Model Comparison

Comprehensive side-by-side analysis of model capabilities and performance

Google

Gemma 3n E4B Instructed

Google

Gemma 3n E4B Instructed is a multimodal language model developed by Google. The model shows competitive results across 18 benchmarks. Notable strengths include HumanEval (75.0%), MGSM (67.0%), MMLU (64.9%). 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 2025, it represents Google's latest advancement in AI technology.

Microsoft

Phi-3.5-mini-instruct

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.

Microsoft

Phi-3.5-mini-instruct

Microsoft

2024-08-23

Google

Gemma 3n E4B Instructed

Google

2025-06-26

10 months newer

Pricing Comparison

Cost per million tokens (USD)

Google

Gemma 3n E4B Instructed

Input:$20.00
Output:$40.00
Microsoft

Phi-3.5-mini-instruct

$59.80 cheaper
Input:$0.10
Output:$0.10

Performance Metrics

Context window and performance specifications

Google

Gemma 3n E4B Instructed

Max Context:64.0K
Parameters:8.0B
Microsoft

Phi-3.5-mini-instruct

Larger context
Max Context:256.0K
Parameters:3.8B

Average performance across 6 common benchmarks

Google

Gemma 3n E4B Instructed

+3.0%
Average Score:57.5%
Microsoft

Phi-3.5-mini-instruct

Average Score:54.5%

Performance comparison across key benchmark categories

Google

Gemma 3n E4B Instructed

code
38.9%
math
52.4%
general
41.6%
Microsoft

Phi-3.5-mini-instruct

code
+27.3%
66.2%
math
+8.5%
60.9%
general
+13.8%
55.4%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Gemma 3n E4B Instructed

2024-06-01

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Google

Gemma 3n E4B Instructed

1 providers

Together

Throughput: 42.09 tok/s
Latency: 0.43ms
Microsoft

Phi-3.5-mini-instruct

1 providers

Azure

Throughput: 23 tok/s
Latency: 0.52ms
Google

Gemma 3n E4B Instructed

+3.0%
Avg Score:57.5%
Providers:1
Microsoft

Phi-3.5-mini-instruct

Avg Score:54.5%
Providers:1