Comprehensive side-by-side LLM comparison
Both models show comparable benchmark performance. Both models have their strengths depending on your specific coding needs.
Alibaba / Qwen
Qwen2.5-32B-Instruct is a 32-billion-parameter open-weight model from Alibaba's Qwen team, released in September 2024 as part of the Qwen2.5 series trained on 18 trillion tokens. The model is positioned as a high-capability option for developers with access to multi-GPU setups or high-VRAM hardware, offering strong performance on coding, structured reasoning, and multilingual tasks while remaining fully open under Apache 2.0. Its 128K context window and support for structured output generation made it a popular choice for document processing and agentic workflows in the open-source community.
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.
1 month newer
Qwen2.5 32B Instruct
Alibaba / Qwen
2024-09-19
Qwen2.5-Coder 7B Instruct
Alibaba / Qwen
2024-11-12
Average performance across 1 common benchmarks
Qwen2.5 32B Instruct
Qwen2.5-Coder 7B Instruct
Performance comparison across key benchmark categories
Qwen2.5 32B Instruct
Qwen2.5-Coder 7B Instruct
Available providers and their performance metrics
Qwen2.5 32B Instruct
Qwen2.5-Coder 7B Instruct
Qwen2.5 32B Instruct
Qwen2.5-Coder 7B Instruct