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GPT-4.1 nano vs Qwen2-VL-72B-Instruct
Comprehensive side-by-side LLM comparison
. 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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Alibaba Cloud / Qwen Team
Qwen2-VL 72B was developed as a large vision-language model, designed to handle multimodal tasks combining visual and textual understanding. Built with 72 billion parameters for integrated vision and language processing, it enables applications requiring sophisticated analysis of images alongside text.
7 months newer
Qwen2-VL-72B-Instruct
Alibaba Cloud / Qwen Team
2024-08-29
GPT-4.1 nano
OpenAI
2025-04-14
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Performance Metrics
Context window and performance specifications
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Knowledge Cutoff
Training data recency comparison
Qwen2-VL-72B-Instruct
2023-06-30
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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Qwen2-VL-72B-Instruct
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GPT-4.1 nano
Avg Score:0.0%
Providers:1
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Qwen2-VL-72B-Instruct
Avg Score:0.0%
Providers:0