BAAI: bge-base-en-v1.5

baai/bge-base-en-v1.5

Created Nov 18, 2025512 context

$0.005/M input tokens$0/M output tokens

The bge-base-en-v1.5 embedding model converts English sentences and paragraphs into 768-dimensional dense vectors, delivering efficient, high-quality semantic embeddings optimized for retrieval, semantic search, and document-matching workflows. This version (v1.5) features improved similarity-score distribution and stronger retrieval performance out of the box.

BAAI: bge-base-en-v1.5

baai/bge-base-en-v1.5

Created Nov 18, 2025512 context

$0.005/M input tokens$0/M output tokens

Providers for bge-base-en-v1.5

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-base-en-v1.5

Compare different providers across OpenRouter

Apps using bge-base-en-v1.5

Top public apps this month

Recent activity on bge-base-en-v1.5

Total usage per day on OpenRouter

Prompt

1.53M

Completion

Prompt tokens measure input size. Reasoning tokens show internal thinking before a response. Completion tokens reflect total output length.

Uptime stats for bge-base-en-v1.5

Uptime stats for bge-base-en-v1.5 across all providers

Sample code and API for bge-base-en-v1.5

OpenRouter normalizes requests and responses across providers for you.

OpenRouter provides an OpenAI-compatible embeddings API that you can call directly, or using the OpenAI SDK.

In the examples below, the OpenRouter-specific headers are optional. Setting them allows your app to appear on the OpenRouter leaderboards.

Using third-party SDKs

For information about using third-party SDKs and frameworks with OpenRouter, please see our frameworks documentation.

See the Request docs for all possible fields, and Parameters for explanations of specific sampling parameters.

bge-base-en-v1.5 - API, Providers, Stats | OpenRouter