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Gemini 2.5 Flash-Lite vs Phi-4-multimodal-instruct
Comprehensive side-by-side LLM comparison
Phi-4-multimodal-instruct leads with 20.4% higher average benchmark score. Gemini 2.5 Flash-Lite offers 858.1K more tokens in context window than Phi-4-multimodal-instruct. Both models have similar pricing. Overall, Phi-4-multimodal-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-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.
4 months newer
Phi-4-multimodal-instruct
Microsoft
2025-02-01
Gemini 2.5 Flash-Lite
2025-06-17
Pricing Comparison
Cost per million tokens (USD)
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Gemini 2.5 Flash-Lite
Input:$0.10
Output:$0.40
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Phi-4-multimodal-instruct
Input:$0.05
Output:$0.10($0.35 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 27 common benchmarks
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Gemini 2.5 Flash-Lite
Average Score:19.7%
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Phi-4-multimodal-instruct
Average Score:40.0%(+20.4%)
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Knowledge Cutoff
Training data recency comparison
Phi-4-multimodal-instruct
2024-06-01
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-4-multimodal-instruct
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Gemini 2.5 Flash-Lite
Avg Score:19.7%
Providers:1
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Phi-4-multimodal-instruct
Avg Score:40.0%(+20.4%)
Providers:1