Model detail
text-embedding-3-small
text-embedding-3-small is OpenAI's improved, more performant version of the ada embedding model. Embeddings are a numerical representation of text that can be used to measure the relatedness between two pieces of text. Embeddings are useful for search, clustering, recommendations, anomaly detection, and classification tasks.
Model specs
- Context length
- 8.191K
- Max output
- –
- I/O modalities
- Text
- Released
- 2025-10
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API endpoints
One MixRoute gateway, OpenAI-compatible
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OpenAI-compatible
/v1/chat/completionsPOST
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Pricing
Flat rate, unit: /1M Tokens
Input
$0.0200 /1M Tokens
Completion
$0.0200 /1M Tokens
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Selection summary
Quickly judge whether it fits your workload
What is this model good for?
Efficient embedding model for cost-sensitive workloads
Use text-embedding-3-small for embedding tasks where cost and speed are more important than maximum accuracy. It is an improved version of the ada embedding model.
What should you check before using it?
Compare accuracy vs text-embedding-3-large
text-embedding-3-small trades some accuracy for lower cost and faster performance. Test your specific use case to confirm the accuracy meets your requirements.
Why use it through MixRoute?
Use the compatible endpoint with stable model ID
Use the confirmed compatible endpoint with model ID text-embedding-3-small through MixRoute.
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Token cost estimator
Live estimate from this page's pricing, not an actual bill
This model has no cache-read price; caching is not counted
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FAQ
text-embedding-3-small is OpenAI’s improved, more performant version of the ada embedding model. It provides efficient text embeddings for measuring relatedness between pieces of text.
One endpoint, a testable decision
Test this model and alternate routes with the same request format
Start from a real workload, then let quality, total cost, and failure conditions decide whether to send production traffic.