Comprehensive side-by-side LLM comparison
Gemma 3 4B leads with 28.5% higher average benchmark score. Gemma 3 4B offers 221.2K more tokens in context window than Gemini 1.0 Pro. Gemma 3 4B is $1.94 cheaper per million tokens. Gemma 3 4B supports multimodal inputs. Overall, Gemma 3 4B is the stronger choice for coding tasks.
Gemini 1.0 Pro is a language model developed by Google. The model shows competitive results across 9 benchmarks. Notable strengths include BIG-Bench (75.0%), MMLU (71.8%), WMT23 (71.7%). The model is available through 1 API provider. Released in 2024, it represents Google's latest advancement in AI technology.
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.
1 year newer
Gemini 1.0 Pro
2024-02-15
Gemma 3 4B
2025-03-12
Cost per million tokens (USD)
Gemini 1.0 Pro
Gemma 3 4B
Context window and performance specifications
Average performance across 33 common benchmarks
Gemini 1.0 Pro
Gemma 3 4B
Gemini 1.0 Pro
2024-02-01
Gemma 3 4B
2024-08-01
Available providers and their performance metrics
Gemini 1.0 Pro
Gemma 3 4B
Gemini 1.0 Pro
Gemma 3 4B
Gemini 1.0 Pro
Gemma 3 4B
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