Comprehensive side-by-side LLM comparison
Gemma 3 27B leads with 25.6% higher average benchmark score. Gemma 3 27B offers 230.1K more tokens in context window than Phi 4. Both models have similar pricing. Gemma 3 27B supports multimodal inputs. Overall, Gemma 3 27B is the stronger choice for coding tasks.
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.
Microsoft
Phi 4 is a language model developed by Microsoft. It achieves strong performance with an average score of 66.0% across 13 benchmarks. It excels particularly in MMLU (84.8%), HumanEval+ (82.8%), HumanEval (82.6%). The model is available through 1 API provider. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Microsoft's latest advancement in AI technology.
3 months newer
Phi 4
Microsoft
2024-12-12
Gemma 3 27B
2025-03-12
Cost per million tokens (USD)
Gemma 3 27B
Phi 4
Context window and performance specifications
Average performance across 33 common benchmarks
Gemma 3 27B
Phi 4
Phi 4
2024-06-01
Available providers and their performance metrics
Gemma 3 27B
DeepInfra
Novita
Gemma 3 27B
Phi 4
Gemma 3 27B
Phi 4
Phi 4
DeepInfra