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DeepSeek-R1 vs GPT-4.1 nano
Comprehensive side-by-side LLM comparison
GPT-4.1 nano leads with 3.6% higher average benchmark score. GPT-4.1 nano offers 944.3K more tokens in context window than DeepSeek-R1. GPT-4.1 nano is $2.24 cheaper per million tokens. GPT-4.1 nano supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
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DeepSeek
DeepSeek-R1, released by DeepSeek on January 20, 2025, is a large reasoning model with 671 billion total parameters (37 billion active in its MoE architecture) designed for extended chain-of-thought reasoning. It features a 128K token context window and demonstrated strong performance on mathematics, coding, and scientific reasoning benchmarks at its release. DeepSeek-R1 targets complex analytical tasks, competitive programming, and applications requiring deep deliberative reasoning under an open MIT license.
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OpenAI
GPT-4.1 nano is OpenAI's smallest member of the GPT-4.1 family, released in April 2025 alongside GPT-4.1 and GPT-4.1 mini as the latency-optimized, cost-minimized option for high-throughput applications. Positioned below GPT-4.1 mini in both size and cost, it was designed for use cases where speed and affordability dominate over raw capability — including tool calling, intent classification, short-form instruction following, and retrieval-augmented lookup tasks. Unlike its larger siblings, it supports fine-tuning, making it a practical candidate for task-specific customization at scale without incurring the cost of fine-tuning larger models.
2 months newer
DeepSeek-R1
DeepSeek
2025-01-20
GPT-4.1 nano
OpenAI
2025-04-14
Pricing Comparison
Cost per million tokens (USD)
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DeepSeek-R1
Input:$0.55
Output:$2.19
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GPT-4.1 nano
Input:$0.10
Output:$0.40($2.24 cheaper)
Performance Metrics
Context window and performance specifications
Average performance across 1 common benchmarks
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DeepSeek-R1
Average Score:62.4%
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GPT-4.1 nano
Average Score:66.0%(+3.6%)
Performance comparison across key benchmark categories
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DeepSeek-R1
Science62.4%
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GPT-4.1 nano
Science66.0%(+3.6%)
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Knowledge Cutoff
Training data recency comparison
GPT-4.1 nano
2024-06
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-R1
1 providers
DeepSeek
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GPT-4.1 nano
1 providers
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DeepSeek-R1
Avg Score:62.4%
Providers:1
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GPT-4.1 nano
Avg Score:66.0%(+3.6%)
Providers:1