LLM Usage Cost Calculator

LLM Usage Snapshot

${{ costPerCall.toFixed(4) }} per request

Prompt {{ formatNumberDisplay(promptTokens) }} tokens Completion {{ formatNumberDisplay(completionTokens) }} tokens ${{ dailyCost.toFixed(2) }} daily ${{ monthlyCost.toFixed(2) }} monthly {{ monthlyTokens.toLocaleString() }} monthly tokens Margin {{ marginPercent }}% Retries ×{{ retryMultiplierSafe.toFixed(2) }} Budget {{ budgetStatusText }}

Preset:

Prompt tokens:

tokens

Completion tokens:

tokens

Requests per day:

req

Billing days per month:

days

Prompt draft:

Estimator auto applied: {{ estimatedTokens }} tokens Updating the prompt updates token count.

Prompt rate:

$ / 1K tokens

Prompt cached rate:

$ / 1K tokens

Cache hit rate:

Completion rate:

$ / 1K tokens

Margin uplift:

Fixed monthly fees:

Growth scenario:

Retry multiplier:

Monthly budget cap:

Waiting for inputs. Enter token counts and requests to see projections.

Preset: {{ presetLabel }}

Cost breakdown per horizon
Metric	Tokens	Cost (USD)	Copy
{{ row.label }}	{{ row.tokensDisplay }}	{{ row.costDisplay }}

Token totals include prompt and completion tokens. Margin uplift, retries, and fixed fees shape daily and monthly costs.

Breakdown of prompt, completion, margin uplift, fixed fees, and totals across request, daily, and monthly horizons.

Cost composition by component
Component	Per Request	Per Day	Per Month	Copy
{{ row.label }}	{{ row.perRequest }}	{{ row.perDay }}	{{ row.perMonth }}

Totals reconcile with the cost breakdown, letting you trace how much margin, retries, or fees contribute to each horizon.

Usage window: {{ billingDays }} days · Growth scenario: +{{ growthPercent }}% · Retry multiplier: ×{{ retryMultiplierSafe.toFixed(2) }}

Usage detail
Component	Per Request	Per Day	Per Month	Copy
{{ row.label }}	{{ row.perRequest }}	{{ row.perDay }}	{{ row.perMonth }}

High-growth scenario adds {{ growthPercent }}% more requests when drawing the chart. Adjust requests per day or the retry multiplier for conservative estimates.

Efficiency metrics reveal how many tokens or requests each dollar buys and how budget caps interact with the current configuration.

Efficiency metrics
Metric	Value	Copy
{{ row.label }}	{{ row.value }}

Tags: Automation , Devtools , Productivity

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Language model usage costs are token based charges that reflect how much text you send and receive, multiplied by provider rates, then adjusted by your workload. A language model token cost calculator helps teams plan capacity and compare pricing in a consistent way without touching production.

You enter typical prompt and completion token counts, the number of successful requests per day, and the billed days in your month. You can choose a pricing preset or set your own rates, add an optional margin, include fixed monthly fees, and account for cache hits, retries, and expected growth so the estimate matches how you operate.

Results show cost per request, per day, and per month along with total tokens. A quick forecast compares base, growth, and peak scenarios so you can see budget headroom or overage at a glance. If a value looks surprising, try smaller requests per day or lower completion tokens and observe how the totals move.

As one example, a workload with 1,400 prompt tokens and 600 completion tokens at typical rates can land under a cent per request and around a few dollars per day at moderate volume. Your figures will shift with cache hits, retries, and any margin uplift, so review those inputs carefully before sharing a number.

Treat these figures as planning signals. Provider tokenizers differ and published price sheets change, so keep inputs current and favor repeatable scenarios for fair comparisons.

Technical Details:

The calculator models prompt tokens and completion tokens as the core quantities. Prices are entered as dollars per 1,000 tokens for prompt input, cached prompt input, and completion output. A cache hit rate blends the two prompt prices. Request volume is expressed per day and scaled by billed days in the month. A retry multiplier expands daily volume to reflect extra attempts.

Computation proceeds by forming an effective prompt rate, adding completion costs per request, and applying a margin multiplier if present. Daily cost multiplies by effective requests per day; monthly cost multiplies by billed days and adds fixed monthly fees. A growth scenario inflates daily requests by a percentage, and a peak scenario uses the larger of one point five times base or growth plus a quarter.

