Jina Reranker V3Pricing
- Input Tokens: $0.05 /M tokens
- Output Tokens: $0.05 /M tokens
Input Modalities
- Text
- Vision
Providers
Performance for jina-reranker-v3
Uptime is the percentage of requests that succeeded over the past 72 hours. AIHubMix continuously monitors every provider and automatically retries with the next-best provider when one returns an error or responds too slowly; Latency is total round-trip time (lower is better); Throughput is how fast the model writes (tokens per second, higher is better).
Frequently asked questions
More models from Jina AI
See all Jina AI models →A 3.8-billion-parameter general vector model (embedding model) for state-of-the-art multilingual embeddings for edge deployment.
A 3.8-billion-parameter general vector (embedding) model providing state-of-the-art multilingual embeddings with task-specific adapters.
DeepSearch combines search, reading, and reasoning capabilities to pursue the best possible answer. It's fully compatible with OpenAI's Chat API format—just replace api.openai.com with aihubmix.com to get started. The stream will return the thinking process.
A general-purpose vector model with 3.8 billion parameters, used for multimodal and multilingual retrieval, supporting both unidirectional and multi-vector embedding outputs.
Multi-modal Embeddings Model, multilingual, 1024-dimensional, 865M parameters.
Multimodal multilingual document reranker, 10K context, 2.4B parameters, for visual document sorting.
