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Gemini 2.0 Flash Thinking vs Gemma 3 4B
Comprehensive side-by-side LLM comparison
Gemma 3 4B leads with 41.2% higher average benchmark score. Overall, Gemma 3 4B is the stronger choice for coding tasks.
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Gemini 2.0 Flash Thinking is a multimodal language model developed by Google. It achieves strong performance with an average score of 74.3% across 3 benchmarks. Notable strengths include MMMU (75.4%), GPQA (74.2%), AIME 2024 (73.3%). As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Google's latest advancement in AI technology.
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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 month newer
Gemini 2.0 Flash Thinking
2025-01-21
Gemma 3 4B
2025-03-12
Performance Metrics
Context window and performance specifications
Average performance across 28 common benchmarks
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Gemini 2.0 Flash Thinking
Average Score:8.0%
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Gemma 3 4B
Average Score:49.2%(+41.2%)
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Knowledge Cutoff
Training data recency comparison
Gemini 2.0 Flash Thinking
2024-08-01
Gemma 3 4B
2024-08-01
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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Gemini 2.0 Flash Thinking
0 providers
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Gemma 3 4B
1 providers
DeepInfra
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Gemini 2.0 Flash Thinking
Avg Score:8.0%
Providers:0
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Gemma 3 4B
Avg Score:49.2%(+41.2%)
Providers:1