Tokens · Estimator

Token count estimator

Estimating tokens is the first step to estimating bills. This page ties rough counts to the pricing math the rest of the site automates.

Token calculation explanation

Start with representative samples per route, measure tokenizer outputs if possible, and track p50/p90 not just means.

Words-to-token examples

Blog paragraphs, JSON logs, and markdown tables tokenize differently—build a small library of examples for your product.

Prompt optimization tips

Ask for structured outputs, specify maximum length in user-visible terms, and avoid redundant politeness tokens in system prompts.

Token reduction techniques

Cache stable system text server-side, move boilerplate to client-only UX where appropriate, and diff prompts in CI to catch accidental bloat.

Context window explanation

As prompts approach context limits, you may see truncation or failures—plan headroom for tool returns and safety layers.

Real pricing examples

Multiply tokens by per-1K rates, then multiply by traffic. The calculator handles currency display for sharing.

From one request to a month

  • Single heavy prompt

    One-shot analysis.

    Per request
    $0.0090
    Monthly (1 req/day × 1 days)
    $0.01
  • Daily assistant habit

    Same mix, 800 times per weekday.

    Per request
    $0.0090
    Monthly (800 req/day × 22 days)
    $158.40

FAQ: Token estimation

Short answers mirror the structured data on this page for search engines and readers.

Is estimation enough for procurement?
Use it for planning; procurement needs vendor quotes and pilots.
How do streaming responses affect counts?
Billing still uses completed tokens—streaming is a UX detail.
What about partial completions?
You typically pay for emitted tokens up to the stop condition.
Can I automate counting in CI?
Yes—wrap official tokenizers in tests for critical prompts.

Use the built-in estimator panel

Copy representative prompts from staging—not production secrets.

Prefilled for this page’s scenario. Pricing loads from config/models.php and /api/pricing.

Calculator

Cost = (prompt ÷ 1000 × Pin) + (completion ÷ 1000 × Pout), then × requests.

Usage presets

Multi-model comparison

Toggle models to compare the same workload. The cheapest option is highlighted.

Monthly cost simulator

Project from average daily requests (uses tokens above).

Uses primary model rates for projections.

Token estimator

Rough heuristic: ~4 characters ≈ 1 token for Latin text (indicative only).

Estimated tokens: 0 · Cost @ primary:

API budget planner

Set a monthly cap to see how many identical requests fit (primary model).

Max requests (approx):

Prompt optimization analyzer

Collapse whitespace and tighten wording to preview savings at the primary model.

Suggested shorter form:


                    

Token delta: 0 · Est. savings / 1k calls:

Fine-tuning cost sketch

Order-of-magnitude helper: training tokens × epochs × rate + storage.

Est. training + 1 mo storage:

Team usage calculator

Multiply per-person daily volume by team size (primary model).

Team monthly (22d):

Cost per feature

Price a single product surface (e.g., one chat turn or one generated article).

Uses prompt & completion tokens from the calculator for one invocation.

Cost per use: · Monthly @ that cadence:

Share & export

Serialize inputs in the URL hash or copy a text summary.

Calculation history

Stored in your browser only (LocalStorage).