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Gemini 2.0 Flash-Lite vs Phi 4 Mini
Comprehensive side-by-side LLM comparison
Phi 4 Mini leads with 12.8% higher average benchmark score. Gemini 2.0 Flash-Lite supports multimodal inputs. Overall, Phi 4 Mini is the stronger choice for coding tasks.
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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 Mini is a language model developed by Microsoft. It achieves strong performance with an average score of 65.4% across 17 benchmarks. It excels particularly in GSM8k (88.6%), ARC-C (83.7%), BoolQ (81.2%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Microsoft's latest advancement in AI technology.
4 days newer
Phi 4 Mini
Microsoft
2025-02-01
Gemini 2.0 Flash-Lite
2025-02-05
Performance Metrics
Context window and performance specifications
Average performance across 27 common benchmarks
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Gemini 2.0 Flash-Lite
Average Score:28.4%
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Phi 4 Mini
Average Score:41.1%(+12.8%)
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Knowledge Cutoff
Training data recency comparison
Gemini 2.0 Flash-Lite
2024-06-01
Phi 4 Mini
2024-06-01
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 Mini
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Gemini 2.0 Flash-Lite
Avg Score:28.4%
Providers:1
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Phi 4 Mini
Avg Score:41.1%(+12.8%)
Providers:0