Model Comparison

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

Google

Gemma 3n E2B

Google

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.

GLM-4.5V

Zhipu AI

GLM-4.5V is a multimodal language model developed by Zhipu AI. It supports a 197K token context window for handling large documents. The model is available through 2 API providers. 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 Zhipu AI's latest advancement in AI technology.

Google

Gemma 3n E2B

Google

2025-06-26

GLM-4.5V

Zhipu AI

2025-08-11

1 month newer

Performance Metrics

Context window and performance specifications

Google

Gemma 3n E2B

Max Context:-
Parameters:8.0B

GLM-4.5V

Larger context
Max Context:196.6K
Parameters:108.0B

Average performance across 11 common benchmarks

Google

Gemma 3n E2B

+58.6%
Average Score:58.6%

GLM-4.5V

Average Score:0.0%
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

Google

Gemma 3n E2B

0 providers

GLM-4.5V

2 providers

Novita

ZeroEval

Throughput: 85 tok/s
Latency: 0.7ms
Google

Gemma 3n E2B

+58.6%
Avg Score:58.6%
Providers:0

GLM-4.5V

Avg Score:0.0%
Providers:2