+
+
+
+
+
+
+
+
VS
VS
VS
VS
VS
VS
GPT-4.1 nano vs Qwen2.5 14B Instruct
Comprehensive side-by-side LLM comparison
GPT-4.1 nano leads with 2.6% higher average benchmark score. GPT-4.1 nano supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
+
+
+
+
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.
+
+
+
+
Alibaba Cloud / Qwen Team
Qwen 2.5 14B was developed as a mid-sized instruction-tuned model, designed to balance capability and efficiency for diverse language tasks. Built with 14 billion parameters, it provides strong performance for applications requiring reliable instruction-following without the resource demands of larger models.
6 months newer
Qwen2.5 14B Instruct
Alibaba Cloud / Qwen Team
2024-09-19
GPT-4.1 nano
OpenAI
2025-04-14
+
+
+
+
+
+
+
+
+
+
+
+
Performance Metrics
Context window and performance specifications
Average performance across 2 common benchmarks
+
+
+
+
GPT-4.1 nano
Average Score:65.2%(+2.6%)
+
+
+
+
Qwen2.5 14B Instruct
Average Score:62.6%
+
+
+
+
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
+
+
+
+
GPT-4.1 nano
1 providers
OpenAI
Throughput: 200 tok/s
Latency: 2ms
+
+
+
+
Qwen2.5 14B Instruct
+
+
+
+
GPT-4.1 nano
Avg Score:65.2%(+2.6%)
Providers:1
+
+
+
+
Qwen2.5 14B Instruct
Avg Score:62.6%
Providers:0