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Qwen2.5-7B-Instruct

by Alibaba

AI Model
Low Confidence

Qwen2.5-7B-Instruct is a large language model (LLM) developed by Alibaba Cloud's Qwen team. It is part of the Qwen2.5 series, which includes models of varying parameter sizes (ranging from 0.5B to 72B). The 7B-Instruct variant is specifically fine-tuned for instruction-following tasks, making it suitable for conversational AI, code generation, text summarization, and other natural language processing (NLP) applications. The model is designed to be efficient, multilingual, and capable of handling complex prompts with high accuracy. It supports extended context lengths (up to 128K tokens) and is optimized for both research and commercial use.

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Transparency Score

Weighted across four pillars · updated August 19, 2026

Overall grade
72% weighted
ABCDF
Model
—
Not yet assessed
Infrastructure
—
Not yet assessed
Openness Assessment
75%Mostly Open
10 Open
1 Partial
3 Closed
Availability
5/5 Open
Documentation
4/6 Open
Access Methods
2/3 Open
Data from EU Open Source AI Index (DOI: 10.5281/zenodo.15386042), licensed under CC-BY 4.0

Capabilities

Text Generation
Code Generation
Conversation
Summarization
Translation
Instruction Following

Vendor Information

Complete information about the vendor/provider of this AI application

AlibabaView all products →
Alibaba Cloud
Contact Information
www.alibabacloud.com/
DPO_qwenlm-intl@service.alibaba.com
+1 646-813-0131
Registered Address
No. 969 West Wen Yi Road, Hangzhou Shi, Yuhang District, China

EU AI Act Provider Information

Verification Status:
Verified
Alibaba Cloud
No. 969 West Wen Yi Road, Hangzhou Shi, Yuhang District, China
DPO_qwenlm-intl@service.alibaba.com+1 646-813-0131
Alibaba (Netherlands) B.V. Herengracht 448, 1017CA Amsterdam, the Netherlands

Potential Risks

1 considerations identified

1

Review recommended before use

These considerations are automatically identified based on publicly available information about the vendor and AI catalog data. Actual risks may vary based on your specific use case and implementation.

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Compliance & Risk

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Added: July 6, 2026
Updated: August 19, 2026

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