Qwen2.5-14B-Instruct
About Qwen2.5-14B-Instruct
Qwen2.5-14B-Instruct is one of the latest large language model series released by Alibaba Cloud. This 14B model demonstrates significant improvements in areas such as coding and mathematics. The model also offers multi-language support, covering over 29 languages, including Chinese and English. It has shown notable advancements in instruction following, understanding structured data, and generating structured outputs, particularly in JSON format.
Explore how Qwen2.5-14B-Instruct's advanced capabilities in coding, math, and structured data processing can solve complex, real-world problems.
Advanced Code Generation
Generate complex code, refactor existing logic, and implement algorithms across languages, adhering to best practices and architectural patterns.
Use Case Example:
"Generated a secure REST API endpoint in Python (FastAPI) from natural language specs, including validation and error handling, cutting development time."
Structured Data Extraction
Extract entities and relationships from unstructured text or tables, transforming them into precise JSON or database-ready formats.
Use Case Example:
"Processed 100+ legal contracts, extracting key clauses, parties, and dates into standardized JSON for automated contract management."
Multilingual Content AI
Generate and localize marketing content, technical docs, or support responses across 29+ languages, maintaining nuance and brand voice.
Use Case Example:
"Localized a product's user manual from English to Japanese and German, ensuring technical accuracy and cultural appropriateness for global markets."
Agentic Workflow Automation
Design and execute multi-step AI agents interacting with tools and APIs, making decisions and generating structured action plans.
Use Case Example:
"Automated a support agent to triage tickets, query CRM for history, and generate personalized responses or escalate via structured API calls."
Mathematical Problem Solver
Solve intricate mathematical problems, verify proofs, and derive complex formulas across scientific and engineering disciplines.
Use Case Example:
"Verified a novel cryptographic algorithm's correctness by logically deducing properties and identifying vulnerabilities, saving weeks of manual review."
Metadata
Specification
State
Deprecated
Architecture
Causal Language Model
Calibrated
Yes
Mixture of Experts
Yes
Total Parameters
14B
Activated Parameters
14.7B
Reasoning
No
Precision
FP8
Context length
33K
Max Tokens
4K
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