BGE M3
Free Playground & API · $5 to Start
1024-dimensional vectors. Up to 8192 tokens per input, 245K total. Multilingual support. Ideal for RAG, semantic search, and similarity matching.
Capabilities
Model ID: Bge_M3_FP16
What you can do with BGE M3.
Text-to-Embedding
Convert text into vector embeddings for semantic search, recommendations, and RAG applications.
Technical Specifications
Max Input
8,192 tokens
Max Total
245,760 tokens
How to Use in deAPI
Integrate BGE M3 into your app with a single API call.
https://api.deapi.ai/api/v1/client/txt2embedding
curl -X 'POST' \
'https://api.deapi.ai/api/v1/client/txt2embedding' \
-H 'accept: application/json' \
-H 'Content-Type: application/json' \
-H 'Authorization: Bearer YOUR_API_KEY' \
-d '{
"model": "Bge_M3_FP16",
"texts": [
"Hello world",
"Semantic search example"
]
}'
{
"model": "Bge_M3_FP16",
"texts": [
"Hello world",
"Semantic search example"
]
}
Tip: The API returns a request_id.
Use webhooks (recommended) or poll
GET /request-status/{'{'}request_id{'}'} for results.
Need an API key?
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Open Playground or API
Call the REST API directly
Generate & Ship
Use in your app, product, or workflow
Frequently Asked Questions
Try BGE M3 for Free
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