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Gemma 3 4B vs QwQ-32B
Comprehensive side-by-side LLM comparison
Gemma 3 4B leads with 28.5% 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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Alibaba Cloud / Qwen Team
QwQ-32B is a language model developed by Alibaba Cloud / Qwen Team. It achieves strong performance with an average score of 74.6% across 7 benchmarks. It excels particularly in MATH-500 (90.6%), IFEval (83.9%), AIME 2024 (79.5%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Alibaba Cloud / Qwen Team's latest advancement in AI technology.
7 days newer
QwQ-32B
Alibaba Cloud / Qwen Team
2025-03-05
Gemma 3 4B
2025-03-12
Performance Metrics
Context window and performance specifications
Average performance across 30 common benchmarks
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Gemma 3 4B
Average Score:45.9%(+28.5%)
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QwQ-32B
Average Score:17.4%
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Knowledge Cutoff
Training data recency comparison
Gemma 3 4B
2024-08-01
QwQ-32B
2024-11-28
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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QwQ-32B
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Gemma 3 4B
Avg Score:45.9%(+28.5%)
Providers:1
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QwQ-32B
Avg Score:17.4%
Providers:0