Measure the cost of the workflow, not one button press.

Lewdora offers 30-day passes for a defined access window and token allowance. Unused pass tokens expire when that window ends. Top-up packs add tokens that remain in the account until used. The live Pricing page shows current products, amounts, and checkout paths.

New accounts receive the configured signup bonus shown on the site. At public launch, that bonus is 30 tokens. A separate one-time Discord community reward grants 100 tokens after membership verification, subject to one claim per Lewdora account and Discord account.

The selected model and compatible options determine the request cost. Reference modes, dimensions, or added processing can affect the total when supported. Read the displayed cost after configuring the complete request, not before choosing the options.

Model availability and pricing can change. Use articles to understand the calculation and the live generator for the current amount. Do not build a long project budget from an old screenshot.

Reserve tokens for a small baseline set before chasing a final image. Several fixed-input outputs show variation and help you judge whether the model and prompt fit the task. One sample can hide a weak setup or make a good setup look bad.

Set a limit for each stage: baseline, prompt revision, reference test, and final batch. Stop a stage when repeated outputs fail the same criterion. Change the model, source, or composition instead of spending the rest of the budget on the same request.

Add all tokens spent on the sample and divide by the number of outputs that meet the written acceptance criteria. If a 40-token test produces two usable images, the accepted-result cost is 20 tokens. Include failed attempts because the workflow paid for them.

Use the same quality bar when comparing models. A cheaper model can cost more per accepted result if it needs many retries. A higher request cost can save tokens when it follows the prompt and required controls with fewer attempts.

A pass suits a concentrated month of regular creation when you expect to use its allowance inside the 30-day window. A top-up suits irregular work or extra capacity because purchased top-up tokens do not expire. Compare current pack and pass values on the live page.

Do not buy from a forecast built on selected successes. Run the free or existing balance through a representative workflow, record accepted-result cost, then estimate the number of finished images you expect to make.

Record date, model, request cost, attempt count, accepted outputs, and the reason for rejection. The ledger can fit in a note or spreadsheet. Its purpose is to reveal where tokens go, not to create administrative work.

Review the largest waste category. Prompt confusion calls for clearer structure. Anatomy failures may call for a simpler pose. Identity drift may call for character reference. The cost record becomes useful when it changes the next workflow choice.

Estimate the number of projects, accepted images per project, and attempts needed per accepted image. Multiply those values by the observed request cost for the models and controls you use. Add a revision allowance for difficult poses, recurring characters, or image-to-image experiments. This forecast is more useful than dividing a token balance by the cheapest visible request.

Use a low, expected, and high case. The low case assumes stable prompts and few retries. The expected case uses your session log. The high case covers a demanding project or model change. Choose a pass only when its 30-day allowance fits the actual schedule; choose a non-expiring top-up when usage is irregular.

Convert every option to cost per usable token and estimated cost per accepted image. Include renewal period, expiration, and any balance rules. A lower token price can still be a poor fit when most of the allowance expires unused. A smaller top-up can be cheaper for occasional work even when its unit price is higher.

Separate signup and community rewards from recurring capacity. The 30-token launch signup bonus and one-time 100-token Discord reward help evaluate the workflow, but they do not repeat every month. Base an ongoing budget on paid capacity and treat promotional balances as initial testing room.

Check cost again whenever you change the model, dimensions, output count, or references. Set a session ceiling before starting. Stop when the next correction is not clearly defined, because unfocused retries consume tokens without producing evidence. Review the outputs and notes before purchasing more capacity.

Keep checkout receipts and read the current Terms for payment, access period, and refund conditions. Public prices and product configurations can change, so the live Pricing page and checkout are authoritative at purchase time. Do not rely on a screenshot or article that lacks a checked date.

Exploration tests prompts, models, ratios, and references. Production repeats an approved setup with controlled variants. Give each phase its own token budget. If experimentation consumes the production reserve, stop and choose from the evidence already collected instead of purchasing reactively.

Archive the approved prompt packet before production begins. Include the active model, cost, dimensions, references, and acceptance criteria. A stable packet reduces accidental settings changes and makes unexpected token use easier to diagnose.