Model reference · open weights
Qwen3-Embedding-G128 is an open-weight embedding model from boboliu, 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
Qwen3-Embedding-4B-W4A16-G128 GPTQ Quantized Qwen/Qwen3-Embedding-4B with THUIR/T2Ranking and m-a-p/COIG-CQIA for calibration set. What's the benefit? VRAM Usage: 17430M - 11000M (w/o FA2). What's the cost? ~0.72% lost in C-MTEB. Evaluation performed with official code. How to use it? pip install compressed-tensors optimum and auto-gptq / gptqmodel, then goto the official usage guide.
Summarised from the published model card. Read the full card on the HuggingFace links below.
Specifications
| Maker | boboliu |
|---|---|
| Type | Embedding models |
| Parameters (lead) | 4.1B |
| Context | 40k tokens |
| Variants | 1 |
| Runs with | sentence-transformers |
| Based on | Qwen/Qwen3-Embedding-4B |
| Released | 2025-06-06 |
| Popularity | 542k downloads / month |
| Likes | 5 |
| 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 |
|---|---|---|---|---|---|
| Qwen3-Embedding-4B-W4A16-G128 | 4.1B | BF16 | ~9.3 GB | ✓ | Weights ↗ |
Using it via the API
Once AxForge deploys qwen3-embedding-g128 for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (qwen3-embedding-g128 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-embedding-g128","input":"text to embed"}'
Details
Tags
Licence
Open weights under apache-2.0 — commercial use is permitted. Deploy it on AxForge EU hardware on request. Read the licence ↗
Explore