qwen3-embedding-8b
Qwen embedding model for semantic search, retrieval, and RAG pipelines.
qwen
40K context
Context rank
#8 of 20
40K token window
Benchmarks
Independent benchmarks for this model have not been published by Artificial Analysis yet. Scores will appear here once they are released.
Best for
Where this model earns its keep.
High-volume general tasks
The numbers
Pricing is live from our platform. Prices per 1M tokens, zero data retention on every request.
| Input price | $0.02 |
| Cache read price | - |
| Output price | - |
| Context window | 40K tokens |
Quick start
OpenAI-compatible. Switch in one line.
# pip install openai
client = OpenAI(base_url="https://api.tensorx.ai/v1", api_key="tsx-...")
r = client.chat.completions.create(
model="qwen/qwen3-embedding-8b",
messages=[{"role": "user", "content": "Hello"}],
)
client = OpenAI(base_url="https://api.tensorx.ai/v1", api_key="tsx-...")
r = client.chat.completions.create(
model="qwen/qwen3-embedding-8b",
messages=[{"role": "user", "content": "Hello"}],
)
Benchmark data from the Artificial Analysis Intelligence Index v4.1, measured independently. Pricing live from the TensorX platform. All inference on EU-sovereign infrastructure with zero data retention.