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GPT-4.1 nano vs Kimi K2 Base
Comprehensive side-by-side LLM comparison
Kimi K2 Base leads with 1.2% higher average benchmark score. GPT-4.1 nano supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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OpenAI
GPT-4.1 nano is a multimodal language model developed by OpenAI. The model shows competitive results across 25 benchmarks. It excels particularly in MMLU (80.1%), IFEval (74.5%), CharXiv-D (73.9%). With a 1.1M token context window, it can handle extensive documents and complex multi-turn conversations. 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 OpenAI's latest advancement in AI technology.
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Moonshot AI
Kimi K2 Base is a language model developed by Moonshot AI. It achieves strong performance with an average score of 69.2% across 13 benchmarks. It excels particularly in C-Eval (92.5%), GSM8k (92.1%), MMLU-redux-2.0 (90.2%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Moonshot AI's latest advancement in AI technology.
2 months newer
GPT-4.1 nano
OpenAI
2025-04-14
Kimi K2 Base
Moonshot AI
2025-07-11
Performance Metrics
Context window and performance specifications
Average performance across 36 common benchmarks
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GPT-4.1 nano
Average Score:23.7%
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Kimi K2 Base
Average Score:25.0%(+1.2%)
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Knowledge Cutoff
Training data recency comparison
GPT-4.1 nano
2024-05-31
More recent knowledge cutoff means awareness of newer technologies and frameworks
Provider Availability & Performance
Available providers and their performance metrics
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GPT-4.1 nano
1 providers
OpenAI
Throughput: 200 tok/s
Latency: 2ms
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Kimi K2 Base
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GPT-4.1 nano
Avg Score:23.7%
Providers:1
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Kimi K2 Base
Avg Score:25.0%(+1.2%)
Providers:0