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

Gemma 3n E2B
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.

GPT-5 nano
OpenAI
GPT-5 nano is a multimodal language model developed by OpenAI. The model shows competitive results across 5 benchmarks. It excels particularly in AIME 2025 (85.2%), HMMT 2025 (75.6%), GPQA (71.2%). It supports a 528K 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. Released in 2025, it represents OpenAI's latest advancement in AI technology.

Gemma 3n E2B
2025-06-26

GPT-5 nano
OpenAI
2025-08-07
1 month newer
Performance Metrics
Context window and performance specifications

Gemma 3n E2B

GPT-5 nano
Performance comparison across key benchmark categories

Gemma 3n E2B

GPT-5 nano
GPT-5 nano
2024-05-30
Gemma 3n E2B
2024-06-01
Provider Availability & Performance
Available providers and their performance metrics

Gemma 3n E2B

GPT-5 nano
ZeroEval
OpenAI

Gemma 3n E2B

GPT-5 nano