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GPT-4.1 nano vs Kimi K2 Base
Comprehensive side-by-side LLM comparison
Kimi K2 Base leads with 2.8% 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 was developed as the smallest and most efficient variant in the GPT-4.1 family, designed for applications requiring minimal latency and resource usage. Built to enable AI capabilities on edge devices and resource-constrained environments, it distills GPT-4.1 capabilities into an ultra-compact form factor.
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Moonshot AI
Kimi K2 Base was created as the foundation model in the K2 series, designed to serve as a starting point for fine-tuning and customization. Built to provide strong base capabilities for domain-specific applications, it enables developers to build specialized solutions on Moonshot's architecture.
2 months newer
GPT-4.1 nano
OpenAI
2025-04-14
Kimi K2 Base
Moonshot AI
2025-07-11
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Performance Metrics
Context window and performance specifications
Average performance across 2 common benchmarks
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GPT-4.1 nano
Average Score:65.2%
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Kimi K2 Base
Average Score:68.0%(+2.8%)
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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:65.2%
Providers:1
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Kimi K2 Base
Avg Score:68.0%(+2.8%)
Providers:0