Model Comparison
DeepSeek R1 Distill Qwen 32B vs GPT-4.1 nanoWhich is better in 2026?
DeepSeek R1 Distill Qwen 32B significantly outperforms across most benchmarks. DeepSeek R1 Distill Qwen 32B is 1.3x cheaper per token.
Verdict: DeepSeek R1 Distill Qwen 32B vs GPT-4.1 nano — which is better?
DeepSeek R1 Distill Qwen 32B (by DeepSeek) and GPT-4.1 nano (by OpenAI) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
DeepSeek R1 Distill Qwen 32B outperforms in 2 benchmarks (AIME 2024, GPQA), while GPT-4.1 nano is better at 0 benchmarks. DeepSeek R1 Distill Qwen 32B significantly outperforms across most benchmarks.
On price, DeepSeek R1 Distill Qwen 32B is roughly 1.3x 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.
Choose DeepSeek R1 Distill Qwen 32B if…
- you want the strongest raw capability — it leads on 2 of 2 shared benchmarks
- cost matters — it's about 1.3x cheaper per token
- you need open weights you can self-host or fine-tune
Choose GPT-4.1 nano if…
- you process long inputs — it offers a 1,047,576 token context window
- you want the most recent training data — it shipped Apr 2025
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek R1 Distill Qwen 32B outperforms in 2 benchmarks (AIME 2024, GPQA), while GPT-4.1 nano is better at 0 benchmarks.
DeepSeek R1 Distill Qwen 32B significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek R1 Distill Qwen 32B ($0.12/1M tokens) is 1.2x more expensive than GPT-4.1 nano ($0.10/1M tokens).
For output processing, DeepSeek R1 Distill Qwen 32B ($0.18/1M tokens) is 2.2x cheaper than GPT-4.1 nano ($0.40/1M tokens).
In conclusion, GPT-4.1 nano is more expensive than DeepSeek R1 Distill Qwen 32B.*
* 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 Distill Qwen 32B's 128,000 tokens. DeepSeek R1 Distill Qwen 32B can generate longer responses up to 128,000 tokens, while GPT-4.1 nano is limited to 32,768 tokens.
Input Capabilities
Supported data types and modalities
GPT-4.1 nano supports multimodal inputs, whereas DeepSeek R1 Distill Qwen 32B 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 Distill Qwen 32B
GPT-4.1 nano
License
Usage and distribution terms
DeepSeek R1 Distill Qwen 32B 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 Distill Qwen 32B 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 Distill Qwen 32B.
Jan 20, 2025
1.4 years ago
Apr 14, 2025
1.2 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 Distill Qwen 32B'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 Distill Qwen 32B's cutoff date.
—
May 2024
Provider Availability
DeepSeek R1 Distill Qwen 32B is available from DeepInfra. GPT-4.1 nano is available from OpenAI.
DeepSeek R1 Distill Qwen 32B
GPT-4.1 nano
Outputs Comparison
Key Takeaways
GPT-4.1 nano
View detailsOpenAI
Detailed Comparison
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FAQ
Common questions about DeepSeek R1 Distill Qwen 32B vs GPT-4.1 nano.