Qwen3-Reranker-4B β€” OpenVINO IR (INT8 weight-only, asymmetric)

This is a redistribution. For the model's intended use, instruction format, full evaluation (MTEB-R / CMTEB-R / MMTEB-R / MLDR / MTEB-Code / FollowIR), and citation, please see the upstream card: Qwen/Qwen3-Reranker-4B.

OpenVINO IR conversion of Qwen/Qwen3-Reranker-4B, weight-only quantized to INT8 asymmetric via NNCF. Intended for the OpenArc reranker engine and optimum-intel pipelines targeting Intel CPUs / iGPUs / dGPUs / NPUs.

Files

  • openvino_model.{xml,bin} β€” Qwen3 (4B) decoder, INT8 weights (~4.0 GB)
  • openvino_tokenizer.{xml,bin} / openvino_detokenizer.{xml,bin} β€” OpenVINO Tokenizers IR
  • chat_template.jinja, generation_config.json
  • Standard HF tokenizer files: tokenizer.json, tokenizer_config.json, special_tokens_map.json, vocab.json, merges.txt
  • LICENSE, NOTICE β€” Apache-2.0 with attribution to the upstream Qwen Team.

Architecture

Base model Qwen3 ForCausalLM (Qwen3-4B-Base)
Hidden size 2560
Layers 36
Attention heads / KV heads 32 / 8
Max position 40 960
Vocabulary 151 669
Source dtype bfloat16
Quantization NNCF INT8 weight-only, asymmetric

Usage with OpenArc

openarc add qwen3-4b-reranker \
  --model-path /path/to/Qwen3-Reranker-4B-int8-ov \
  --model-type rerank \
  --engine optimum \
  --device GPU

openarc serve
# POST /v1/rerank  {"model": "qwen3-4b-reranker", "query": "...", "documents": [...]}

Conversion notes

The standard CLI route currently fails silently for this model on optimum-intel @ HEAD:

optimum-cli export openvino --weight-format int8 \
  --model Qwen/Qwen3-Reranker-4B ./out
# exits 0; openvino_model.xml is 0 bytes, openvino_model.bin is a ~13 MB stub

The Python API path produces a usable model:

from optimum.intel import OVModelForCausalLM, OVWeightQuantizationConfig

quant = OVWeightQuantizationConfig(bits=8, sym=False)
m = OVModelForCausalLM.from_pretrained(
    "Qwen/Qwen3-Reranker-4B",
    export=True,
    quantization_config=quant,
    trust_remote_code=True,
)
m.save_pretrained("./out")

Tokenizer / detokenizer IR generated separately via openvino_tokenizers.convert_tokenizer(..., with_detokenizer=True).

A more detailed walkthrough lives in OpenArc/docs/openvino_qwen3.md.

License

Apache-2.0, inherited from Qwen/Qwen3-Reranker-4B. See LICENSE and NOTICE in this repo.

Citation

From the upstream model card:

@article{qwen3embedding,
  title={Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models},
  author={Zhang, Yanzhao and Li, Mingxin and Long, Dingkun and Zhang, Xin and Lin, Huan and Yang, Baosong and Xie, Pengjun and Yang, An and Liu, Dayiheng and Lin, Junyang and Huang, Fei and Zhou, Jingren},
  journal={arXiv preprint arXiv:2506.05176},
  year={2025}
}
Downloads last month
43
Inference Providers NEW
This model isn't deployed by any Inference Provider. πŸ™‹ Ask for provider support

Model tree for kread/Qwen3-Reranker-4B-int8-ov

Quantized
(50)
this model

Paper for kread/Qwen3-Reranker-4B-int8-ov