Comprehensive side-by-side LLM comparison
Qwen2.5 14B Instruct leads with 2.8% higher average benchmark score. 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
Qwen2.5-7B-Instruct is a 7-billion-parameter open-weight language model from Alibaba's Qwen team, released in September 2024 as part of the Qwen2.5 series trained on 18 trillion tokens with improved code, math, and multilingual coverage. The model delivers significantly stronger instruction-following, structured output generation, and long-context handling compared to its predecessor, supporting 128K context windows in a compact form factor. It became widely adopted as a foundation for fine-tuning, RAG pipelines, and on-device deployment due to its balance of capability and efficiency.
Launched on the same date
Qwen2.5 14B Instruct
Alibaba / Qwen
2024-09-19
Qwen2.5 7B Instruct
Alibaba / Qwen
2024-09-19
Average performance across 1 common benchmarks
Qwen2.5 14B Instruct
Qwen2.5 7B Instruct
Performance comparison across key benchmark categories
Qwen2.5 14B Instruct
Qwen2.5 7B Instruct
Available providers and their performance metrics
Qwen2.5 14B Instruct
Qwen2.5 7B Instruct
Qwen2.5 14B Instruct
Qwen2.5 7B Instruct