text-embedding-v4 · Qwen
This is the Tongyi Laboratory's multilingual unified text vector model trained based on Qwen3, which significantly improves performance in text retrieval, clustering, and classification compared to version V3; it achieves a 15% to 40% improvement on evaluation tasks such as MTEB multilingual, Chinese-English, and code retrieval; supports user-defined vector dimensions ranging from 64 to 2048.
This is the Tongyi Laboratory's multilingual unified text vector model trained based on Qwen3, which significantly improves performance in text retrieval, clustering, and classification compared to version V3; it achieves a 15% to 40% improvement on evaluation tasks such as MTEB multilingual, Chinese-English, and code retrieval; supports user-defined vector dimensions ranging from 64 to 2048.
On AIHubMix, Text Embedding V4 costs $0.08 per million input tokens and $0.08 per million output tokens.
Text Embedding V4 accepts text input.
Text Embedding V4 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 text-embedding-v4 — no other code changes needed.
Text Embedding V4 is developed by Qwen. AIHubMix aggregates it alongside models from other providers behind one API and one bill.
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Use Text Embedding V4 via the AIHubMix unified API — one interface for every major LLM.