Model card
Qwen2.5 72B is a high-performance, open-weights model from Alibaba designed to bridge the gap between proprietary frontier models and local deployment. For developers, the primary value proposition lies in its sophisticated bilingual capabilities, offering exceptional proficiency in both Chinese and English. Unlike many models that struggle with cross-lingual nuance, Qwen2.5 maintains high reasoning density and coding accuracy across both languages. At 72B parameters, it strikes a pragmatic balance: it is large enough to handle complex instruction following, mathematical reasoning, and structured data extraction, yet optimized enough to run on high-end consumer hardware or localized enterprise clusters. Because it is released under the Apache 2.0 license, it provides a permissive foundation for commercial integration, fine-tuning for domain-specific tasks, and building private RAG pipelines without the restrictive overhead of closed-source APIs.
Model files and versions
Download this model
We recommend using the ModelScope CLI or SDK. Install ModelScope first, then choose a full snapshot, single file, SDK or Git LFS workflow.
Qwen/Qwen2.5-72B-InstructInstall the CLI and SDK dependency before downloading.
pip install modelscopeDownload the complete weights, configuration and model card.
modelscope download --model Qwen/Qwen2.5-72B-InstructREADME.md is used as an example; replace it with another repository file when needed.
modelscope download --model Qwen/Qwen2.5-72B-Instruct README.md --local_dir ./dirUseful in Python projects and automation scripts.
from modelscope import snapshot_download
model_dir = snapshot_download('Qwen/Qwen2.5-72B-Instruct')Make sure Git LFS is installed correctly.
git lfs install
git clone https://www.modelscope.cn/Qwen/Qwen2.5-72B-Instruct.gitFetch the repository structure first, then pull large files when needed.
GIT_LFS_SKIP_SMUDGE=1 git clone https://www.modelscope.cn/Qwen/Qwen2.5-72B-Instruct.gitHow to use
- 01Step 1
Read the model card and source information.
- 02Step 2
Start with a small, non-sensitive evaluation.
- 03Step 3
Review quality, licensing and usage limits.
- 04Step 4
Adopt it only after validation.
Discussions
Use this space to keep checking source information, usage experience and maintenance status.
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