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Gemma 3 4B vs Magistral Small 2506
Comprehensive side-by-side LLM comparison
Gemma 3 4B leads with 40.2% higher average benchmark score. Gemma 3 4B supports multimodal inputs. Overall, Gemma 3 4B is the stronger choice for coding tasks.
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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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Mistral AI
Magistral Small 2506 is a language model developed by Mistral AI. It achieves strong performance with an average score of 63.2% across 4 benchmarks. Notable strengths include AIME 2024 (70.7%), GPQA (68.2%), AIME 2025 (62.8%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Mistral AI's latest advancement in AI technology.
3 months newer
Gemma 3 4B
2025-03-12
Magistral Small 2506
Mistral AI
2025-06-10
Performance Metrics
Context window and performance specifications
Average performance across 28 common benchmarks
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Gemma 3 4B
Average Score:49.2%(+40.2%)
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Magistral Small 2506
Average Score:9.0%
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Knowledge Cutoff
Training data recency comparison
Gemma 3 4B
2024-08-01
Magistral Small 2506
2025-06-01
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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Magistral Small 2506
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Gemma 3 4B
Avg Score:49.2%(+40.2%)
Providers:1
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Magistral Small 2506
Avg Score:9.0%
Providers:0