BAAI: bge-m3

baai/bge-m3

Created Nov 18, 20258,192 context

$0.01/M input tokens$0/M output tokens

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.

BAAI: bge-m3

baai/bge-m3

BAAI: bge-m3

baai/bge-m3

Providers for bge-m3

OpenRouter routes requests to the best providers that are able to handle your prompt size and parameters, with fallbacks to maximize uptime.

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Uptime stats for bge-m3

Uptime stats for bge-m3 across all providers

Sample code and API for bge-m3

OpenRouter normalizes requests and responses across providers for you.

Using third-party SDKs

Providers for bge-m3

OpenRouter routes requests to the best providers that are able to handle your prompt size and parameters, with fallbacks to maximize uptime.

Performance for bge-m3

Compare different providers across OpenRouter

Apps using bge-m3

Top public apps this month

Recent activity on bge-m3

Total usage per day on OpenRouter

Uptime stats for bge-m3

Uptime stats for bge-m3 across all providers

Sample code and API for bge-m3

OpenRouter normalizes requests and responses across providers for you.

Using third-party SDKs