How to use from the
Use from the
sentence-transformers library
from sentence_transformers import CrossEncoder

model = CrossEncoder("tencent/R3-rerank-0.6b")

query = "Which planet is known as the Red Planet?"
passages = [
	"Venus is often called Earth's twin because of its similar size and proximity.",
	"Mars, known for its reddish appearance, is often referred to as the Red Planet.",
	"Jupiter, the largest planet in our solar system, has a prominent red spot.",
	"Saturn, famous for its rings, is sometimes mistaken for the Red Planet."
]

scores = model.predict([(query, passage) for passage in passages])
print(scores)

R3-Rerank-0.6B

The latest agent skill reranking model at the 0.6B scale. R3-Reranker is the cross-encoder (rerank) stage of R3-Skill's two-stage retriever for query-conditional agent skill retrieval. It scores each (query, skill) pair jointly, paired with R3-Embedding-0.6B for recall.

Usage

from sentence_transformers import CrossEncoder

model = CrossEncoder("tencent/R3-rerank-0.6b")
query = "I need to compose music"
skills = [  # The format is "name | description | skill_md"
    "music-composer | Composes original music | Creates music for various media formats ...",
    "music-lyricist | Writes lyrics for songs | Creates lyrics for various music genres ...",
    "music-editor | Edits and mixes music tracks | Provides audio editing and mixing services ...",
]
pairs = [(query, skill) for skill in skills]
scores = model.predict(pairs)
print(scores)
# [ 0.34937477 -1.7738094  -1.6604462 ]

Citation

@inproceedings{r3skill2026,
  title  = {Skill Is Not Document: A Query-Conditional Benchmark and Two-Stage Retriever for LLM Agent Skill Routing},
  author = {Wang, Zifei and Wen, Wei and Ji, Qiang and Qiao, Ruizhi and Sun, Xing},
  year   = {2026},
  url    = {https://arxiv.org/abs/2606.03565},
}
Downloads last month
1,214
Safetensors
Model size
0.6B params
Tensor type
F32
·
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support

Model tree for tencent/R3-rerank-0.6b

Finetuned
(24)
this model
Quantizations
1 model

Paper for tencent/R3-rerank-0.6b