Outputs include cost per request, daily and monthly costs, total monthly tokens, and efficiency metrics such as effective cost per thousand tokens, tokens per dollar, and requests per dollar. Budget delta is computed against an optional monthly cap; non‑negative values indicate headroom while negative values indicate overage.

\begin{matrix} R p_{eff} & = & R p_{base} \cdot (1 - H) + R p_{cache} \cdot H \\ k {req}_{base} & = & \frac{P}{1000} \cdot R p_{eff} + \frac{C}{1000} \cdot R c_{omp} \\ k {req}_{bill} & = & k {req}_{base} \cdot (1 + \frac{M}{100}) \\ Q e_{ff} & = & Q \cdot S \\ D {aily}_{cost} & = & k {req}_{bill} \cdot Q e_{ff} \\ T {month}_{tokens} & = & (P + C) \cdot Q e_{ff} \cdot D \\ M {onthly}_{cost} & = & D {aily}_{cost} \cdot D + F \\ g & = & (1 + \frac{G}{100}) \\ p & = & max (g + 0.25, 1.5) \end{matrix}

Symbols and units
Symbol	Meaning	Unit/Datatype	Source
P	Prompt tokens per request	tokens	Input
C	Completion tokens per request	tokens	Input
Q	Successful requests per day	requests	Input
S	Retry multiplier	×	Input
D	Billing days in the month	days	Input
R_p base	Prompt price per 1,000 tokens	$ / 1,000 tokens	Input/Preset
R_p cache	Cached prompt price per 1,000 tokens	$ / 1,000 tokens	Input/Preset
H	Cache hit ratio	0 to 1	Input
R_comp	Completion price per 1,000 tokens	$ / 1,000 tokens	Input/Preset
M	Margin uplift	%	Input
F	Fixed monthly fees	$	Input

Worked example. P = 1,400, C = 600, Q = 240, S = 1, D = 30, R_p base = 0.0025, R_p cache = 0.00125, H = 0, R_comp = 0.01, M = 0, F = 0.

\begin{matrix} R p_{eff} & = & 0.0025 \\ k {req}_{base} & = & \frac{1400}{1000} \cdot 0.0025 + \frac{600}{1000} \cdot 0.01 = 0.0095 \\ D {aily}_{cost} & = & 0.0095 \cdot 240 = 2.28 \\ M {onthly}_{cost} & = & 2.28 \cdot 30 = 68.40 \\ T {month}_{tokens} & = & (2000) \cdot 240 \cdot 30 = 14400000 \end{matrix}

At these settings, cost per request is $0.0095, daily cost is $2.28, monthly cost is $68.40, and monthly tokens are 14,400,000.

Budget interpretation
Threshold band	Lower bound	Upper bound	Interpretation	Action cue
Headroom	0	∞	Monthly cost is within the cap.	Scale volume or tighten cap as needed.
Overage	−∞	< 0	Monthly cost exceeds the cap.	Reduce tokens, lower retries, or adjust rates.

Units, precision, and rounding:

Currency shows two to four decimal places; negatives are prefixed with a minus sign.
Token counts display as whole numbers with thousands separators.
Requests per dollar prints two decimals; tokens per dollar prints without decimals.

Validation and bounds:

Input validation and limits
Field	Type	Min	Max	Step/Pattern	Placeholder
Model preset	Select	—	—	Preset or Custom	—
Prompt tokens	Number	1	—	Step 1	—
Completion tokens	Number	0	—	Step 1	—
Requests per day	Number	0	—	Step 1	—
Billing days	Number	1	—	Step 1	—
Prompt rate	Currency	0	—	Step 0.0001	—
Prompt cached rate	Currency	0	—	Step 0.0001	—
Cache hit rate	Percent	0	100	Step 1	—
Completion rate	Currency	0	—	Step 0.0001	—
Margin uplift	Percent	0	—	Step 1	—
Fixed monthly fees	Currency	0	—	Step 0.01	—
Growth scenario	Percent	0	—	Step 1	—
Retry multiplier	Number	1	—	Step 0.01	—
Monthly budget cap	Currency	0	—	Step 0.01	—
Prompt draft	Text	—	—	Blend estimator	Quarterly earnings prompt example

I/O formats:

Inputs and outputs
Input	Accepted families	Output	Encoding/Precision	Rounding
Numeric fields	Integer, decimal	Costs, tokens, efficiency	USD, tokens	2–4 decimals for currency
Prompt draft	Plain text	Token estimate	Blend of chars and words	Nearest integer
Snapshot	JSON	Current state	ISO timestamp	As displayed

Networking & storage:

Processing is client only; no data is transmitted or stored server side.

Performance & determinism:

All calculations are constant time for a given input.
Identical inputs yield identical outputs.

