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DeepSeek VL2 vs GPT-4.1 nano
Comprehensive side-by-side LLM comparison
DeepSeek VL2 leads with 1.1% higher average benchmark score. GPT-4.1 nano offers 821.8K more tokens in context window than DeepSeek VL2. GPT-4.1 nano is $4809.00 cheaper per million tokens. Both models have their strengths depending on your specific coding needs.
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DeepSeek
DeepSeek-VL2 was developed as a vision-language model, designed to handle both visual and textual inputs for multimodal understanding tasks. Built to extend DeepSeek's capabilities beyond text-only processing, it enables applications requiring integrated analysis of images and language.
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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.
4 months newer
DeepSeek VL2
DeepSeek
2024-12-13
GPT-4.1 nano
OpenAI
2025-04-14
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Pricing Comparison
Cost per million tokens (USD)
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DeepSeek VL2
Input:$9.50
Output:$4800.00
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GPT-4.1 nano
Input:$0.10
Output:$0.40($4809.00 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 2 common benchmarks
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DeepSeek VL2
Average Score:57.0%(+1.1%)
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GPT-4.1 nano
Average Score:55.8%
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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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DeepSeek VL2
1 providers
Replicate
Throughput: 22 tok/s
Latency: 0.5ms
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GPT-4.1 nano
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DeepSeek VL2
Avg Score:57.0%(+1.1%)
Providers:1
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GPT-4.1 nano
Avg Score:55.8%
Providers:1