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Qwen3-VL Reranker (multimodal)

Scores relevance across modalities, text against images and back

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Overview

Qwen3-VL-Reranker-8B is the reranking half of the Qwen3-VL retrieval suite, built on Qwen3-VL-8B-Instruct. It takes a query and document pair where either side may be text, an image, a screenshot, video or a mixture, and returns a relevance score. Qwen intends it as the second stage after Qwen3-VL-Embedding recall. It covers 30+ languages with a 32K context.

Strengths

  • Reranks across modalities, not only text
  • Designed to pair with qwen3-vl-embedding
  • 30+ languages

Use cases

  • Refining multimodal knowledge-base search
  • Text-to-image and image-to-text relevance

Good to know

8B parameters against bge-reranker's ~568M makes it far costlier per candidate. Worth it only when the documents really are multimodal.

API access

One OpenAI-compatible API for every model in the catalog, plus the CLI and the function SDK inside workflows. Sign up free, add a card for $5 in credits, and these requests work:

qwen3-vl-reranker · curl
# Reranker models are called through the
# platform APIs and workflows; list what is deployed:
curl https://gateway.graphn.ai/v1/models \
  -H "Authorization: Bearer $GRAPHN_API_KEY"