Model Comparison

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

Google

Gemma 3n E2B Instructed LiteRT (Preview)

Google

Gemma 3n E2B Instructed LiteRT (Preview) is a multimodal language model developed by Google. The model shows competitive results across 28 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. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Google's latest advancement in AI technology.

Microsoft

Phi-4-multimodal-instruct

Microsoft

Phi-4-multimodal-instruct is a multimodal language model developed by Microsoft. It achieves strong performance with an average score of 72.0% across 15 benchmarks. It excels particularly in ScienceQA Visual (97.5%), DocVQA (93.2%), MMBench (86.7%). The model shows particular specialization in general tasks with an average performance of 75.8%. It supports a 256K 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 Microsoft's latest advancement in AI technology.

Microsoft

Phi-4-multimodal-instruct

Microsoft

2025-02-01

Google

Gemma 3n E2B Instructed LiteRT (Preview)

Google

2025-05-20

3 months newer

Performance Metrics

Context window and performance specifications

Google

Gemma 3n E2B Instructed LiteRT (Preview)

Max Context:-
Parameters:1.9B
Microsoft

Phi-4-multimodal-instruct

Larger context
Max Context:256.0K
Parameters:5.6B

Performance comparison across key benchmark categories

Google

Gemma 3n E2B Instructed LiteRT (Preview)

general
42.2%
math
40.4%
Microsoft

Phi-4-multimodal-instruct

general
+33.6%
75.8%
math
+22.0%
62.4%
Knowledge Cutoff
Training data recency comparison

Gemma 3n E2B Instructed LiteRT (Preview)

2024-06-01

Phi-4-multimodal-instruct

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 E2B Instructed LiteRT (Preview)

0 providers
Microsoft

Phi-4-multimodal-instruct

1 providers

DeepInfra

Throughput: 25 tok/s
Latency: 0.5ms
Google

Gemma 3n E2B Instructed LiteRT (Preview)

Avg Score:0.0%
Providers:0
Microsoft

Phi-4-multimodal-instruct

Avg Score:0.0%
Providers:1
Gemma 3n E2B Instructed LiteRT (Preview) vs Phi-4-multimodal-instruct - AI Model Comparison | The AI Forger