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Gemini 2.0 Flash-Lite vs Phi 4 Reasoning
Comprehensive side-by-side LLM comparison
Phi 4 Reasoning leads with 2.7% higher average benchmark score. Gemini 2.0 Flash-Lite supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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Gemini 2.0 Flash-Lite is a multimodal language model developed by Google. The model shows competitive results across 13 benchmarks. It excels particularly in MATH (86.8%), FACTS Grounding (83.6%), Global-MMLU-Lite (78.2%). 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.
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Microsoft
Phi 4 Reasoning is a language model developed by Microsoft. It achieves strong performance with an average score of 75.1% across 11 benchmarks. It excels particularly in FlenQA (97.7%), HumanEval+ (92.9%), IFEval (83.4%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Microsoft's latest advancement in AI technology.
2 months newer
Gemini 2.0 Flash-Lite
2025-02-05
Phi 4 Reasoning
Microsoft
2025-04-30
Performance Metrics
Context window and performance specifications
Average performance across 22 common benchmarks
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Gemini 2.0 Flash-Lite
Average Score:34.8%
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Phi 4 Reasoning
Average Score:37.6%(+2.7%)
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Knowledge Cutoff
Training data recency comparison
Gemini 2.0 Flash-Lite
2024-06-01
Phi 4 Reasoning
2025-03-01
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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Gemini 2.0 Flash-Lite
1 providers
Throughput: 85 tok/s
Latency: 0.7ms
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Phi 4 Reasoning
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Gemini 2.0 Flash-Lite
Avg Score:34.8%
Providers:1
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Phi 4 Reasoning
Avg Score:37.6%(+2.7%)
Providers:0