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Gemma 3n E4B Instructed vs QwQ-32B
Comprehensive side-by-side LLM comparison
Gemma 3n E4B Instructed leads with 10.2% higher average benchmark score. Gemma 3n E4B Instructed supports multimodal inputs. Overall, Gemma 3n E4B Instructed is the stronger choice for coding tasks.
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Gemma 3n E4B Instructed is a multimodal language model developed by Google. The model shows competitive results across 18 benchmarks. Notable strengths include HumanEval (75.0%), MGSM (67.0%), MMLU (64.9%). The model is available through 1 API provider. 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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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.
3 months newer
QwQ-32B
Alibaba Cloud / Qwen Team
2025-03-05
Gemma 3n E4B Instructed
2025-06-26
Performance Metrics
Context window and performance specifications
Average performance across 23 common benchmarks
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Gemma 3n E4B Instructed
Average Score:32.9%(+10.2%)
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QwQ-32B
Average Score:22.7%
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Knowledge Cutoff
Training data recency comparison
Gemma 3n E4B Instructed
2024-06-01
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 3n E4B Instructed
1 providers
Together
Throughput: 42.09 tok/s
Latency: 0.43ms
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QwQ-32B
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Gemma 3n E4B Instructed
Avg Score:32.9%(+10.2%)
Providers:1
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QwQ-32B
Avg Score:22.7%
Providers:0