OpenAI Embeddings Pricing 2026
Complete pricing guide with plans, hidden costs, and cost analysis
OpenAI Embeddings uses usage-based pricing from $0.010–$0.130 per million tokens; there is no monthly subscription price for this API tier.
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Is OpenAI Embeddings a fit?
Derived from this product's own pricing and contract record — not a review.
Not a fit if
- The sticker price is your whole budget — Storage Costs for Embeddings (and 3 more).
OpenAI Embeddings Usage Pricing
| Model | Input | Output | Cached | Per |
|---|---|---|---|---|
| text-embedding-3-small | $0.020 | — | — | 1M input tokens |
| Item | Dimension | Unit | Rate |
|---|---|---|---|
| text-embedding-3-small | tokens | 1M tokens | $0.010 |
| Model | Input | Output | Cached | Per |
|---|---|---|---|---|
| text-embedding-3-large | $0.130 | — | — | 1M input tokens |
| Item | Dimension | Unit | Rate |
|---|---|---|---|
| text-embedding-3-large | tokens | 1M tokens | $0.065 |
| Model | Input | Output | Cached | Per |
|---|---|---|---|---|
| text-embedding-ada-002 | $0.100 | — | — | 1M input tokens |
| Item | Dimension | Unit | Rate |
|---|---|---|---|
| text-embedding-ada-002 | tokens | 1M tokens | $0.050 |
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OpenAI Embeddings uses usage-based pricing from $0.020 to $0.130 per million tokens as of August 2026. Usage cost depends on the selected model and generation volume.
- 7 documented hidden costs beyond list price
- G2 rating: 4.6 out of 5 from 2,734 reviews (as of Jun 2026)
How much does OpenAI Embeddings cost?
OpenAI Embeddings Pricing Overview
OpenAI Embeddings uses usage-based pricing from $0.010–$0.130 per million tokens across 6 published rates.
There are at least 7 documented hidden costs beyond OpenAI Embeddings's list price, including implementation, training, and add-on fees.
This pricing was last verified in May 30, 2026.
OpenAI Embeddings is a pay-per-use API that converts text into dense vector representations, enabling semantic search, clustering, classification, and retrieval-augmented generation (RAG). The current generation offers two models: text-embedding-3-small ($0.02/M tokens) for cost-efficient workloads and text-embedding-3-large ($0.13/M tokens) for maximum accuracy. All models support dimensionality reduction and a Batch API for 50% off on asynchronous workloads.
How OpenAI Embeddings Pricing Compares
Compare OpenAI Embeddings pricing against top alternatives in Embedding APIs.
Compare OpenAI Embeddings vs Alternatives
Before committing to OpenAI Embeddings, compare pricing with these 3 alternatives in the same category.
What Companies Actually Pay for OpenAI Embeddings
Score gap reflects platform demographics — G2 surveys verified business users; Trustpilot is open to all, skewing toward support complaints.
How OpenAI Embeddings Pricing Compares
| Software | Starting Price | Top Price |
|---|---|---|
| OpenAI Embeddings | $0.020 | $0.130 per million tokens |
| Jina Embeddings | Free | $500 per million tokens |
| Mixedbread | Free | $20/month |
| Nomic Embed | Custom | Custom |
| Voyage AI | Free | $0.18 per million tokens |
| Cohere Embed | $0.1/month | $0.12/month |
Detailed pricing comparisons:
OpenAI Embeddings Contract Terms
OpenAI Embeddings contracts do not auto-renew. Changes require Notice of non-renewal or scope reduction must be provided at least 30 days before the start of the next renewal term.. These terms are sourced from verified buyer experiences.
OpenAI Embeddings Pricing FAQ
01 How much does OpenAI Embeddings cost?
OpenAI Embeddings are priced per million input tokens. text-embedding-3-small costs $0.02/M tokens, text-embedding-3-large costs $0.13/M tokens, and the legacy text-embedding-ada-002 costs $0.10/M tokens. The Batch API offers a 50% discount on all models.
02 Does OpenAI charge for output tokens on the Embeddings API?
No. The OpenAI Embeddings API only charges for input tokens. There are no output token charges since the API returns vector representations rather than generated text.
03 What is the difference between the standard API and the Batch API for embeddings?
The standard Embeddings API processes requests synchronously and is best for real-time use cases. The Batch API accepts asynchronous jobs and returns results within 24 hours, offering a 50% cost reduction — making it ideal for large-scale offline embedding tasks like indexing document libraries.
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