ReadyGPU TEE

Qwen: Qwen3 VL 30B A3B Instruct

Model IDqwen/qwen3-vl-30b-a3b-instructModel weights

Qwen3-VL-30B-A3B-Instruct is a multimodal model that unifies strong text generation with visual understanding for images and videos. Its Instruct variant optimizes instruction-following for general multimodal tasks. It excels in perception of real-world/synthetic categories, 2D/3D spatial grounding, and long-form visual comprehension, achieving competitive multimodal benchmark results. For agentic use, it handles multi-image multi-turn instructions, video timeline alignments, GUI automation, and visual coding from sketches to debugged UI. Text performance matches flagship Qwen3 models, suiting document AI, OCR, UI assistance, spatial tasks, and agent research.

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input

$0.20/M

output

$0.70/M

cache read

$0.03/M

context

128K

added

Nov 28, 2025

Supported API shape

input

text · image

output

text

max output tokens

32,768

tools

Supported

json mode

Supported

Verification

Available evidence. Use a verified client to authenticate the quote, connection, and receipt.

Verify private inference

receipt

signed receipt + hashes

attestation

gateway report

session

attested upstream

serving provider

read from receipt session

Provider

Phala

GPU TEE

input

$0.20/M

output

$0.70/M

cache read

$0.03/M

context

128K

Performance comparison

Last 72h · UTC

$ pip install openai

1from openai import OpenAI
2import os
3
4MODEL = "qwen/qwen3-vl-30b-a3b-instruct"
5
6client = OpenAI(
7    base_url="https://inference.phala.com/v1",
8    api_key=os.environ["PHALA_AI_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-vl-30b-a3b-instruct"
4
5const openai = new OpenAI({
6  baseURL: "https://inference.phala.com/v1",
7  apiKey: process.env.PHALA_AI_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_AI_API_KEY" \
3  -H "Content-Type: application/json" \
4  -d '{
5    "model": "qwen/qwen3-vl-30b-a3b-instruct",
6    "messages": [
7      { "role": "user", "content": "Run this privately." }
8    ]
9  }'

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