Assumptions & limitations:

Token estimator blends characters per token and words per token; it is approximate.
Cache savings apply only to prompt tokens, not completions.
Growth and peak scenarios modify request counts, not prices.
Margin multiplies base costs; it is not added as a flat fee.
Fixed monthly fees are added after token costs.
Budget requests per day subtract fixed fees before allocation.
Only USD currency is shown.
Heads‑up Tiered pricing, taxes, and provider discounts are not modeled.

Edge cases & error sources:

Zero billing days forces per day fee display to omit fixed fees.
Very large counts may overflow chart axes on small screens.
Floating point rounding can slightly shift cents at high volume.
Cache hit percent outside 0 to 100 is clamped in calculations.
Retry multiplier below 1 is forced to 1.
Negative values are coerced to zero where applicable.
Locale number formatting may differ for separators.
Copy to clipboard can be blocked by browser settings.
Export timing may vary with device performance.
Token estimator accuracy varies by tokenizer and language.

Privacy & compliance:

No data is transmitted or stored server side. Outputs are educational and not financial advice.

Step‑by‑Step Guide:

Cost estimation for tokenized language model workloads follows a simple sequence to produce daily and monthly totals.

Pick a pricing Preset or choose Custom to enter rates.
Enter Prompt tokens and Completion tokens.
Set Requests per day and Billing days.
Optional: paste a prompt to auto estimate tokens.
Open Advanced to adjust cache hit, retries, margin, fees, growth, and a budget cap.
Review the summary, components, usage, efficiency, and forecast to confirm fit.

Example. With 1,400 prompt and 600 completion tokens at typical rates and 240 requests per day, cost per request is about $0.0095 and monthly cost about $68.40.

If budget is tight, lower completion tokens or growth and revisit headroom.
Use a conservative retry multiplier for production sizing.

FAQ:

Is my data stored?

No. All calculations run in your browser and nothing is sent to a server or persisted remotely.

Keep sensitive text out of shared screens.

How accurate is the token estimate?

It blends characters per token and words per token, then rounds to an integer. Exact counts vary by tokenizer and language.

What units are used?

Prices are dollars per 1,000 tokens, token counts are integers, and time uses requests per day and billed days per month.

Can I model caching?

Yes. Set a cache hit percent to blend the prompt rate with a lower cached prompt rate. Savings apply only to prompt tokens.

How do I estimate tokens from a prompt?

Paste a typical prompt into the draft field. The estimator updates the prompt token input automatically unless you override it.

What does “borderline” budget mean?

When budget headroom is near zero, small changes in tokens or retries can tip into overage. Reduce volume or raise the cap.

Does it work offline?

Once loaded, calculations continue to work without a network connection because processing occurs locally.

Are prices up to date?

Presets are editable. Confirm current provider prices and adjust the rates to keep estimates aligned with your account.

Troubleshooting:

Numbers do not change: ensure a preset is selected or rates are entered.
Budget badge missing: add a positive monthly budget cap.
Cache savings not shown: set cache hit percent above zero.
Exports look empty: ensure results are visible before exporting.
Chart not visible: switch to the forecast tab after entering inputs.
Copy shows strange separators: check your locale number formatting.

If daily or monthly cost reads zero, verify that both token fields and requests per day are greater than zero.

Advanced Tips:

Tip Keep prompts short when possible and shift heavy lifting to cached system text.
Tip Track worst case completions to size budget for spikes.
Tip Apply a modest margin to cover payment fees and support overhead.
Tip Model retries separately for streaming and non‑streaming pathways.
Tip Revisit growth percent monthly to align forecast with reality.
Tip Use budget headroom as a guardrail when planning launches.

Glossary:

Prompt tokens: Input tokens sent with each request.
Completion tokens: Output tokens generated per request.
Cache hit rate: Share of prompt tokens billed at the cached price.
Retry multiplier: Average attempts per successful request.
Margin uplift: Percentage markup applied to base token costs.
Effective cost per 1K: Blended dollars per 1,000 tokens for your request mix.
Budget headroom: Remaining dollars before reaching the monthly cap.
Peak scenario: Stress case using the larger of growth plus a quarter or one point five times base volume.

LLM Usage Cost Calculator

LLM Usage Snapshot

Introduction:

Technical Details:

Units, precision, and rounding:

Validation and bounds:

I/O formats:

Networking & storage:

Performance & determinism:

Assumptions & limitations:

Edge cases & error sources:

Privacy & compliance:

Step‑by‑Step Guide:

FAQ:

Troubleshooting:

Advanced Tips:

Glossary: