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Gemini 2.5 Pro vs Phi-3.5-mini-instruct
Comprehensive side-by-side LLM comparison
Gemini 2.5 Pro leads with 52.6% higher average benchmark score. Gemini 2.5 Pro offers 858.1K more tokens in context window than Phi-3.5-mini-instruct. Phi-3.5-mini-instruct is $11.05 cheaper per million tokens. Gemini 2.5 Pro supports multimodal inputs. Overall, Gemini 2.5 Pro is the stronger choice for coding tasks.
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Gemini 2.5 Pro was developed as Google's most intelligent AI model, designed to comprehend vast datasets and challenging problems from diverse information sources including text, audio, images, and video. Built to handle complex reasoning and multi-step problem solving, it represents Google's flagship offering for enterprise and advanced applications.
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Microsoft
Phi-3.5 Mini was developed by Microsoft as a small language model designed to deliver impressive performance despite its compact size. Built with efficiency in mind, it demonstrates that capable language understanding and generation can be achieved with fewer parameters, making AI more accessible for edge and resource-constrained deployments.
9 months newer
Phi-3.5-mini-instruct
Microsoft
2024-08-23
Gemini 2.5 Pro
2025-05-20
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Pricing Comparison
Cost per million tokens (USD)
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Gemini 2.5 Pro
Input:$1.25
Output:$10.00
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Phi-3.5-mini-instruct
Input:$0.10
Output:$0.10($11.05 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 1 common benchmarks
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Gemini 2.5 Pro
Average Score:83.0%(+52.6%)
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Phi-3.5-mini-instruct
Average Score:30.4%
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Knowledge Cutoff
Training data recency comparison
Gemini 2.5 Pro
2025-01-31
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 Pro
2 providers
Throughput: 85 tok/s
Latency: 0.7ms
ZeroEval
Throughput: 85 tok/s
Latency: 0.7ms
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Gemini 2.5 Pro
Avg Score:83.0%(+52.6%)
Providers:2
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Phi-3.5-mini-instruct
Avg Score:30.4%
Providers:1