Comprehensive side-by-side LLM comparison
Gemma 3 12B leads with 15.1% higher average benchmark score. Gemma 3 12B offers 6.1K more tokens in context window than Phi-4-multimodal-instruct. Both models have similar pricing. 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-multimodal-instruct is a multimodal language model developed by Microsoft. It achieves strong performance with an average score of 72.0% across 15 benchmarks. It excels particularly in ScienceQA Visual (97.5%), DocVQA (93.2%), MMBench (86.7%). It supports a 256K 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 Microsoft's latest advancement in AI technology.
1 month newer
Phi-4-multimodal-instruct
Microsoft
2025-02-01
Gemma 3 12B
2025-03-12
Cost per million tokens (USD)
Gemma 3 12B
Phi-4-multimodal-instruct
Context window and performance specifications
Average performance across 36 common benchmarks
Gemma 3 12B
Phi-4-multimodal-instruct
Phi-4-multimodal-instruct
2024-06-01
Available providers and their performance metrics
Gemma 3 12B
DeepInfra
Phi-4-multimodal-instruct
Gemma 3 12B
Phi-4-multimodal-instruct
Gemma 3 12B
Phi-4-multimodal-instruct
DeepInfra