Comprehensive side-by-side LLM comparison
Qwen2.5-VL 32B Instruct leads with 2.0% higher average benchmark score. Qwen2.5-VL 32B Instruct supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
Alibaba / Qwen
Qwen2.5-14B-Instruct is a 14-billion-parameter language model from Alibaba released in September 2024 within the Qwen2.5 family, occupying the mid-tier of the series between efficiency-focused small models and the high-capability 72B flagship. Trained on 18 trillion tokens with emphasis on instruction alignment, code understanding, and multilingual reasoning, it offers a strong performance-to-compute ratio for developers who need more capability than 7B but cannot serve 32B or larger models. The model supports 128K context windows and structured output generation out of the box.
Alibaba / Qwen
Qwen2.5-VL-32B-Instruct is a 32-billion-parameter vision-language model from Alibaba, extending the Qwen2.5 architecture with multimodal capabilities for understanding images, documents, charts, and video frames alongside text. The model was designed for tasks requiring deep visual reasoning — such as document parsing, table extraction, and spatial understanding — with performance that made it a practical choice for document intelligence and visual data analysis workflows. As an open-weight model, it became a widely adopted foundation for fine-tuning domain-specific multimodal applications.
5 months newer
Qwen2.5 14B Instruct
Alibaba / Qwen
2024-09-19
Qwen2.5-VL 32B Instruct
Alibaba / Qwen
2025-03-01
Average performance across 1 common benchmarks
Qwen2.5 14B Instruct
Qwen2.5-VL 32B Instruct
Performance comparison across key benchmark categories
Qwen2.5 14B Instruct
Qwen2.5-VL 32B Instruct
Available providers and their performance metrics
Qwen2.5 14B Instruct
Qwen2.5-VL 32B Instruct
Qwen2.5 14B Instruct
Qwen2.5-VL 32B Instruct