Text Embedding
Extract semantic embeddings from documents, transcripts and text content
Input
Enter the text you want to process
The embedding model to use. Default: text-embedding-3-large
Whether to truncate long texts. Default: true
Whether to normalize the embeddings. Default: true
Output
{
"embedding": [
0.024,
-0.015,
0.128,
0.035,
"..."
],
"dimensions": 1536,
"model": "text-embedding-3-large",
"text_chunk": "Sample text content for embedding generation",
"token_count": 128,
"truncated": false,
"normalized": true
}Ready to run Text Embedding on your data? Spin it up in Studio: no infra to host.
Run this in StudioText Embedding: common questions
- How much does the Text Embeddings (E5-Large) extractor cost?
- 1 cr/1k_tokens. Credits are billed per unit processed; see mixpeek.com/pricing for the credit rate.
- What file types does Text Embeddings (E5-Large) support?
- Text. It produces embeddings from intfloat/multilingual-e5-large-instruct.
Already have embeddings? Skip extraction: search your own vectors with MVS, from $25/mo for up to 1M vectors.
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