Qwen3 VL 32B Instruct

qwen3-vl-32b-instruct

Qwen3-VL-32B-Instruct is a 32B-parameter multimodal model built for precise reasoning across text, images, and video. It combines strong perception with advanced language understanding for tasks like spatial reasoning, document and scene analysis, and long video comprehension. With robust OCR in 32 languages and enhanced fusion architectures, it’s optimized for agent-style interaction and visual tool use, delivering state-of-the-art results on complex real-world multimodal tasks.

Context: 262.1K tokens
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Pricing

Input$0.35 / 1M

Output$1.10 / 1M

Cache Write (5m)$0.35 / 1M

Cache Write (1h)$0.35 / 1M

Cache Read$0.35 / 1M

Web Search$0 / 1M

Quick Start

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Endpoint

python

from openai import OpenAI client = OpenAI(    api_key="YOUR_API_KEY",    base_url="https://api.apertis.ai/v1") response = client.chat.completions.create(    model="qwen3-vl-32b-instruct",    messages=[        {"role": "user", "content": "Hello!"}    ],    max_tokens=1024,    temperature=0.7) print(response.choices[0].message.content) # Optional: Enable context compression to reduce token usage# response = client.chat.completions.create(#     model="qwen3-vl-32b-instruct",#     messages=[{"role": "user", "content": "Hello!"}],#     extra_body={"compression": {"enabled": True, "model": "gpt-4.1-mini"}}# )

Supported Parameters

API docs

Common7 params

modelmessagesmax_tokenstemperaturetop_pstreamtools

Extended4 params

reasoning_effortstream_optionsthinkingextra_body

Cursor IDE Model IDs

Use these namespaced identifiers in Cursor IDE to avoid conflicts with built-in models.

qwen3-vl-32b-instruct

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