Model reference · open weights
R3-embedding is an open-weight embedding model from tencent, 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.
About
R3-Embedding-0.6B The latest agent skill retrieval model at the 0.6B scale. R3-Embedding is the bi-encoder (recall) stage of R3-Skill's two-stage retriever for query-conditional agent skill retrieval. It embeds a query and every skill independently and ranks candidates by cosine similarity, paired with R3-Rerank-0.6B for reranking. - 📄 Paper: Skill Is Not Document: A Query-Conditional Benchmark and Two-Stage Retriever for LLM Agent Skill Routing - 💻 Code: Tencent/R3-Skill Usage Citation
Summarised from the published model card. Read the full card on the HuggingFace links below.
Specifications
| Maker | tencent |
|---|---|
| Type | Embedding models |
| Parameters (lead) | 596M |
| Variants | 1 |
| Runs with | sentence-transformers |
| Based on | Qwen/Qwen3-Embedding-0.6B |
| Released | 2026-07-08 |
| Popularity | 628 downloads / month |
| Likes | 27 |
| Licence | Open weights |
How it works
Variants
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.
| Variant | Params | Precision | VRAM | Fits 16 GB | Weights |
|---|---|---|---|---|---|
| R3-embedding-0.6b | 596M | BF16 | ~1.4 GB | ✓ | Weights ↗ |
Using it via the API
Once AxForge deploys r3-embedding for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (r3-embedding 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":"r3-embedding","input":"text to embed"}'
Licence
Open weights under apache-2.0 — commercial use is permitted. Deploy it on AxForge EU hardware on request. Read the licence ↗
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