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Gemma 3 4B vs Phi-3.5-MoE-instruct
Comprehensive side-by-side LLM comparison
Phi-3.5-MoE-instruct leads with 13.1% higher average benchmark score. Gemma 3 4B supports multimodal inputs. Overall, Phi-3.5-MoE-instruct is the stronger choice for coding tasks.
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Gemma 3 4B is a multimodal language model developed by Google. The model shows competitive results across 26 benchmarks. It excels particularly in IFEval (90.2%), GSM8k (89.2%), DocVQA (75.8%). It supports a 262K 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 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.
6 months newer
Phi-3.5-MoE-instruct
Microsoft
2024-08-23
Gemma 3 4B
2025-03-12
Performance Metrics
Context window and performance specifications
Average performance across 50 common benchmarks
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Gemma 3 4B
Average Score:27.6%
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Phi-3.5-MoE-instruct
Average Score:40.6%(+13.1%)
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Knowledge Cutoff
Training data recency comparison
Gemma 3 4B
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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Gemma 3 4B
1 providers
DeepInfra
Throughput: 33 tok/s
Latency: 0.2ms
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Phi-3.5-MoE-instruct
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Gemma 3 4B
Avg Score:27.6%
Providers:1
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Phi-3.5-MoE-instruct
Avg Score:40.6%(+13.1%)
Providers:0