Model reference · open weights

Qwen3-Reranker-seq-cls

Qwen3-Reranker-seq-cls is an open-weight embedding model from tomaarsen, listed in the AxForge catalogue. AxForge can bring it up on EU-owned hardware for you on request — with the licence handled where one is required.

Embeddings tomaarsen 2 variants 186k downloads/mo
Request this model on EU hardware All served models Not on the shared API today — deployed on request.

About

What Qwen3-Reranker-seq-cls is

Qwen3-Reranker-0.6B [!NOTE] This is a copy of the Qwen3-Reranker-0.6B model, part of the Qwen3 Reranker series, modified as a sequence classification model instead. See Updated Usage for details on how to use it, or Original Usage for the original usage. See this discussion for details on the conversion approach. Highlights 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). This series inherits the exceptional multilingual capabilities, long-text understanding, and reasoning skills of its foundational model. The Qwen3 Embedding series represents significant advancements in multiple text embedding and ranking tasks, including text retrieval, code retrieval, text classification, text clustering, and bitext mining. Exceptional Versatility: The embedding model has achieved state-of-the-art performance across a wide range of downstream application evaluations. The 8B size embedding model ranks No.1 in the MTEB multilingual leaderboard (as of June 5, 2025, score 70.58), while the reranking model excels in various text retrieval scenarios. Comprehensive Flexibility: The Qwen3 Embedding series offers a full spectrum of sizes (from 0.6B to 8B) for both embedding and reranking models, catering to diverse use cases that prioritize efficiency and effectiveness. Developers can seamlessly combine these two modules. Additionally, the embedding model allows for flexible vector definitions across all dimensions, and both embedding and reranking models support user-defined instructions to enhance performance for specific tasks, languages, or scenarios. Multilingual Capability: The Qwen3 Embedding series offer support for over 100 languages, thanks to the multilingual capabilites of Qwen3 models. This includes various programming languages, and provides robust multilingual, cross-lingual, and code retrieval capabilities. Model Overview Qwen3-Reranker-0.6B has the following features: - Model Type: Text Reranking - Su

Summarised from the published model card. Read the full card on the HuggingFace links below.

Specifications

What it is

Makertomaarsen
TypeEmbedding models
Parameters (lead)596M
Context40k tokens
Variants2
Runs withsentence-transformers
Based onQwen/Qwen3-0.6B-Base
Released2025-06-06
Popularity186k downloads / month
Likes39
LicenceOpen weights

How it works

How embedding models work

Your textsentence / documentEncodermaps meaningVectorlist of numbersAn embedding model turns text into a vector, so similar meanings sit close together — the basis of search and RAG.

Variants

Sizes & precisions

Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.

VariantParamsPrecisionVRAMFits 16 GBWeights
Qwen3-Reranker-0.6B-seq-cls596MBF16~1.4 GBWeights ↗
Qwen3-Reranker-8B-seq-cls7.6BBF16~17.4 GBWeights ↗

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys qwen3-reranker-seq-cls for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (qwen3-reranker-seq-cls below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/embeddings \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"qwen3-reranker-seq-cls","input":"text to embed"}'

Details

Languages, data & research

Tags

sentence-transformers safetensors qwen3 text-classification transformers text-ranking

Papers

Licence

Open weights

Open weights under apache-2.0 — commercial use is permitted. Deploy it on AxForge EU hardware on request. Read the licence ↗

Sources

Weights & code

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