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Gemini 1.5 Pro vs Phi-3.5-MoE-instruct
Comprehensive side-by-side LLM comparison
Phi-3.5-MoE-instruct leads with 8.1% higher average benchmark score. Gemini 1.5 Pro supports multimodal inputs. Overall, Phi-3.5-MoE-instruct is the stronger choice for coding tasks.
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Gemini 1.5 Pro is a multimodal language model developed by Google. It achieves strong performance with an average score of 72.6% across 23 benchmarks. It excels particularly in XSTest (98.8%), HellaSwag (93.3%), GSM8k (90.8%). With a 2.1M 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 2024, 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.
3 months newer
Gemini 1.5 Pro
2024-05-01
Phi-3.5-MoE-instruct
Microsoft
2024-08-23
Performance Metrics
Context window and performance specifications
Average performance across 45 common benchmarks
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Gemini 1.5 Pro
Average Score:37.1%
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Phi-3.5-MoE-instruct
Average Score:45.2%(+8.1%)
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Knowledge Cutoff
Training data recency comparison
Gemini 1.5 Pro
2023-11-01
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 1.5 Pro
1 providers
Throughput: 85 tok/s
Latency: 0.7ms
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Phi-3.5-MoE-instruct
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Gemini 1.5 Pro
Avg Score:37.1%
Providers:1
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Phi-3.5-MoE-instruct
Avg Score:45.2%(+8.1%)
Providers:0