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Gemma 3 12B vs Phi-3.5-MoE-instruct
Comprehensive side-by-side LLM comparison
Phi-3.5-MoE-instruct leads with 8.2% higher average benchmark score. Gemma 3 12B supports multimodal inputs. Overall, Phi-3.5-MoE-instruct is the stronger choice for coding tasks.
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Gemma 3 12B is a multimodal language model developed by Google. It achieves strong performance with an average score of 62.5% across 26 benchmarks. It excels particularly in GSM8k (94.4%), IFEval (88.9%), DocVQA (87.1%). 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 12B
2025-03-12
Performance Metrics
Context window and performance specifications
Average performance across 50 common benchmarks
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Gemma 3 12B
Average Score:32.5%
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Phi-3.5-MoE-instruct
Average Score:40.6%(+8.2%)
Provider Availability & Performance
Available providers and their performance metrics
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Gemma 3 12B
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 12B
Avg Score:32.5%
Providers:1
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Phi-3.5-MoE-instruct
Avg Score:40.6%(+8.2%)
Providers:0