Comprehensive side-by-side LLM comparison
Both models show comparable benchmark performance. 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.
Mistral AI
Mistral Small 3.1 is a 24-billion-parameter multimodal model from Mistral AI, released in March 2025 as an update to Mistral Small 3 that added vision understanding and expanded the context window from 32K to 128K tokens. The model accepts both text and image inputs, broadening its applicability to document analysis, image-grounded reasoning, and mixed-media workflows without requiring an increase in parameter count. Released under Apache 2.0, it continued Mistral's pattern of incremental capability gains delivered in compact, practically deployable open-weight packages.
5 days newer

Gemma 3 27B
Google DeepMind
2025-03-12

Mistral Small 3.1 24B Instruct
Mistral AI
2025-03-17
Average performance across 1 common benchmarks
Gemma 3 27B
Mistral Small 3.1 24B Instruct
Performance comparison across key benchmark categories
Gemma 3 27B
Mistral Small 3.1 24B Instruct
Available providers and their performance metrics
Gemma 3 27B
Mistral Small 3.1 24B Instruct
Gemma 3 27B
Mistral Small 3.1 24B Instruct