ReadyGPU TEE

Qwen: Qwen3.5 397B A17B

Model IDqwen/qwen3.5-397b-a17b

The Qwen3.5 series 397B-A17B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. It delivers state-of-the-art performance comparable to leading-edge models across a wide range of tasks, including language understanding, logical reasoning, code generation, agent-based tasks, image understanding, video understanding, and graphical user interface (GUI) interactions. With its robust code-generation and agent capabilities, the model exhibits strong generalization across diverse agent.

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input

$0.55/M

output

$3.50/M

context

262K

created

Feb 28, 2026

Supported API shape

input

text · image · video

output

text

tools

Supported

json mode

Supported

Verification

receipt

x-receipt-id

attestation

gateway report

session

attested upstream

provider

Phala

Provider

Phala

GPU TEE

input

$0.55/M

output

$3.50/M

context

262K

$ pip install openai

1from openai import OpenAI
2import os
3
4MODEL = "qwen/qwen3.5-397b-a17b"
5
6client = OpenAI(
7    base_url="https://inference.phala.com/v1",
8    api_key=os.environ["PHALA_API_KEY"],
9)
10
11response = client.chat.completions.create(
12    model=MODEL,
13    messages=[{"role": "user", "content": "Run this privately."}],
14)
15
16print(response.id)
17print(response.choices[0].message.content)

$ npm install openai

1import OpenAI from "openai"
2
3const MODEL = "qwen/qwen3.5-397b-a17b"
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.chat.completions.create({
11  model: MODEL,
12  messages: [{ role: "user", content: "Run this privately." }],
13})
14
15console.log(response.id)
16console.log(response.choices[0].message.content)

1curl https://inference.phala.com/v1/chat/completions \
2  -H "Authorization: Bearer $PHALA_API_KEY" \
3  -H "Content-Type: application/json" \
4  -d '{
5    "model": "qwen/qwen3.5-397b-a17b",
6    "messages": [
7      { "role": "user", "content": "Run this privately." }
8    ]
9  }'

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