{"head":{"title":"Embedding Cost Calculator by Model | OceanLab","description":"Turn a document set in pages, words or tokens into embedding cost per model, one-off and monthly. Prices from official pages, each with a checked date.","canonical":"https://oceanlab.in/tools/embedding-cost-calculator"},"tool":{"slug":"embedding-cost-calculator","path":"/tools/embedding-cost-calculator","name":"Embedding cost","h1":"Embedding cost calculator","lede":"Enter the size of your documents and compare what embedding them costs on each model, now and each month.","category":"ai","categoryTitle":"AI cost and planning","method":["Tokens = pages × words per page × tokens per word (or the words or tokens you enter). Chunk overlap is added, because overlapping text is embedded twice.","One-off cost = embedded tokens × the model's price per 1M tokens, after any free allowance. Monthly cost re-embeds the share of the corpus that changes.","Only models with a price read on the vendor's own pricing page are listed. OpenAI, Cohere and Mistral embeddings are left out because no price was found on their pricing pages on the checked date."],"sources":[{"label":"Google embedding pricing","url":"https://ai.google.dev/gemini-api/docs/pricing","checkedAt":"2026-10-25"},{"label":"Voyage AI embedding pricing","url":"https://docs.voyageai.com/docs/pricing","checkedAt":"2026-10-25"}],"faq":[{"question":"Which embedding models are included?","answer":"Only models whose price was read on the vendor's official page on the checked date. Models without a published price there are left out rather than guessed."},{"question":"Why add chunk overlap?","answer":"Chunks usually share some text with their neighbour, and that text is embedded twice. The overlap share is an editable assumption."},{"question":"Are free tiers included?","answer":"Optionally. A free allowance is applied to the first embedding run, not to batch jobs or monthly re-embedding."},{"question":"Where do the prices come from?","answer":"Each price is read from the provider's official pricing page and shows the date it was checked. Prices that could not be verified are left out, or start at 0 for you to fill in."}],"updatedAt":"2026-10-25"},"related":[{"href":"/tools/rag-cost-calculator","label":"RAG cost","detail":"Work out the one-off and monthly cost of a retrieval-augmented (RAG) app, and what each question costs."},{"href":"/tools/token-counter","label":"Token counter","detail":"Paste any text to estimate how many tokens it is, and what it would cost to send to each model."},{"href":"/tools/llm-api-cost-calculator","label":"LLM API cost","detail":"Enter your monthly tokens and the input, cached and output mix, and compare what each model would cost."}],"studies":[{"meta":{"slug":"kaganek","industry":"ai","projectType":"RAG knowledge assistant","country":"pl","tags":["ai","enterprise"],"compliances":["GDPR","EU AI Act","ISO/IEC 27001","ISO/IEC 42001","Polish labour law"],"cover":{"src":"/case-studies/kaganek/01-home.png","width":1440,"height":1000}},"text":{"en":{"title":"Kaganek - RAG Knowledge Assistant with Citations and Permissions Intact","description":"Designed and built a clickable internal knowledge assistant for a Kraków consulting engineering firm: staff ask in Polish or English and get answers built only from the firm's own SharePoint, Confluence, Google Drive and file share documents, with every claim linked to its source passage and an honest \"I don't know\" when the sources are weak.","category":"AI Agents & Automation / Knowledge Assistant","client":"Modrzew Engineering"}}},{"meta":{"slug":"lukturis","industry":"internal","projectType":"AI knowledge search","country":"lv","tags":["ai","enterprise"],"compliances":["GDPR","Latvian Personal Data Processing Law","EU AI Act","DORA","ISO/IEC 27001"],"cover":{"src":"/case-studies/lukturis/01-home.png","width":1440,"height":1000}},"text":{"en":{"title":"Lukturis - Permission-Aware Enterprise Search Across Seven Internal Tools","description":"Designed and built a clickable enterprise search product for a 600-person Riga software company: one search box over Google Drive, Notion, Jira, Slack, GitHub, HubSpot and the HR policy site, with every result filtered by what the person can already open in the source tool, extractive answer cards that always link to the source, review nudges for content owners and an admin view of connector health and index freshness.","category":"Internal Tools / Enterprise Search","client":"Vējzeme Software"}}},{"meta":{"slug":"chaffline","industry":"legal","projectType":"E-discovery search","country":"us","tags":["enterprise","ai"],"compliances":["FRCP 26 and 34","FRE 502","FRCP 5.2","HIPAA","Illinois BIPA","Illinois PIPA","CCPA","ABA Model Rules","Sedona Principles"],"cover":{"src":"/case-studies/chaffline/01-home.png","width":1440,"height":1000}},"text":{"en":{"title":"Chaffline - E-Discovery Search and Document Review Platform","description":"Designed and built a clickable e-discovery platform for a Chicago litigation support firm that hosts and reviews data for US law firms: a dashboard across every matter, each matter's path from collection to production, Boolean, proximity and concept search, and a review pane where contract reviewers code documents with the privilege basis recorded at the moment of the call.","category":"LegalTech / E-Discovery","client":"Kedzie Row Discovery Services"}}}],"more":[{"href":"/case-studies/industry/ai","label":"AI agents & automation case studies","detail":"Every OceanLab product build in AI agents & automation."},{"href":"/case-studies/industry/data","label":"Data & analytics case studies","detail":"Every OceanLab product build in Data & analytics."},{"href":"/case-studies","label":"All case studies","detail":"Every OceanLab product build."},{"href":"/ai-automation","label":"AI automation","detail":"AI built into real business workflows, with people in charge."}],"today":"2026-10-25"}