BAAI: bge-m3
Baai
The bge-m3 embedding model encodes sentences, paragraphs, and long documents into a 1024-dimensional dense vector space, delivering high-quality semantic embeddings optimized for multilingual retrieval, semantic search, and large-context applications.
Pricing
Source-reported prices are shown in their native units. No missing fee is estimated.
Input
$0.010
USD / 1M input tokens
Output
Free
USD / 1M output tokens
Capabilities
A check means the source explicitly lists support; a dash means the source did not publish a value.
Text input Supported
Text output Not listed
Vision Not listed
Tools N/A
Reasoning N/A
Structured outputs N/A
Audio Not listed
Image generation Not listed
Embeddings Supported
Alternatives
Suggestions use deterministic rules: overlapping modalities, a context window within 2×, and shared source-reported signals. No AI-generated recommendations.
Similar models
OpenAI: Text Embedding 3 Small
openai/text-embedding-3-small
Input
$0.020
Intelligence
N/A
Similar category, context, price or shared benchmark signals.
OpenAI: Text Embedding 3 Small (batch)
openai/text-embedding-3-small:batch
Input
$0.010
Intelligence
N/A
Similar category, context, price or shared benchmark signals.
BAAI: bge-base-en-v1.5
baai/bge-base-en-v1.5
Input
$0.0050
Intelligence
N/A
Similar category, context, price or shared benchmark signals.
BAAI: bge-large-en-v1.5
baai/bge-large-en-v1.5
Input
$0.010
Intelligence
N/A
Similar category, context, price or shared benchmark signals.