by Jina AI
Model optimized for code and document search, 768-dimensional, 137M parameters.
Model optimized for code and document search, 768-dimensional, 137M parameters.
On AIHubMix, jina-embeddings-v2-base-code costs $0.05 per million input tokens and $0.05 per million output tokens.
jina-embeddings-v2-base-code accepts text input.
jina-embeddings-v2-base-code 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 jina-embeddings-v2-base-code — no other code changes needed.
jina-embeddings-v2-base-code is developed by Jina AI. AIHubMix aggregates it alongside models from other providers behind one API and one bill.
jina-reranker-v3.5 is a 0.6B-parameter multilingual listwise document reranker and a…
A 3.8-billion-parameter general vector model (embedding model) for state-of-the-art…
A 3.8-billion-parameter general vector (embedding) model providing state-of-the-art…
DeepSearch combines search, reading, and reasoning capabilities to pursue the best…
A general-purpose vector model with 3.8 billion parameters, used for multimodal and…
Multimodal multilingual document reranker, 131K context, 0.6B parameters, for visual…
Use jina-embeddings-v2-base-code via the AIHubMix unified API — one interface for every major LLM.