● Qwen · embedding

Qwen3 Embedding 8B

SAMPLE: Qwen's 8B embedding model for long-document retrieval.

Get API key All models

Input / 1M tokens$0.02

Context32K

Example: 1M input tokens = $0.02

Call Qwen3 Embedding 8B

OpenAI-compatible. Use any OpenAI SDK with the Keyra base URL and your key.

curl

curl https://api.keyra.example/v1/embeddings \
  -H "Authorization: Bearer $KEYRA_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model": "qwen3-embedding-8b", "input": "Hello, world"}'

Python · openai SDK

import os
from openai import OpenAI

client = OpenAI(base_url="https://api.keyra.example/v1", api_key=os.environ["KEYRA_API_KEY"])

result = client.embeddings.create(model="qwen3-embedding-8b", input="Hello, world")
print(len(result.data[0].embedding))

Related models

Model	Creator	Type	Context	Input / 1M	Output / 1M
BGE-M3	BAAI	embedding	8K	$0.01	—