Activefastllm Open Source

Qwen2 1.5B

by Alibaba· Released June 2024· Cutoff March 2024

Qwen2 1.5B is a small, efficient language model from Alibaba's Qwen2 series, designed for lightweight deployment and fast inference. It balances performance and resource usage, making it suitable for edge devices and applications with limited compute. As the smallest model in the Qwen2 family, it offers strong multilingual capabilities and supports a 32K token context window.

Official Site API Docs 🤗 Hugging Face 📄 Research Paper

Input cost

Free (open source)

Output cost

Free (open source)

Context window

32K tokens

Max output

8192 tokens

Modalities

text

Parameters

1.5B

License

Apache-2.0

Capabilities

Text GenerationCode GenerationMultilingual SupportFunction CallingStreamingJSON Mode

Best For

Lightweight, fast inference tasks on resource-constrained devices or applications requiring low latency.

Strengths

Very small model size (1.5B parameters) enabling deployment on edge devices
Fast inference speed suitable for real-time applications
Strong multilingual performance for its size
Supports 32K context window, longer than many small models

Limitations

Lower accuracy and reasoning capability compared to larger models
Limited to text-only input and output
May struggle with complex tasks requiring deep understanding
Smaller knowledge base due to fewer parameters

Use Cases

On-device chatbots and virtual assistants

Real-time text generation and autocomplete

Simple code generation and completion

Multilingual translation and summarization

Educational tools and tutoring

IoT and embedded system applications

Lightweight data extraction and classification

Improvements Over Previous Model

Context window increased from 8K (Qwen1.5-1.8B) to 32K tokens
Improved multilingual capabilities with better performance on non-English languages
Enhanced code generation and understanding
Better instruction following and alignment
Reduced model size from 1.8B to 1.5B while maintaining or improving performance
Supports function calling and JSON mode, new in Qwen2 series

Back to all models

Improvements Over Previous Model

Context window increased from 8K (Qwen1.5-1.8B) to 32K tokens

Improved multilingual capabilities with better performance on non-English languages

Enhanced code generation and understanding

Better instruction following and alignment

Reduced model size from 1.8B to 1.5B while maintaining or improving performance

Supports function calling and JSON mode, new in Qwen2 series