Alibaba Cloud
Qwen Embedding / Rerank
Qwen Cloud's model-selection docs list text-embedding-v4, tongyi-embedding-vision-plus and qwen3-rerank for search, RAG and retrieval accuracy improvement.
Quick answers
At a glance
- Overview
- Qwen Cloud's retrieval model line for text embeddings, multimodal embeddings and reranking.
- Best fit
- Teams building RAG, semantic search or ranking pipelines around Chinese and multilingual content.
- Trust
- 1/1 sources verified · 2026-05-17
- Coverage
- 96/100 · backfill: sources
Editorial verdict
Best for
Teams building RAG, semantic search or ranking pipelines around Chinese and multilingual content.
Avoid if
Avoid choosing it only from model specs; run corpus-level retrieval checks first.
Why it matters
Qwen Cloud includes retrieval infrastructure models, so Qwen coverage should include more than chat and generation.
Pricing
Pay-as-you-go retrieval API billing varies by model
Payment
Qwen Cloud billing, Pay-as-you-go API billing
Commercial use
Commercial use should follow the current product, API, model license and billing terms.
Privacy
Review prompt, file, media upload, retention and training-use terms before sensitive workloads.
Use-case fit
RAG retrieval
StrongUse embeddings and rerankers to build retrieval and answer pipelines.
Multimodal search
MediumUse multimodal embedding when text and image search need one retrieval layer.
Global user checklist
This profile is stale enough to recheck before commercial use.
Pros
- - Text, vision embedding and rerank models are documented
- - Useful for RAG systems on the same Qwen Cloud account
Cons
- - Retrieval quality should be benchmarked on your own corpus
Decision paths
qwen
deepseek
zhipu-glm
Sources
docs · en · verified 2026-05-17
Lists text-embedding-v4, tongyi-embedding-vision-plus and qwen3-rerank.