Comprehensive side-by-side LLM comparison
Gemma 3 27B leads with 38.4% higher average benchmark score. Gemma 3 27B offers 221.2K more tokens in context window than Gemini 1.0 Pro. Gemma 3 27B is $1.70 cheaper per million tokens. Gemma 3 27B supports multimodal inputs. Overall, Gemma 3 27B is the stronger choice for coding tasks.
Gemini 1.0 Pro is a language model developed by Google. The model shows competitive results across 9 benchmarks. Notable strengths include BIG-Bench (75.0%), MMLU (71.8%), WMT23 (71.7%). The model is available through 1 API provider. Released in 2024, it represents Google's latest advancement in AI technology.
Gemma 3 27B is a multimodal language model developed by Google. It achieves strong performance with an average score of 65.4% across 26 benchmarks. It excels particularly in GSM8k (95.9%), IFEval (90.4%), MATH (89.0%). It supports a 262K token context window for handling large documents. The model is available through 2 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Google's latest advancement in AI technology.
1 year newer
Gemini 1.0 Pro
2024-02-15
Gemma 3 27B
2025-03-12
Cost per million tokens (USD)
Gemini 1.0 Pro
Gemma 3 27B
Context window and performance specifications
Average performance across 33 common benchmarks
Gemini 1.0 Pro
Gemma 3 27B
Gemini 1.0 Pro
2024-02-01
Available providers and their performance metrics
Gemini 1.0 Pro
Gemma 3 27B
Gemini 1.0 Pro
Gemma 3 27B
Gemini 1.0 Pro
Gemma 3 27B
DeepInfra
Novita