Qwen1.5-72B

Powerful, Transparent & Scalable

What is Qwen1.5-72B?

Qwen1.5-72B is the flagship model in Alibaba Cloud’s Qwen1.5 series—a next-generation large language model with 72 billion parameters. Built on a dense transformer architecture, it is optimized for complex reasoning, natural language understanding, code generation, and advanced multilingual tasks.

Designed for both enterprise and research applications, Qwen1.5-72B is released as an open-weight model under a permissive license, allowing full access to weights and configuration for customization, fine-tuning, and deployment at scale.

Key Features of Qwen1.5-72B

Massive 72B Transformer Architecture

Delivers exceptional performance in language understanding, logical reasoning, and knowledge synthesis.

Truly Open & Commercial-Friendly

Released with full weight access and licensing for unrestricted research and enterprise integration.

Instruction-Tuned Intelligence

Specially fine-tuned for real-world instruction-following, summarization, dialogue, and Q&A.

Multilingual Mastery

Supports 50+ languages including English, Chinese, Arabic, Hindi, French, and more—built for global applications.

Elite Code Generation

Trained on diverse, high-quality coding datasets. Excels at code completion, debugging, and synthesis across multiple languages.

Enterprise-Grade Scalability

Optimized for inference across distributed cloud systems, on-prem clusters, and high-throughput applications.

Use Cases of Qwen1.5-72B

Build enterprise-scale chatbots, knowledge bases, and intelligent customer support powered by 72B-level reasoning.

Enhance IDEs, code editors, and developer platforms with state-of-the-art code generation and suggestion engines.

Power multi-language document processing, real-time translation, and global content moderation tools.

Accelerate academic and industrial NLP research with full access to training weights and model internals.

Use Qwen1.5-72B as a foundation for domain-specific fine-tuning in healthcare, legal, finance, and other verticals.

Qwen1.5-72B

vs

Other LLMs

Feature	GPT-4	LLaMA 2 70B	Claude 3 Opus	Qwen1.5-72B
Model Type	Dense Transformer	Dense Transformer	Mixture of Experts	Dense Transformer
Inference Cost	High	Moderate	High	Moderate
Total Parameters	~175B	70B	~200B (MoE)	72B
Multilingual Support	Advanced	Moderate	Advanced	Advanced+
Code Generation	Strong	Moderate	Strong	Advanced+
Licensing	Closed	Open	Closed	Open-Weight
Best Use Case	General + Coding	Research & Apps	General AI	Complex NLP + Code