Why does OpenAI Embedding return different vectors for identical text inputs?

Deterministic Behavior of Embeddings

OpenAI’s embeddings are designed to be deterministic. This means that with the same text input, model, and parameters, you should receive the same vector every time. There is no functionality that randomly selects from a limited set of embedding vectors.

Possible Sources of Observed Variations

• Floating-Point Precision: In some cases, very minor differences can appear due to floating-point arithmetic variations across different compute environments (e.g., different CPUs or hardware configurations). These differences are typically negligible and do not indicate any randomness or bug.

• Input or Parameter Differences: Ensure that the exact same text (including whitespace/punctuation) and identical parameters (such as the model name and encoding options) are used for every call. Small differences in input formatting could lead to different outputs.

• Edge Cases in the Infrastructure: If you observe significant variations beyond tiny precision differences, it’s worth verifying that the correct parameters are being used consistently. There is no known behavior where the API intentionally returns one out of a set of predefined vectors.

Conclusion

The behavior you’re observing is not by design. The OpenAI Embedding endpoint returns a deterministic vector representation for a given input. If you’re experiencing substantial inconsistencies, it may be valuable to double-check your input and parameters or contact OpenAI support with detailed logs for further investigation—it is highly unlikely to be due to inconsistent information across nodes in the server cluster.