Qwen3-Reranker-0.6B
About Qwen3-Reranker-0.6B
Qwen3-Reranker-0.6B is a text reranking model from the Qwen3 series. It is specifically designed to refine the results from initial retrieval systems by re-ordering documents based on their relevance to a given query. With 0.6 billion parameters and a context length of 32k, this model leverages the strong multilingual (supporting over 100 languages), long-text understanding, and reasoning capabilities of its Qwen3 foundation. Evaluation results show that Qwen3-Reranker-0.6B achieves strong performance across various text retrieval benchmarks, including MTEB-R, CMTEB-R, and MLDR
Available Serverless
Run queries immediately, pay only for usage
$
0.01
Per 1M Tokens
Metadata
Specification
State
Available
Architecture
Calibrated
No
Mixture of Experts
No
Total Parameters
1
Activated Parameters
0.6B
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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