QwenChat
Qwen: Qwen2.5 VL 32B Instruct
qwen/qwen2.5-vl-32b-instruct
128KContext Window
Supported Protocols:max_tokenstemperaturetop_pstopfrequency_penaltypresence_penaltyrepetition_penaltytop_kseedmin_presponse_format
Online
Qwen2.5-VL-32B is a multimodal vision-language model fine-tuned through reinforcement learning for enhanced mathematical reasoning, structured outputs, and visual problem-solving capabilities. It excels at visual analysis tasks, including object recognition, textual interpretation within images, and precise event localization in extended videos. Qwen2.5-VL-32B demonstrates state-of-the-art performance across multimodal benchmarks such as MMMU, MathVista, and VideoMME, while maintaining strong reasoning and clarity in text-based tasks like MMLU, mathematical problem-solving, and code generation.
Capabilities
👁 VisionText GenerationCode GenerationAnalysis & Reasoningmodels.reasoning
Technical Specs
Input Modality
Text、Image
Output Modality
Text
Arch
—
Pricing
Pay per use, no monthly feesInput Token< ¥0.001/1K Token
Output Token< ¥0.001/1K Token
Quick Start
from openai import OpenAI
client = OpenAI(
base_url="https://api.uniontoken.ai/v1",
api_key="YOUR_UNIONTOKEN_API_KEY",
)
response = client.chat.completions.create(
model="qwen/qwen2.5-vl-32b-instruct",
messages=[
{"role": "user", "content": "Hello!"}
],
)
print(response.choices[0].message.content)FAQ
Qwen
Qwen: Qwen2.5 VL 32B Instruct
qwen/qwen2.5-vl-32b-instruct
In< ¥0.001/1K
Out< ¥0.001/1K
Context Window128K
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