Comprehensive side-by-side LLM comparison
Gemma 3 27B leads with 48.4% higher average benchmark score. GPT-5 nano offers 265.9K more tokens in context window than Gemma 3 27B. Both models have similar pricing. Overall, Gemma 3 27B is the stronger choice for coding tasks.
Gemma 3 27B is a multimodal language model developed by Google. It achieves strong performance with an average score of 65.4% across 26 benchmarks. It excels particularly in GSM8k (95.9%), IFEval (90.4%), MATH (89.0%). It supports a 262K 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. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Google's latest advancement in AI technology.
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.
4 months newer
Gemma 3 27B
2025-03-12
GPT-5 nano
OpenAI
2025-08-07
Cost per million tokens (USD)
Gemma 3 27B
GPT-5 nano
Context window and performance specifications
Average performance across 30 common benchmarks
Gemma 3 27B
GPT-5 nano
GPT-5 nano
2024-05-30
Available providers and their performance metrics
Gemma 3 27B
DeepInfra
Novita
Gemma 3 27B
GPT-5 nano
Gemma 3 27B
GPT-5 nano
GPT-5 nano
OpenAI
ZeroEval