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Gemma 3 12B vs Phi-3.5-mini-instruct
Comprehensive side-by-side LLM comparison
Gemma 3 12B leads with 15.7% higher average benchmark score. Gemma 3 12B offers 6.1K more tokens in context window than Phi-3.5-mini-instruct. Both models have similar pricing. Gemma 3 12B supports multimodal inputs. Overall, Gemma 3 12B is the stronger choice for coding tasks.
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Gemma 3 12B was developed as part of the third generation of Google's open-source model family, designed to provide enhanced capabilities in a mid-sized format. Built with improved architecture and training techniques, it balances performance with practical deployment considerations for diverse use cases.
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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.
6 months newer
Phi-3.5-mini-instruct
Microsoft
2024-08-23
Gemma 3 12B
2025-03-12
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Pricing Comparison
Cost per million tokens (USD)
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Gemma 3 12B
Input:$0.05
Output:$0.10($0.05 cheaper)
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Phi-3.5-mini-instruct
Input:$0.10
Output:$0.10
Performance Metrics
Context window and performance specifications
Average performance across 7 common benchmarks
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Gemma 3 12B
Average Score:74.8%(+15.7%)
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Phi-3.5-mini-instruct
Average Score:59.1%
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-mini-instruct
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Gemma 3 12B
Avg Score:74.8%(+15.7%)
Providers:1
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Phi-3.5-mini-instruct
Avg Score:59.1%
Providers:1