Comprehensive side-by-side LLM comparison
Gemma 3 4B leads with 37.6% higher average benchmark score. GPT-5 nano offers 265.9K more tokens in context window than Gemma 3 4B. Both models have similar pricing. Overall, Gemma 3 4B is the stronger choice for coding tasks.
Gemma 3 4B is a multimodal language model developed by Google. The model shows competitive results across 26 benchmarks. It excels particularly in IFEval (90.2%), GSM8k (89.2%), DocVQA (75.8%). It supports a 262K token context window for handling large documents. The model is available through 1 API provider. 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 4B
2025-03-12
GPT-5 nano
OpenAI
2025-08-07
Cost per million tokens (USD)
Gemma 3 4B
GPT-5 nano
Context window and performance specifications
Average performance across 30 common benchmarks
Gemma 3 4B
GPT-5 nano
GPT-5 nano
2024-05-30
Gemma 3 4B
2024-08-01
Available providers and their performance metrics
Gemma 3 4B
DeepInfra
GPT-5 nano
Gemma 3 4B
GPT-5 nano
Gemma 3 4B
GPT-5 nano
OpenAI
ZeroEval