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Gemini 2.0 Flash vs Phi-3.5-mini-instruct
Comprehensive side-by-side LLM comparison
Gemini 2.0 Flash leads with 34.0% higher average benchmark score. Gemini 2.0 Flash offers 800.8K more tokens in context window than Phi-3.5-mini-instruct. Both models have similar pricing. Gemini 2.0 Flash supports multimodal inputs. Overall, Gemini 2.0 Flash is the stronger choice for coding tasks.
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Gemini 2.0 Flash was developed as the next generation of Google's fast multimodal model, designed to provide improved performance while maintaining the speed and efficiency that defines the Flash family. Built with enhanced reasoning and generation capabilities, it serves applications requiring both quality and responsiveness.
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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.
3 months newer
Phi-3.5-mini-instruct
Microsoft
2024-08-23
Gemini 2.0 Flash
2024-12-01
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Pricing Comparison
Cost per million tokens (USD)
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Gemini 2.0 Flash
Input:$0.10
Output:$0.40
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Phi-3.5-mini-instruct
Input:$0.10
Output:$0.10($0.30 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 3 common benchmarks
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Gemini 2.0 Flash
Average Score:76.1%(+34.0%)
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Phi-3.5-mini-instruct
Average Score:42.1%
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Knowledge Cutoff
Training data recency comparison
Gemini 2.0 Flash
2024-08-01
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
1 providers
Throughput: 183 tok/s
Latency: 0.4ms
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Phi-3.5-mini-instruct
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Gemini 2.0 Flash
Avg Score:76.1%(+34.0%)
Providers:1
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Phi-3.5-mini-instruct
Avg Score:42.1%
Providers:1