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Gemma 2 27B vs GPT-4.1 nano
Comprehensive side-by-side LLM comparison
Gemma 2 27B leads with 6.3% higher average benchmark score. GPT-4.1 nano supports multimodal inputs. 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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OpenAI
GPT-4.1 nano is a multimodal language model developed by OpenAI. The model shows competitive results across 25 benchmarks. It excels particularly in MMLU (80.1%), IFEval (74.5%), CharXiv-D (73.9%). 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 OpenAI's latest advancement in AI technology.
9 months newer
Gemma 2 27B
2024-06-27
GPT-4.1 nano
OpenAI
2025-04-14
Performance Metrics
Context window and performance specifications
Average performance across 40 common benchmarks
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Gemma 2 27B
Average Score:27.6%(+6.3%)
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GPT-4.1 nano
Average Score:21.4%
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Knowledge Cutoff
Training data recency comparison
GPT-4.1 nano
2024-05-31
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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Gemma 2 27B
0 providers
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GPT-4.1 nano
1 providers
OpenAI
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Gemma 2 27B
Avg Score:27.6%(+6.3%)
Providers:0
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GPT-4.1 nano
Avg Score:21.4%
Providers:1