Comprehensive side-by-side LLM comparison
Qwen2.5 7B Instruct leads with 4.8% higher average benchmark score. Gemma 3 27B supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
Google DeepMind
Gemma 3 27B is a 27-billion-parameter open-weight model from Google DeepMind, released in March 2025 alongside the Gemma 3 12B as the higher-capability variant in the series, built with native vision-language support for text and image inputs across a 128K token context window. Among the Gemma 3 releases, the 27B delivered the strongest results on instruction-following and knowledge-intensive reasoning tasks, making it the preferred option for developers needing greater accuracy from a self-hostable model. Its open-weight availability under a permissive license made it a common starting point for vision-language fine-tuning projects.
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.
5 months newer
Qwen2.5 7B Instruct
Alibaba / Qwen
2024-09-19

Gemma 3 27B
Google DeepMind
2025-03-12
Average performance across 1 common benchmarks
Gemma 3 27B
Qwen2.5 7B Instruct
Performance comparison across key benchmark categories
Gemma 3 27B
Qwen2.5 7B Instruct
Available providers and their performance metrics
Gemma 3 27B
Qwen2.5 7B Instruct
Gemma 3 27B
Qwen2.5 7B Instruct