qwen3-embedding-4b

by Qwen

The Qwen3 Embedding model series is the latest proprietary model family from Qwen, specifically designed for text embedding and ranking tasks. Based on the dense base models of the Qwen3 series, it offers comprehensive text embedding and reranking models in various sizes (0.6B, 4B, and 8B). This series inherits the excellent multilingual capabilities, long-text understanding, and reasoning skills of its base models. The Qwen3 Embedding series demonstrates significant advancements in various text embedding and ranking tasks, including text retrieval, code retrieval, text classification, text clustering, and bilingual text mining.

API Pricing

Input$0.07 / 1M tokens
Output$0.07 / 1M tokens

Specifications

Modalitiestext

FAQ

What is qwen3-embedding-4b?

The Qwen3 Embedding model series is the latest proprietary model family from Qwen, specifically designed for text embedding and ranking tasks. Based on the dense base models of the Qwen3 series, it offers comprehensive text embedding and reranking models in various sizes (0.6B, 4B, and 8B). This series inherits the excellent multilingual capabilities, long-text understanding, and reasoning skills of its base models. The Qwen3 Embedding series demonstrates significant advancements in various text embedding and ranking tasks, including text retrieval, code retrieval, text classification, text clustering, and bilingual text mining.

How much does qwen3-embedding-4b cost?

On AIHubMix, qwen3-embedding-4b costs $0.07 per million input tokens and $0.07 per million output tokens.

What modalities does qwen3-embedding-4b support?

qwen3-embedding-4b accepts text input.

How do I call qwen3-embedding-4b via API?

qwen3-embedding-4b is available through the AIHubMix unified API. The API is OpenAI-compatible: point your OpenAI SDK at https://aihubmix.com/v1, use your AIHubMix API key, and set the model name to qwen3-embedding-4b — no other code changes needed.

Who develops qwen3-embedding-4b?

qwen3-embedding-4b is developed by Qwen. AIHubMix aggregates it alongside models from other providers behind one API and one bill.

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Use qwen3-embedding-4b via the AIHubMix unified API — one interface for every major LLM.