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Gemma 2 27B vs Llama 4 Scout
Comprehensive side-by-side LLM comparison
Gemma 2 27B leads with 11.9% higher average benchmark score. Llama 4 Scout supports multimodal inputs. Llama 4 Scout is available on 6 providers. Overall, Gemma 2 27B is the stronger choice for coding tasks.
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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%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Google's latest advancement in AI technology.
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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%). 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.
9 months newer
Gemma 2 27B
2024-06-27
Llama 4 Scout
Meta
2025-04-05
Performance Metrics
Context window and performance specifications
Average performance across 25 common benchmarks
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Gemma 2 27B
Average Score:44.2%(+11.9%)
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Llama 4 Scout
Average Score:32.3%
Provider Availability & Performance
Available providers and their performance metrics
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Gemma 2 27B
0 providers
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Llama 4 Scout
6 providers
DeepInfra
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Gemma 2 27B
Avg Score:44.2%(+11.9%)
Providers:0
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Llama 4 Scout
Avg Score:32.3%
Providers:6