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Gemma 3n E4B Instructed vs Kimi-k1.5
Comprehensive side-by-side LLM comparison
Both models show comparable benchmark performance. Both models have their strengths depending on your specific coding needs.
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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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Moonshot AI
Kimi-k1.5 is a multimodal language model developed by Moonshot AI. This model demonstrates exceptional performance with an average score of 81.7% across 9 benchmarks. It excels particularly in MATH-500 (96.2%), CLUEWSC (91.4%), C-Eval (88.3%). As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Moonshot AI's latest advancement in AI technology.
5 months newer
Kimi-k1.5
Moonshot AI
2025-01-20
Gemma 3n E4B Instructed
2025-06-26
Performance Metrics
Context window and performance specifications
Average performance across 26 common benchmarks
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Gemma 3n E4B Instructed
Average Score:29.1%(+0.8%)
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Kimi-k1.5
Average Score:28.3%
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Knowledge Cutoff
Training data recency comparison
Gemma 3n E4B Instructed
2024-06-01
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 3n E4B Instructed
1 providers
Together
Throughput: 42.09 tok/s
Latency: 0.43ms
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Kimi-k1.5
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Gemma 3n E4B Instructed
Avg Score:29.1%(+0.8%)
Providers:1
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Kimi-k1.5
Avg Score:28.3%
Providers:0