DeepSeek-R1 vs GPT-4.1 nano
Comparing DeepSeek-R1 and GPT-4.1 nano across benchmarks, pricing, and capabilities.
DeepSeek · OpenAI · Updated for 2026
Which is better?
DeepSeek-R1 and GPT-4.1 nano trade strengths across price, capabilities, and technical limits. The better choice depends on the workload.
On price, GPT-4.1 nano is roughly 5.5x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-4.1 nano also accepts a larger context window (1,047,576 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek-R1
- you need open weights you can self-host or fine-tune
Choose GPT-4.1 nano
- cost matters — it's about 5.5x cheaper per token
- you process long inputs — it offers a 1,047,576 token context window
- you want the most recent training data — it shipped Apr 2025
At a glance
The differences that matter most.
Individual benchmarks
0 reported for DeepSeek-R1 · 24 for GPT-4.1 nano
DeepSeek-R1 and GPT-4.1 nanodon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-R1 ($0.55/1M tokens) is 5.5x more expensive than GPT-4.1 nano ($0.10/1M tokens).
For output processing, DeepSeek-R1 ($2.19/1M tokens) is 5.5x more expensive than GPT-4.1 nano ($0.40/1M tokens).
In conclusion, DeepSeek-R1 is more expensive than GPT-4.1 nano.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-4.1 nano accepts 1,047,576 input tokens compared to DeepSeek-R1's 131,072 tokens. DeepSeek-R1 can generate longer responses up to 131,072 tokens, while GPT-4.1 nano is limited to 32,768 tokens.
Input capabilities
Documented input modalities across available providers
GPT-4.1 nano supports multimodal inputs, whereas DeepSeek-R1 does not.
GPT-4.1 nano can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-R1
GPT-4.1 nano
License
Usage and distribution terms
DeepSeek-R1 is licensed under MIT, while GPT-4.1 nano uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
DeepSeek-R1 was released on 2025-01-20, while GPT-4.1 nano was released on 2025-04-14.
GPT-4.1 nano is 3 months newer than DeepSeek-R1.
Jan 20, 2025
1.7 years ago
Apr 14, 2025
1.5 years ago
2mo newerKnowledge Cutoff
When training data ends
GPT-4.1 nano has a documented knowledge cutoff of 2024-05-31, while DeepSeek-R1's cutoff date is not specified.
We can confirm GPT-4.1 nano's training data extends to 2024-05-31, but cannot make a direct comparison without DeepSeek-R1's cutoff date.
—
May 2024
Provider Availability
DeepSeek-R1 is available from DeepSeek, DeepInfra, Together, Fireworks. GPT-4.1 nano is available from OpenAI.
DeepSeek-R1
GPT-4.1 nano
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-R1 and GPT-4.1 nano side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-R1 vs GPT-4.1 nano.