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

Gemma 3n E2B Instructed LiteRT (Preview)
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.

Qwen2.5 7B Instruct
Alibaba
Qwen2.5 7B Instruct is a language model developed by Alibaba. It achieves strong performance with an average score of 65.6% across 14 benchmarks. It excels particularly in GSM8k (91.6%), MT-Bench (87.5%), HumanEval (84.8%). The model shows particular specialization in math tasks with an average performance of 83.5%. It supports a 139K 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 Alibaba's latest advancement in AI technology.

Qwen2.5 7B Instruct
Alibaba
2024-09-19

Gemma 3n E2B Instructed LiteRT (Preview)
2025-05-20
8 months newer
Performance Metrics
Context window and performance specifications

Gemma 3n E2B Instructed LiteRT (Preview)

Qwen2.5 7B Instruct
Average performance across 5 common benchmarks

Gemma 3n E2B Instructed LiteRT (Preview)

Qwen2.5 7B Instruct
Performance comparison across key benchmark categories

Gemma 3n E2B Instructed LiteRT (Preview)

Qwen2.5 7B Instruct
Gemma 3n E2B Instructed LiteRT (Preview)
2024-06-01
Provider Availability & Performance
Available providers and their performance metrics

Gemma 3n E2B Instructed LiteRT (Preview)

Qwen2.5 7B Instruct
Together

Gemma 3n E2B Instructed LiteRT (Preview)

Qwen2.5 7B Instruct