ReadyGPU TEE

Qwen: Qwen3 Embedding 8B

Model IDqwen/qwen3-embedding-8b

The Qwen3 Embedding model series is the latest proprietary model of the Qwen family, specifically designed for text embedding and ranking tasks. This series inherits the exceptional multilingual capabilities, long-text understanding, and reasoning skills of its foundational model. The Qwen3 Embedding series represents significant advancements in multiple text embedding and ranking tasks, including text retrieval, code retrieval, text classification, text clustering, and bitext mining.

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input

$0.01/M

output

Free/M

context

33K

created

Jan 14, 2026

Supported API shape

input

text · embeddings

output

embeddings

tools

Not listed

json mode

Not listed

Verification

receipt

x-receipt-id

attestation

gateway report

session

attested upstream

provider

Phala

Provider

Phala

GPU TEE

input

$0.01/M

output

Free/M

context

33K

$ pip install openai

1from openai import OpenAI
2import os
3
4MODEL = "qwen/qwen3-embedding-8b"
5
6client = OpenAI(
7    base_url="https://inference.phala.com/v1",
8    api_key=os.environ["PHALA_API_KEY"],
9)
10
11response = client.embeddings.create(
12    model=MODEL,
13    input="Phala keeps inference data inside a confidential runtime.",
14)
15
16print(response.data[0].embedding[:8])

$ npm install openai

1import OpenAI from "openai"
2
3const MODEL = "qwen/qwen3-embedding-8b"
4
5const openai = new OpenAI({
6  baseURL: "https://inference.phala.com/v1",
7  apiKey: process.env.PHALA_API_KEY,
8})
9
10const response = await openai.embeddings.create({
11  model: MODEL,
12  input: "Phala keeps inference data inside a confidential runtime.",
13})
14
15console.log(response.data[0].embedding.slice(0, 8))

1curl https://inference.phala.com/v1/embeddings \
2  -H "Authorization: Bearer $PHALA_API_KEY" \
3  -H "Content-Type: application/json" \
4  -d '{
5    "model": "qwen/qwen3-embedding-8b",
6    "input": "Phala keeps inference data inside a confidential runtime."
7  }'

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