Comprehensive side-by-side LLM comparison
Phi 4 leads with 13.7% higher average benchmark score. Gemini 2.5 Flash-Lite offers 1.1M more tokens in context window than Phi 4. Both models have similar pricing. Gemini 2.5 Flash-Lite supports multimodal inputs. Overall, Phi 4 is the stronger choice for coding tasks.
Gemini 2.5 Flash-Lite is a multimodal language model developed by Google. The model shows competitive results across 13 benchmarks. It excels particularly in FACTS Grounding (84.1%), Global-MMLU-Lite (81.1%), MMMU (72.9%). With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 1 API provider. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. 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.
6 months newer
Phi 4
Microsoft
2024-12-12
Gemini 2.5 Flash-Lite
2025-06-17
Cost per million tokens (USD)
Gemini 2.5 Flash-Lite
Phi 4
Context window and performance specifications
Average performance across 24 common benchmarks
Gemini 2.5 Flash-Lite
Phi 4
Phi 4
2024-06-01
Gemini 2.5 Flash-Lite
2025-01-01
Available providers and their performance metrics
Gemini 2.5 Flash-Lite
Phi 4
Gemini 2.5 Flash-Lite
Phi 4
Gemini 2.5 Flash-Lite
Phi 4
DeepInfra