Qwen3-Reranker-4B
About Qwen3-Reranker-4B
Qwen3-Reranker-4B is a powerful text reranking model from the Qwen3 series, featuring 4 billion parameters. It is engineered to significantly improve the relevance of search results by re-ordering an initial list of documents based on a query. This model inherits the core strengths of its Qwen3 foundation, including exceptional understanding of long-text (up to 32k context length) and robust capabilities across more than 100 languages. According to benchmarks, the Qwen3-Reranker-4B model demonstrates superior performance in various text and code retrieval evaluations
Available Serverless
Run queries immediately, pay only for usage
$
0.02
Per 1M Tokens
Metadata
Specification
State
Available
Architecture
Calibrated
Yes
Mixture of Experts
No
Total Parameters
4
Activated Parameters
4B
Reasoning
No
Precision
FP8
Context length
33K
Max Tokens
Supported Functionality
Serverless
Supported
Serverless LoRA
Not supported
Fine-tuning
Not supported
Embeddings
Not supported
Rerankers
Supported
Support image input
Not supported
JSON Mode
Not supported
Structured Outputs
Not supported
Tools
Not supported
Fim Completion
Not supported
Chat Prefix Completion
Not supported
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Input:
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Model FAQs: Usage, Deployment
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