Qwen2-0.5B|1.5B|7B|57B-A14B-MoE|72B

Overview

Qwen2 is a family of open-source large language models released by the Qwen team, available in five sizes from 0.5B to 72B parameters. It includes both pretrained and instruction-tuned variants, supports up to 128K token context windows, and covers 29 languages. The models show strong benchmark performance, especially in coding and mathematics.

Best for

Best for
Developers needing a flexible, open-source LLM family with strong multilingual and coding capabilities

Use cases

• Deploying a small, efficient model for on-device or edge inference
• Building multilingual chatbots or assistants with extended context handling
• Fine-tuning for specialized coding or math reasoning tasks

Notes

Qwen2 is a family of open-source large language models released by the Qwen team, available in five sizes from 0.5B to 72B parameters. It includes both pretrained and instruction-tuned variants, supports up to 128K token context windows, and covers 29 languages. The models show strong benchmark performance, especially in coding and mathematics.

Use cases

• Deploying a small, efficient model for on-device or edge inference
• Building multilingual chatbots or assistants with extended context handling
• Fine-tuning for specialized coding or math reasoning tasks

Pros

• Multiple size options allow matching model to compute budget
• Strong coding and math performance relative to parameter count
• Long 128K context window supported on instruction-tuned variants

Cons

• Community-driven release may have less formal support than vendor-backed models
• Larger models (72B) require significant hardware for inference
• Benchmark gains may not translate equally to all downstream tasks

Indexed from awesome-llm and enriched against its public facts.