Independent AI pricing research

Pricing Research

Flagship source-backed resources for AI pricing and unit economics.

LLM API Cost Guide: Input, Output, Cached and Batch Tokens

A source-backed guide to the token billing variables that change a production LLM API bill.

OpenAI vs Anthropic vs Gemini vs DeepSeek: Realistic Workload Cost Comparison

Compare model cost under realistic workloads rather than only price-per-million-token tables.

AI Chatbot Cost Model for 1,000, 10,000 and 100,000 Conversations

Estimate monthly chatbot costs using transparent conversation scenarios and official pricing sources.

RAG Application Cost Guide: Embeddings, Retrieval and Generation

A practical cost model for RAG apps that separates ingestion, retrieval, reranking and answer generation.

AI SaaS Unit Economics: Inference Cost, Gross Margin and Break-Even

A practical framework for pricing AI SaaS plans when API usage changes gross margin.

Prompt Caching Economics: When It Saves Money and When It Does Not

Calculate when cached input pricing changes LLM economics and when it is only a small discount.

AI Coding Assistant Cost Model: Cost per Developer and Team

Estimate coding assistant API cost by developer usage, prompt size, output patches and retry overhead.

AI Image Generation Cost Comparison: Cost per Usable Image

Estimate AI image cost from usable images, retries and official unit pricing where available.

AI Video Generation Budget Guide: Cost per Finished Minute

Plan AI video budgets from seconds generated, failed generations, revisions and finished output length.

AI API Budget Template: Forecast Monthly Usage and Avoid Billing Surprises

A practical template for forecasting AI API usage by users, calls, tokens, retries and fixed costs.

How to choose the right pricing research guide

Tokencost keeps this section focused on pages that solve different planning problems. If you are building an AI product, start with the LLM or SaaS calculator because API calls usually become the largest variable cost. If you are making creator content, use the music, video and voice calculators to model attempts, regeneration and usable-output rate. If you are comparing providers, use the pricing research pages because they explain the assumptions behind each estimate.

A useful cost page should do more than show one number. It should explain the formula, list the source, warn about missing variables and show related decisions. That is why weak duplicated pages are removed from the sitemap and stronger guides are linked here instead. This helps users find fewer but better resources, and it helps search engines understand the site as a practical AI pricing reference rather than a collection of keyword-only pages.

Recommended workflow

  1. Use a calculator with your own monthly volume and token or media assumptions.
  2. Open the related research page to understand the billing logic and caveats.
  3. Check the sources page before using a figure in a business plan.
  4. Save the result as a range rather than a single exact number, because provider prices and usage patterns change.

When to revisit estimates

Recalculate after a model launch, a provider price cut, a major prompt change, a new customer segment, a move from prototype to production, or any change in user behavior that increases average calls per session. Small prompt and retry changes can become large monthly changes once traffic grows.

Related calculators and research

Why this pricing research section exists

Tokencost is built for people who need to make a practical money decision before they have perfect data. A developer might be deciding whether a chatbot can fit inside a $19/month subscription. A creator might be checking whether a short-video workflow can survive the cost of regenerated clips, voiceovers and music. A small SaaS team might need to know whether an AI feature should be free, metered, routed to a cheaper model or limited behind a paid plan.

Those decisions are difficult because AI pricing is fragmented. LLMs bill input, output and sometimes cached input. Video and music tools may use subscriptions, credits, region-specific plans or private enterprise rates. Voice tools may charge by characters, minutes or seats. Some providers publish clear API rates while others hide the practical unit cost behind plan limits. Tokencost keeps calculators flexible by allowing manual input when verified pricing is not available.

What makes a useful estimate

A useful estimate includes the whole workflow. For LLM products, that means request count, prompt size, output size, retries, cache ratio, hidden reasoning or agent loops and monthly active use. For creator workflows, it means finished output, rejected attempts, editing tools, revenue assumptions and break-even views. For SaaS businesses, it means revenue, payment fees, infrastructure, marketing, team cost and churn. A single provider price rarely answers the real business question.

How to read Tokencost pages

Use every result as a planning range. The calculators show how cost moves when assumptions change, while the research pages explain why those assumptions matter. The sources and methodology pages show where factual pricing came from and where users should verify. If a provider publishes a newer source, the site can be corrected through the contact email. This structure is intentionally conservative because publishing a transparent caveat is more valuable than showing a precise-looking but unverifiable number.

Editorial promise

Tokencost avoids copyrighted logos, keeps ads separate from calculator logic, removes thin duplicate pages from the sitemap and keeps legal/trust pages accessible without login. The goal is to be a durable reference for AI pricing, token cost calculation, creator cost planning and AI SaaS economics, not a temporary collection of search-keyword pages.

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