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GPT-4.1 nano vs Qwen2.5-Omni-7B
Comprehensive side-by-side LLM comparison
GPT-4.1 nano leads with 1.3% higher average benchmark score. 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
Qwen2.5-Omni 7B was created as a multimodal model supporting text, audio, and other modalities, designed to provide integrated understanding across diverse input types. Built with 7 billion parameters for efficient omni-modal processing, it extends AI capabilities beyond traditional text-only or vision-language boundaries.
18 days newer
Qwen2.5-Omni-7B
Alibaba Cloud / Qwen Team
2025-03-27
GPT-4.1 nano
OpenAI
2025-04-14
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Performance Metrics
Context window and performance specifications
Average performance across 3 common benchmarks
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GPT-4.1 nano
Average Score:54.0%(+1.3%)
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Qwen2.5-Omni-7B
Average Score:52.6%
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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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Qwen2.5-Omni-7B
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GPT-4.1 nano
Avg Score:54.0%(+1.3%)
Providers:1
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Qwen2.5-Omni-7B
Avg Score:52.6%
Providers:0