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Embedding cost calculator

Estimate corpus indexing and per-query embedding spend from tokens and an editable $/1M rate. Compare reference models and optional batch discounts.

Common public list price reference. Verify on OpenAI pricing.

Effective rate $0.020/1M. 0% = standard. Set only if your provider publishes a batch discount for embeddings.

Corpus size

Index volume ≈ 5,000,000 tokens.

Refresh + query embeds

0% = one-time index only. 10% amortizes a full re-embed about every 10 months.

Index once
$0.1
Index amortized / month
$0.01
Query embed / call
$0.0000016
Query embeds / month
$0.048
Embed API / month
$0.058
Effective $/1M
$0.020/1M
Reference preset$/1M (eff.)Index onceEmbed / month
OpenAI text-embedding-3-small$0.020/1M$0.1$0.058
OpenAI text-embedding-3-large$0.130/1M$0.65$0.377
OpenAI text-embedding-ada-002 (legacy)$0.100/1M$0.5$0.29

Compare table uses the same corpus, batch discount, refresh, and query volume. Rates are reference defaults only.

How to use this

  1. Pick a preset or Custom, then edit $/1M to match your provider.
  2. Size the corpus with docs × tokens, a total token count, or a pasted sample scaled by document count.
  3. Set re-embed share and monthly query embeds. Read index vs query lines.
  4. For full RAG (generation + retrieval), open the RAG cost calculator.

RAG cost calculator · OpenAI embedding pricing · Batch savings · Reindex cost

Related tools

RAG cost · Batch pricing

Related guides

Embedding cost calculator: estimate corpus spend · OpenAI embedding pricing: text-embedding-3 planning · Estimate embedding tokens · Batch embedding cost savings · Embedding reindex cost: how often to re-embed

Sources and references

Official documentation used for definitions, counting methods, or rate cards. Always confirm critical budgets on the provider page.

FAQ

How is embedding API pricing calculated?
Cost ≈ (tokens embedded / 1,000,000) × price per million tokens. Embeddings bill input text only. There is no separate “output token” line like chat completions.
Do embeddings charge for output tokens?
No. You pay to process the text you send. The API returns a vector; that vector is not billed as generated tokens.
Are these rates from the TokenCalculator LLM catalog?
No. Presets are editable reference defaults. Always verify on your embed provider’s pricing page or invoice before budgeting.
Does Batch API reduce embedding cost?
Some providers discount async batch embedding jobs. Set the batch discount % to match the published offer (often ~50% on OpenAI when available). Confirm current terms before you rely on it.