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GPT-4.1 nano vs Qwen2 7B Instruct
Comprehensive side-by-side LLM comparison
Both models show comparable benchmark performance. 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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Alibaba Cloud / Qwen Team
Qwen2 7B Instruct is a language model developed by Alibaba Cloud / Qwen Team. The model shows competitive results across 14 benchmarks. It excels particularly in MT-Bench (84.1%), GSM8k (82.3%), HumanEval (79.9%). It's licensed for commercial use, making it suitable for enterprise applications. Released in 2024, it represents Alibaba Cloud / Qwen Team's latest advancement in AI technology.
8 months newer
Qwen2 7B Instruct
Alibaba Cloud / Qwen Team
2024-07-23
GPT-4.1 nano
OpenAI
2025-04-14
Performance Metrics
Context window and performance specifications
Average performance across 37 common benchmarks
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GPT-4.1 nano
Average Score:23.1%(+0.6%)
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Qwen2 7B Instruct
Average Score:22.5%
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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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Qwen2 7B Instruct
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GPT-4.1 nano
Avg Score:23.1%(+0.6%)
Providers:1
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Qwen2 7B Instruct
Avg Score:22.5%
Providers:0