+
+
+
+
+
+
+
+
VS
VS
VS
VS
VS
VS
GPT-4.1 nano vs Qwen2.5 VL 32B Instruct
Comprehensive side-by-side LLM comparison
Qwen2.5 VL 32B Instruct leads with 2.9% higher average benchmark score. 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
Qwen2.5-VL 32B was developed as a mid-sized vision-language model, designed to balance multimodal capability with practical deployment considerations. Built with 32 billion parameters for vision and language integration, it serves applications requiring strong visual understanding without flagship-scale resources.
1 month newer
Qwen2.5 VL 32B Instruct
Alibaba Cloud / Qwen Team
2025-02-28
GPT-4.1 nano
OpenAI
2025-04-14
+
+
+
+
+
+
+
+
+
+
+
+
Performance Metrics
Context window and performance specifications
Average performance across 3 common benchmarks
+
+
+
+
GPT-4.1 nano
Average Score:61.9%
+
+
+
+
Qwen2.5 VL 32B Instruct
Average Score:64.8%(+2.9%)
+
+
+
+
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 VL 32B Instruct
+
+
+
+
GPT-4.1 nano
Avg Score:61.9%
Providers:1
+
+
+
+
Qwen2.5 VL 32B Instruct
Avg Score:64.8%(+2.9%)
Providers:0