OpenAI Embedding Cost Calculator
Calculate the cost of text-embedding-3-small and text-embedding-3-large at your scale. From 1M to 100B tokens — see exactly what OpenAI embeddings will cost.
Embedding Cost Calculator
Enter your workload details below
Total documents to embed
Typical document length in tokens (~750 words = 1000 tokens)
Search/retrieval queries per month
Typical query length in tokens
1536 dimensions · 8,191 max tokens · MTEB 62
Total Tokens to Embed
50.0M
50,000,000 tokens
Embedding Cost
$1.00
One-time cost to embed all documents
Monthly Query Cost
$0.0500
50,000 queries/mo
Total Monthly Cost
$1.05
Embedding + query costs
Annual Cost
$12.60
Cost Per Document
$0.0000
Cheapest Alternative
Switch to text-embedding-005
Google · 768 dims · MTEB 63
Save $1.05/month ($12.60/year)
Vector database providers
Once you generate embeddings, you need somewhere to store and query them. These vector databases handle similarity search at scale.
Need help optimizing AI costs?
Digital Signet builds AI-powered systems and provides fractional CTO leadership. 20+ years shipping software.
This costs you ~$13/year
We'll identify the top 3 drivers and give you a 90-day mitigation plan.
Get a Free Exposure Teardown →Or email Oliver directly → oliver@digitalsignet.com
OpenAI Embedding Models
| Model | Price / 1M Tokens | Dimensions | Max Tokens | MTEB Score |
|---|---|---|---|---|
| text-embedding-3-smallBest value | $0.020 | 1,536 | 8,191 | 62 |
| text-embedding-3-large | $0.130 | 3,072 | 8,191 | 65 |
| text-embedding-ada-002 | $0.100 | 1,536 | 8,191 | 61 |
Dimensionality Reduction
Both text-embedding-3 models support custom dimensions. Reducing dimensions lowers vector database storage costs without dramatically impacting quality. A 256-dimension text-embedding-3-large still outperforms ada-002 at full 1,536 dimensions.
Frequently Asked Questions
How much do OpenAI embeddings cost?
OpenAI offers two embedding models: text-embedding-3-small at $0.02 per 1M tokens and text-embedding-3-large at $0.13 per 1M tokens. For context, embedding 1 million typical documents (~500 words each) with text-embedding-3-small would cost approximately $10. The legacy text-embedding-ada-002 is $0.10/1M tokens but is outperformed by text-embedding-3-small in most benchmarks.
Which OpenAI embedding model should I use?
For most use cases, text-embedding-3-small offers the best price-performance ratio at $0.02/1M tokens with a 62 MTEB score. Choose text-embedding-3-large ($0.13/1M) when you need maximum retrieval quality for complex semantic search or when your application is quality-sensitive. Both support dimensionality reduction, allowing you to reduce storage costs by lowering vector dimensions.
How does OpenAI embedding cost compare to alternatives?
text-embedding-3-small ($0.02/1M) is competitively priced with Voyage-3-lite ($0.02/1M) and Jina-v3 ($0.02/1M). For quality, Voyage-3 scores 67 MTEB vs OpenAI text-embedding-3-large's 65—at $0.06/1M vs $0.13/1M. Cohere embed-v4 at $0.10/1M is comparable to ada-002 but with better quality.
What is the token limit for OpenAI embeddings?
Both OpenAI embedding models support up to 8,191 tokens per input. Text exceeding this limit needs to be chunked. A typical 500-word document is approximately 670 tokens, well within the limit. For long documents, chunk at sentence or paragraph boundaries and embed each chunk separately.
Compare providers: Cohere embeddings · Voyage AI embeddings · Full model comparison