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Gemini 2.5 Flash-Lite vs Phi-3.5-MoE-instruct
Comprehensive side-by-side LLM comparison
Phi-3.5-MoE-instruct leads with 34.9% higher average benchmark score. Gemini 2.5 Flash-Lite supports multimodal inputs. Overall, Phi-3.5-MoE-instruct is the stronger choice for coding tasks.
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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.
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Microsoft
Phi-3.5-MoE-instruct is a language model developed by Microsoft. It achieves strong performance with an average score of 65.6% across 31 benchmarks. It excels particularly in ARC-C (91.0%), OpenBookQA (89.6%), GSM8k (88.7%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Microsoft's latest advancement in AI technology.
9 months newer
Phi-3.5-MoE-instruct
Microsoft
2024-08-23
Gemini 2.5 Flash-Lite
2025-06-17
Performance Metrics
Context window and performance specifications
Average performance across 43 common benchmarks
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Gemini 2.5 Flash-Lite
Average Score:12.3%
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Phi-3.5-MoE-instruct
Average Score:47.3%(+34.9%)
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Knowledge Cutoff
Training data recency comparison
Gemini 2.5 Flash-Lite
2025-01-01
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 2.5 Flash-Lite
1 providers
Throughput: 5.69 tok/s
Latency: 0.44ms
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Phi-3.5-MoE-instruct
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Gemini 2.5 Flash-Lite
Avg Score:12.3%
Providers:1
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Phi-3.5-MoE-instruct
Avg Score:47.3%(+34.9%)
Providers:0