Qwen3 VL 30B A3B Instruct is an open-weight mixture-of-experts vision-language model that balances capability with efficiency through roughly 3B active parameters from a 30B base. With a 131K context window, it handles long documents, video understanding, and visual agent tasks. The model targets visual agent functions for PC and mobile GUI automation, code generation from images and video, OCR in 32 languages, and spatial perception for object positioning and viewpoint understanding. It fuses text and vision for multimodal comprehension alongside STEM reasoning. It is designed for cost-efficient deployment of visual agents, document processing pipelines, and multimodal RAG where lower latency and a smaller memory footprint matter relative to the 235B variant. The open-weight release supports local deployment, fine-tuning for specialized visual domains, and integration into automation loops.
Qwen3 VL 30B A3B Instruct runs on 2 different routes through the Opper gateway. Compare residency, ZDR, and training posture at a glance β full data-handling detail per route below.
Training posture across routes: No training on prompts by default.
Each route hosting Qwen3 VL 30B A3B Instruct has its own privacy posture, residency, and GDPR terms. Postures are maintained by Opper with a last-verification timestamp.
Zero data retention is available via Opper Enterprise contract. No training on customer data. US; unknown.
Zero data retention is available via Opper Enterprise contract. No training on customer data. US; SCCs; DPA available.
Independent benchmark scores β composite indices for reasoning, coding, and math, plus individual eval scores where available.
Call Qwen3 VL 30B A3B Instruct through the Opper gateway with one API key. Let your coding agent set it up, or call it directly β Opper is drop-in compatible with the OpenAI, Anthropic, and Google AI SDKs.
Copy this and paste it into your coding agent β Claude Code, Cursor, Codex, and more β and it'll wire up Opper for you.
import OpenAI from "openai";const client = new OpenAI({apiKey: process.env.OPPER_API_KEY,baseURL: "https://api.opper.ai/v3/compat",});const completion = await client.chat.completions.create({model: "deepinfra/Qwen/Qwen3-VL-30B-A3B-Instruct",messages: [{ role: "user", content: "Hello" }],});console.log(completion.choices[0].message.content);
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