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Qwen/Qwen3-Reranker-4B

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Primitive: /score · Score · Qwen3

The Qwen3 Embedding model series is the latest proprietary model of the Qwen family, specifically designed for text embedding and ranking tasks. Building upon the dense foundational models of the Qwen3 series, it provides a comprehensive range of text embeddings and reranking models in various sizes (0.6B, 4B, and 8B).

Long context

Overview

Hardware: — drives latency, throughput & cost

Size4.0B params
Tasks /score
Licenseapache-2.0
Latency580 ms
Throughput4.4K tok/s
Cost$0.050 /1M tok

Cost is approximate — computed from list GPU prices; your actual price depends on the provider you deploy SIE with.

Scoring

Inputstext
Max sequence length32,768

Benchmarks

AskUbuntuDupQuestions

technology reranking en

Duplicate question detection from AskUbuntu

Corpus: 6,743 Queries: 360
Quality
ndcg at 10 0.6953
map at 10 0.5480
mrr at 10 0.7743
Performance L4 b1 c16
Reference →

Open source inference for agents

Open-source inference for the models behind your agents. Run it yourself, or let us run it for you.

Github 2.3K

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