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

Gemma 2 27B
Gemma 2 27B is a language model developed by Google. It achieves strong performance with an average score of 69.1% across 16 benchmarks. It excels particularly in ARC-E (88.6%), HellaSwag (86.4%), BoolQ (84.8%). The model shows particular specialization in reasoning tasks with an average performance of 82.5%. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Google's latest advancement in AI technology.

Llama 4 Scout
Meta
Llama 4 Scout is a multimodal language model developed by Meta. It achieves strong performance with an average score of 67.3% across 12 benchmarks. It excels particularly in DocVQA (94.4%), MGSM (90.6%), ChartQA (88.8%). The model shows particular specialization in vision tasks with an average performance of 81.9%. With a 20.0M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 6 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Meta's latest advancement in AI technology.

Gemma 2 27B
2024-06-27

Llama 4 Scout
Meta
2025-04-05
9 months newer
Performance Metrics
Context window and performance specifications

Gemma 2 27B

Llama 4 Scout
Average performance across 3 common benchmarks

Gemma 2 27B

Llama 4 Scout
Performance comparison across key benchmark categories

Gemma 2 27B

Llama 4 Scout
Provider Availability & Performance
Available providers and their performance metrics

Gemma 2 27B

Llama 4 Scout
Together
DeepInfra
Fireworks
Groq
Novita
Lambda

Gemma 2 27B

Llama 4 Scout