Qwen3-VL-Reranker-8B
by Qwen
8B cross-encoder reranker for text, image, screenshot, and video retrieval
Qwen/Qwen3-VL-Reranker-8Bmixpeek://reranker@v1/qwen3_vl_reranker_8b_v1Overview
Qwen3-VL-Reranker-8B is the larger sibling of the 2B variant, built on the Qwen3-VL-8B-Instruct vision-language backbone. As a cross-encoder, it jointly attends to query and document tokens with full cross-attention, producing a single relevance score per pair. It handles text, images, screenshots, and video frames in both query and document positions, supporting 30+ languages and inputs up to 32K tokens.
The 8B variant consistently outperforms the 2B model across most multimodal reranking benchmarks, making it the best choice when precision matters more than latency. On Mixpeek, it serves as a second-stage reranker that rescores candidates retrieved by a fast bi-encoder embedding model, dramatically improving top-K precision for cross-modal search.
Architecture
Cross-encoder architecture built on Qwen3-VL-8B-Instruct. Jointly processes query and document tokens with full bidirectional cross-attention. Outputs a scalar relevance score per pair. Supports text, images, screenshots, and video frames as both query and document inputs. 32K token context window. 30+ language support.
Mixpeek SDK Integration
import { Mixpeek } from "mixpeek";
const mx = new Mixpeek({ apiKey: "API_KEY" });
// Managed: create a collection over a bucket; Mixpeek runs this model's extractor
const collection = await mx.collections.create({
namespace_id: "my-namespace",
collection_name: "my-collection",
source: { type: "bucket", bucket_ids: ["bkt_your_bucket"] },
feature_extractor: {
feature_extractor_name: "feature_search",
version: "v1",
parameters: { model_id: "Qwen/Qwen3-VL-Embedding-8B" },
},
});Capabilities
- Cross-modal reranking across text, image, screenshot, and video
- Full cross-attention for higher precision than bi-encoder models
- 32K token context for long-document reranking
- 30+ language support including CJK
- Consistently outperforms 2B variant on most benchmarks
Use Cases on Mixpeek
Benchmarks
| Dataset | Metric | Score | Source |
|---|---|---|---|
| Multimodal reranking (MMEB-V2) | nDCG@10 | Best in class (8B) | Qwen, 2026: arxiv,2601.04720 |
| Visual document reranking | nDCG@10 | Outperforms 2B variant | Qwen, 2026: arxiv,2601.04720 |
Performance
Common Pipeline Companions
Specification
Research Paper
Qwen3-VL-Embedding and Qwen3-VL-Reranker: A Unified Framework for State-of-the-Art Multimodal Retrieval and Ranking
arxiv.orgBuild a pipeline with Qwen3-VL-Reranker-8B
Add this model to a processing pipeline alongside other extractors. Combine with retrieval stages for end-to-end search.
Run on your data