+
+
+
+
+
+
+
+
VS
VS
VS
VS
VS
VS
Gemma 3n E2B vs Phi-3.5-mini-instruct
Comprehensive side-by-side LLM comparison
Phi-3.5-mini-instruct leads with 33.6% higher average benchmark score. Gemma 3n E2B supports multimodal inputs. Overall, Phi-3.5-mini-instruct is the stronger choice for coding tasks.
+
+
+
+
Gemma 3n E2B is a multimodal language model developed by Google. The model shows competitive results across 11 benchmarks. Notable strengths include PIQA (78.9%), BoolQ (76.4%), ARC-E (75.8%). As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Google's latest advancement in AI technology.
+
+
+
+
Microsoft
Phi-3.5-mini-instruct is a language model developed by Microsoft. The model shows competitive results across 31 benchmarks. It excels particularly in GSM8k (86.2%), ARC-C (84.6%), RULER (84.1%). It supports a 256K token context window for handling large documents. The model is available through 1 API provider. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Microsoft's latest advancement in AI technology.
10 months newer
Phi-3.5-mini-instruct
Microsoft
2024-08-23
Gemma 3n E2B
2025-06-26
Performance Metrics
Context window and performance specifications
Average performance across 35 common benchmarks
+
+
+
+
Gemma 3n E2B
Average Score:18.4%
+
+
+
+
Phi-3.5-mini-instruct
Average Score:52.0%(+33.6%)
+
+
+
+
Knowledge Cutoff
Training data recency comparison
Gemma 3n E2B
2024-06-01
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
+
+
+
+
Gemma 3n E2B
0 providers
+
+
+
+
Phi-3.5-mini-instruct
1 providers
Azure
+
+
+
+
Gemma 3n E2B
Avg Score:18.4%
Providers:0
+
+
+
+
Phi-3.5-mini-instruct
Avg Score:52.0%(+33.6%)
Providers:1