Qwen2.5-72B-Instruct-128K
About Qwen2.5-72B-Instruct-128K
Qwen2.5-72B-Instruct is one of the latest large language models series released by Alibaba Cloud. This 72B model demonstrates significant improvements in areas such as coding and mathematics. It supports a context length of up to 128K tokens. The model also offers multilingual support, covering over 29 languages, including Chinese, English, and others. It has shown notable enhancements in instruction following, understanding structured data, and generating structured outputs, particularly in JSON format.
Discover how Qwen2.5-72B-Instruct-128K's extensive context, advanced coding, and structured output capabilities solve complex, real-world challenges.
Advanced Code Generation
Generate production-ready code, refactor legacy systems, and implement complex algorithms across diverse languages with deep contextual understanding.
Use Case Example:
"Developed a complete microservice in Go, including API endpoints, database interactions, and unit tests, by analyzing existing system architecture and requirements from a 50-page specification."
Deep Document Analysis
Process and extract insights from extensive legal contracts, research papers, or technical manuals, generating structured summaries and answering complex queries.
Use Case Example:
"Summarized a 100-page legal brief into key arguments and potential liabilities, presented as a JSON object, enabling rapid review by legal teams."
Multilingual Data Processing
Translate, localize, and process structured data across 29+ languages, ensuring accurate context preservation and consistent output formats like JSON.
Use Case Example:
"Translated a product catalog from English to Japanese and German, automatically converting product specifications into a localized JSON format for e-commerce platforms."
Advanced Mathematical Reasoning
Solve intricate mathematical problems, generate proofs, and derive formulas, providing step-by-step explanations for scientific and engineering challenges.
Use Case Example:
"Derived a novel optimization algorithm for a supply chain network, including the mathematical formulation and Python implementation, based on a detailed problem description."
Structured API & Config Generation
Automatically generate API specifications (e.g., OpenAPI), system configurations, or data schemas in precise JSON/YAML formats from natural language requirements.
Use Case Example:
"Created a complete OpenAPI 3.0 specification for a new REST API, including authentication, endpoints, and data models, from a high-level design document and example requests."
Metadata
Specification
State
Deprecated
Architecture
Transformer Decoder
Calibrated
No
Mixture of Experts
No
Total Parameters
72B
Activated Parameters
72B
Reasoning
No
Precision
FP8
Context length
131K
Max Tokens
4K
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