, completion tokens, fixed system tokens, and the share of prompt tokens likely to be cached.
- Set prompt compression, retry rate, daily requests, monthly billing days, and projected demand growth.
- Enter your model context window, reserved context percentage, and peak concurrency assumptions.
- Click Simulate Token Budget to show results above the form and directly under the page header.
- Use the CSV and PDF buttons to save the summary and scenario tables for planning reviews.
FAQs
1) What does this simulator estimate?
It estimates request cost, affordable traffic, context pressure, monthly token volume, and budget headroom using pricing, prompt size, retry, caching, and growth assumptions.
2) Why separate cached and uncached input tokens?
Many providers bill cached input at a lower rate. Splitting these categories shows whether reuse of repeated instructions or retrieved context meaningfully lowers cost.
3) What is prompt compression in this tool?
Prompt compression represents token savings from summarization, shorter templates, cleaner retrieval chunks, or removing repeated instructions before each request is sent.
4) Why include retry and regeneration rate?
Real systems often regenerate outputs after moderation failures, tool errors, or user retries. Including that overhead makes the budget estimate more realistic.
5) What does context utilization show?
It shows how much of the reserved usable context is consumed by one request. High values warn that truncation or overflow may happen sooner.
6) Can I compare multiple demand scenarios?
Yes. The scenario table projects conservative, base, and aggressive traffic levels so you can see how spending changes as usage rises.
7) Is this suitable for production forecasting?
It is a planning tool, not an invoice engine. Provider rounding rules, hidden overhead, and model behavior can shift actual billed costs.
8) How can I reduce token spend quickly?
Reduce prompt length, improve retrieval quality, increase safe caching, limit unnecessary completions, trim retries, and move heavy flows to cheaper models.