Model Comparison

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

Google

Gemini 1.5 Pro

Google

Gemini 1.5 Pro is a multimodal language model developed by Google. It achieves strong performance with an average score of 72.6% across 23 benchmarks. It excels particularly in XSTest (98.8%), HellaSwag (93.3%), GSM8k (90.8%). With a 2.1M 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 2024, it represents Google's latest advancement in AI technology.

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.

Google

Gemini 1.5 Pro

Google

2024-05-01

Google

Gemma 3n E2B Instructed LiteRT (Preview)

Google

2025-05-20

1 year newer

Performance Metrics

Context window and performance specifications

Google

Gemini 1.5 Pro

Larger context
Max Context:2.1M
Google

Gemma 3n E2B Instructed LiteRT (Preview)

Max Context:-
Parameters:1.9B

Average performance across 9 common benchmarks

Google

Gemini 1.5 Pro

+28.7%
Average Score:78.0%
Google

Gemma 3n E2B Instructed LiteRT (Preview)

Average Score:49.2%

Performance comparison across key benchmark categories

Google

Gemini 1.5 Pro

reasoning
+26.7%
93.3%
math
+34.5%
74.9%
code
+41.3%
74.5%
general
+26.8%
68.9%
Google

Gemma 3n E2B Instructed LiteRT (Preview)

reasoning
66.6%
math
40.4%
code
33.2%
general
42.2%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

Gemini 1.5 Pro

2023-11-01

Gemma 3n E2B Instructed LiteRT (Preview)

2024-06-01

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

Google

Gemini 1.5 Pro

1 providers

Google

Throughput: 85 tok/s
Latency: 0.7ms
Google

Gemma 3n E2B Instructed LiteRT (Preview)

0 providers
Google

Gemini 1.5 Pro

+28.7%
Avg Score:78.0%
Providers:1
Google

Gemma 3n E2B Instructed LiteRT (Preview)

Avg Score:49.2%
Providers:0