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Gemma 3 4B vs Granite 3.3 8B Base
Comprehensive side-by-side LLM comparison
Gemma 3 4B leads with 2.2% higher average benchmark score. Both models have their strengths depending on your specific coding needs.
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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.
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IBM
Granite 3.3 8B Base is a multimodal language model developed by IBM. It achieves strong performance with an average score of 64.3% across 20 benchmarks. It excels particularly in HumanEval (89.7%), AttaQ (88.5%), HumanEval+ (86.1%). 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 IBM's latest advancement in AI technology.
1 month newer
Gemma 3 4B
2025-03-12
Granite 3.3 8B Base
IBM
2025-04-16
Performance Metrics
Context window and performance specifications
Average performance across 42 common benchmarks
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Gemma 3 4B
Average Score:32.8%(+2.2%)
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Granite 3.3 8B Base
Average Score:30.6%
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Knowledge Cutoff
Training data recency comparison
Granite 3.3 8B Base
2024-04-01
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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Gemma 3 4B
1 providers
DeepInfra
Throughput: 33 tok/s
Latency: 0.2ms
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Granite 3.3 8B Base
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Gemma 3 4B
Avg Score:32.8%(+2.2%)
Providers:1
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Granite 3.3 8B Base
Avg Score:30.6%
Providers:0