Comprehensive side-by-side LLM comparison
Gemma 3 12B leads with 23.2% higher average benchmark score. Gemma 3 12B offers 230.1K more tokens in context window than Phi 4. Both models have similar pricing. Gemma 3 12B supports multimodal inputs. Overall, Gemma 3 12B is the stronger choice for coding tasks.
Gemma 3 12B is a multimodal language model developed by Google. It achieves strong performance with an average score of 62.5% across 26 benchmarks. It excels particularly in GSM8k (94.4%), IFEval (88.9%), DocVQA (87.1%). It supports a 262K token context window for handling large documents. The model is available through 1 API provider. 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 12B
2025-03-12
Cost per million tokens (USD)
Gemma 3 12B
Phi 4
Context window and performance specifications
Average performance across 33 common benchmarks
Gemma 3 12B
Phi 4
Phi 4
2024-06-01
Available providers and their performance metrics
Gemma 3 12B
DeepInfra
Phi 4
Gemma 3 12B
Phi 4
Gemma 3 12B
Phi 4
DeepInfra