Comprehensive side-by-side LLM comparison
Both models show comparable benchmark performance. Qwen2.5-VL 32B Instruct supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
Alibaba / Qwen
Qwen2.5-Coder-7B-Instruct is a 7-billion-parameter code-specialized model from Alibaba, released in November 2024 as part of the Qwen2.5-Coder family, trained on a curated corpus spanning 92 programming languages with emphasis on code generation, debugging, and fill-in-the-middle completion. Built on the Qwen2.5 architecture, it extends the base series' improvements in instruction-following and long-context handling to coding-specific tasks within a compact deployable footprint. It became popular for integration into IDE extensions, CI pipelines, and self-hosted code assistant tools.
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.
3 months newer
Qwen2.5-Coder 7B Instruct
Alibaba / Qwen
2024-11-12
Qwen2.5-VL 32B Instruct
Alibaba / Qwen
2025-03-01
Average performance across 1 common benchmarks
Qwen2.5-Coder 7B Instruct
Qwen2.5-VL 32B Instruct
Performance comparison across key benchmark categories
Qwen2.5-Coder 7B Instruct
Qwen2.5-VL 32B Instruct
Available providers and their performance metrics
Qwen2.5-Coder 7B Instruct
Qwen2.5-VL 32B Instruct
Qwen2.5-Coder 7B Instruct
Qwen2.5-VL 32B Instruct