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ebasKing/Qwen3-Reranker-8B-GGUF-llama_cpp
Qwen3-Reranker-8B-GGUF-llama_cpp is a text ranking model from ebasKing. Use it for the text ranking task on the model card, and read the license before you ship it in a product. It is set up for gguf. The card lists the license as apache-2.0.
Working GGUF of Qwen/Qwen3-Reranker-8B for llama.cpp. Converted 2025-03-09 with the official converthftogguf.py.
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.gguf56.2 GB · 100%
From the Hugging Face model README
Working GGUF of Qwen/Qwen3-Reranker-8B for llama.cpp. Converted 2025-03-09 with the official convert_hf_to_gguf.py.
| File | Quant | Size | Description |
|---|---|---|---|
Qwen3-Reranker-8B-F16.gguf | F16 | 14.10 GB | Full precision, no quality loss |
Qwen3-Reranker-8B-Q8_0.gguf | Q8_0 | 7.49 GB | 8-bit quantized, half the size |
Yes. Most community GGUFs of Qwen3-Reranker produce garbage scores (4.5e-23) because they're missing reranker-specific tensors. See llama.cpp #16407. This one works:
Doc 0 (relevant): relevance_score = 0.99XX
Doc 1 (irrelevant): relevance_score = 0.00XX
llama-server -m Qwen3-Reranker-8B-f16.gguf --reranking --pooling rank --embedding --port 8081
curl http://localhost:8081/v1/rerank \
-H "Content-Type: application/json" \
-d '{
"query": "employment termination notice period",
"documents": [
"The Labour Code requires 30 calendar days written notice.",
"Corporate tax rates for small enterprises."
]
}'
Use /v1/rerank, not /v1/embeddings. The embeddings endpoint returns zeros for reranker models.
The official convert_hf_to_gguf.py detects Qwen3-Reranker and does things naive converters skip:
cls.output.weight (the yes/no classifier) from lm_headpooling_type = RANK metadataclassifier.output_labels = ["yes", "no"]Without these, llama-server has nothing to compute scores from.
[Qwen3-Reranker-8B-f16]
model = /path/to/Qwen3-Reranker-8B-f16.gguf
reranking = true
pooling = rank
embedding = true
ctx-size = 32768
For a full multi-model setup guide (embedding + reranking + chat on one server), see the llama-server Qwen3 guide.
pip install huggingface_hub gguf torch safetensors sentencepiece
python -c "from huggingface_hub import snapshot_download; snapshot_download('Qwen/Qwen3-Reranker-8B', local_dir='Qwen3-Reranker-8B-src')"
python convert_hf_to_gguf.py --outtype f16 --outfile Qwen3-Reranker-8B-f16.gguf Qwen3-Reranker-8B-src/
Apache 2.0 — same as the original model.