Model Comparison

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

Google

Gemini 2.5 Pro

Google

Gemini 2.5 Pro is a multimodal language model developed by Google. It achieves strong performance with an average score of 67.1% across 16 benchmarks. It excels particularly in MRCR (93.0%), AIME 2024 (92.0%), Global-MMLU-Lite (88.6%). The model shows particular specialization in vision tasks with an average performance of 82.2%. With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. 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.

Google

Gemma 3n E4B Instructed LiteRT Preview

Google

Gemma 3n E4B Instructed LiteRT Preview is a multimodal language model developed by Google. The model shows competitive results across 28 benchmarks. It excels particularly in ARC-E (81.6%), BoolQ (81.6%), PIQA (81.0%). 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.

Google

Gemini 2.5 Pro

Google

2025-05-20

Google

Gemma 3n E4B Instructed LiteRT Preview

Google

2025-05-20

0 days newer

Performance Metrics

Context window and performance specifications

Google

Gemini 2.5 Pro

Larger context
Max Context:1.1M
Google

Gemma 3n E4B Instructed LiteRT Preview

Max Context:-
Parameters:1.9B

Average performance across 4 common benchmarks

Google

Gemini 2.5 Pro

+51.2%
Average Score:82.5%
Google

Gemma 3n E4B Instructed LiteRT Preview

Average Score:31.4%

Performance comparison across key benchmark categories

Google

Gemini 2.5 Pro

reasoning
4.9%
code
+31.7%
70.6%
general
+21.1%
69.4%
Google

Gemma 3n E4B Instructed LiteRT Preview

reasoning
+68.5%
73.4%
code
38.9%
general
48.4%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Gemma 3n E4B Instructed LiteRT Preview

2024-06-01

Gemini 2.5 Pro

2025-01-31

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Google

Gemini 2.5 Pro

1 providers

Google

Throughput: 85 tok/s
Latency: 0.7ms
Google

Gemma 3n E4B Instructed LiteRT Preview

0 providers
Google

Gemini 2.5 Pro

+51.2%
Avg Score:82.5%
Providers:1
Google

Gemma 3n E4B Instructed LiteRT Preview

Avg Score:31.4%
Providers:0