text-embedding-3-large pricing
text-embedding-3-large from OpenAI — embeddings API at $0.130 per 1M tokens, 3072 dimensions, 8,191-token max input. Highest-quality OpenAI embedding; 3072 dims (shortenable).
text-embedding-3-largeBilled per input token · prices USD, last verified 2026-06-27.
text-embedding-3-large cost calculator
Estimate the bill for embedding a corpus. Enter total tokens (≈ words × 1.3).
Re-embedding on model changes repeats this cost. Compare all models on the embeddings pricing page.
text-embedding-3-large vs other embedding models
Cost per 1M tokens, cheapest first — text-embedding-3-large highlighted.
| Model | Provider | Per 1M | Dimensions | Max input |
|---|---|---|---|---|
| BGE-M3open | BAAI | $0.010 | 1024 | 8K |
| text-embedding-3-small | OpenAI | $0.020 | 1536 | 8K |
| Jina Embeddings v3 | Jina AI | $0.020 | 1024 | 8K |
| Voyage-3.5 | Voyage AI | $0.060 | 1024 | 32K |
| Mistral Embed | Mistral | $0.100 | 1024 | 8K |
| Cohere Embed v4 | Cohere | $0.120 | 1536 | 128K |
| text-embedding-3-large | OpenAI | $0.130 | 3072 | 8K |
| Gemini Embedding | $0.150 | 3072 | 2K |
How text-embedding-3-large pricing works
text-embedding-3-large bills per input token at $0.130 per million — there are no output tokens, since the response is a fixed 3072-dimension vector. Cost scales only with how much text you embed, so the levers are corpus size and how often you re-embed. The batch endpoint halves the price to $0.065 per 1M for non-urgent jobs.
Higher dimensions improve retrieval marginally but increase vector-database storage and query cost proportionally — many models (including this one where noted) support shortening dimensions to trade a little accuracy for big storage savings.
text-embedding-3-large pricing FAQ
How much does text-embedding-3-large cost?
text-embedding-3-large costs $0.130 per 1M input tokens ($0.065 on the batch endpoint). Embedding 1 million typical documents of ~500 tokens each (500M tokens) would cost about $65.00.
How many dimensions does text-embedding-3-large output?
text-embedding-3-large returns 3072-dimension vectors, and supports Matryoshka shortening to smaller dimensions to cut storage. Its max input is 8,191 tokens per request.
Is there a cheaper embedding model than text-embedding-3-large?
Yes — BGE-M3 (BAAI) is cheaper at $0.010 per 1M tokens. The cheapest tracked here is BGE-M3 at $0.010.