embedding-v1 · Baidu
Embedding-V1 is a text representation model based on Baidu's Wenxin large model technology, capable of converting text into numerical vector forms for applications such as text retrieval, information recommendation, and knowledge mining. Embedding-V1 provides an Embeddings interface that generates corresponding vector representations based on the input content. By calling this interface, you can input text into the model and obtain the corresponding vector representations for subsequent text processing and analysis.
Embedding-V1 is a text representation model based on Baidu's Wenxin large model technology, capable of converting text into numerical vector forms for applications such as text retrieval, information recommendation, and knowledge mining. Embedding-V1 provides an Embeddings interface that generates corresponding vector representations based on the input content. By calling this interface, you can input text into the model and obtain the corresponding vector representations for subsequent text processing and analysis.
On AIHubMix, Embedding V1 costs $0.068 per million input tokens.
Embedding V1 accepts text input.
Embedding V1 is available through the AIHubMix unified API. The API is OpenAI-compatible: point your OpenAI SDK at https://aihubmix.com/v1, use your AIHubMix API key, and set the model name to embedding-v1 — no other code changes needed.
Embedding V1 is developed by Baidu. AIHubMix aggregates it alongside models from other providers behind one API and one bill.
ERNIE 5.1 is the latest model in the Wenxin series, with comprehensive upgrades to its…
ERNIE 5.0 is the next-generation natively multimodal foundation model in the ERNIE…
The Ernie-image-Turbo model is an 8-step distilled version of the Ernie-image model, also…
musesteamer-air-image is a text-to-image model developed by the Baidu Search team aimed…
Qianfan-OCR-Fast is a multimodal large model specialized for OCR, trained primarily on…
Qianfan-OCR-Fast is a multimodal large model specialized for OCR, trained primarily on…
Use Embedding V1 via the AIHubMix unified API — one interface for every major LLM.