TensorX / tensorx/qwen3-embedding-8b-tensorx

Qwen3 Embedding 8B - access through LLMTR

Qwen3 Embedding 8B is a multilingual embedding model that produces a 4096-dimension vector per input. Its 40,960-token context window is enough to vectorize long documents in one piece. The higher dimensionality takes more room in a vector database. Pricing is on input tokens only.

Same model, other providers: GreenPT (EU)

Technical specifications

Canonical ID	`tensorx/qwen3-embedding-8b-tensorx`
Provider	TensorX
Context window	40,960 tokens
Operations	EMBEDDINGS
Modalities	text, embedding

Pricing

An 8% platform margin applies to credit top-ups; model usage prices are not separately marked up.

Operation	Metric	Unit	Price
EMBEDDINGS	INPUT_TEXT	PER_1M_TOKENS	$0.020000

Example usage

With existing OpenAI SDK flows, change only the base URL and model identifier.

curl https://llmtr.com/v1/chat/completions   -H "Authorization: Bearer llmtr-your_key"   -H "Content-Type: application/json"   -d '{"model":"tensorx/qwen3-embedding-8b-tensorx","messages":[{"role":"user","content":"Hello"}]}'

Guides about this model

TensorX API: EU-Hosted Models Through One API - LLMTR offers 12 TensorX chat models and 1 embedding model as tensorx/<model>-tensorx ids at https://llmtr.com/v1. A call needs the TensorX data-transfer consent on the account; the same key and balance also work for every other model.
EU-Hosted Embedding API for a GDPR-Minded RAG - A RAG pipeline can run its embedding and answer steps on TensorX rows through LLMTR. Embedding 10 million tokens costs $0.20, and one data-transfer consent covers both steps. The GDPR assessment stays with you.

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