Model Comparison

DeepSeek-V2.5 vs GPT-4.1 nanoWhich is better in 2026?

DeepSeek-V2.5 significantly outperforms across most benchmarks. DeepSeek-V2.5 and GPT-4.1 nano cost the same.

Verdict: DeepSeek-V2.5 vs GPT-4.1 nano — which is better?

DeepSeek-V2.5 (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-V2.5 outperforms in 1 benchmarks (MMLU), while GPT-4.1 nano is better at 0 benchmarks. DeepSeek-V2.5 significantly outperforms across most benchmarks.

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-V2.5 if…

  • you want the strongest raw capability — it leads on 1 of 1 shared benchmarks
  • 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
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Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

DeepSeek-V2.5 outperforms in 1 benchmarks (MMLU), while GPT-4.1 nano is better at 0 benchmarks.

DeepSeek-V2.5 significantly outperforms across most benchmarks.

Fri Jun 12 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

For input processing, DeepSeek-V2.5 ($0.14/1M tokens) is 1.4x more expensive than GPT-4.1 nano ($0.10/1M tokens).

For output processing, DeepSeek-V2.5 ($0.28/1M tokens) is 1.4x cheaper than GPT-4.1 nano ($0.40/1M tokens).

In conclusion, DeepSeek-V2.5 and GPT-4.1 nano cost the same.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Fri Jun 12 2026 • llm-stats.com
DeepSeek
DeepSeek-V2.5
Input tokens$0.14
Output tokens$0.28
Best providerDeepSeek
OpenAI
GPT-4.1 nano
Input tokens$0.10
Output tokens$0.40
Best providerOpenAI
Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

GPT-4.1 nano accepts 1,047,576 input tokens compared to DeepSeek-V2.5's 8,192 tokens. GPT-4.1 nano can generate longer responses up to 32,768 tokens, while DeepSeek-V2.5 is limited to 8,192 tokens.

DeepSeek
DeepSeek-V2.5
Input8,192 tokens
Output8,192 tokens
OpenAI
GPT-4.1 nano
Input1,047,576 tokens
Output32,768 tokens
Fri Jun 12 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

GPT-4.1 nano supports multimodal inputs, whereas DeepSeek-V2.5 does not.

GPT-4.1 nano can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V2.5

Text
Images
Audio
Video

GPT-4.1 nano

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V2.5 is licensed under deepseek, 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.

DeepSeek-V2.5

deepseek

Open weights

GPT-4.1 nano

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-V2.5 was released on 2024-05-08, while GPT-4.1 nano was released on 2025-04-14.

GPT-4.1 nano is 11 months newer than DeepSeek-V2.5.

DeepSeek-V2.5

May 8, 2024

2.1 years ago

GPT-4.1 nano

Apr 14, 2025

1.2 years ago

11mo newer

Knowledge Cutoff

When training data ends

GPT-4.1 nano has a documented knowledge cutoff of 2024-05-31, while DeepSeek-V2.5'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-V2.5's cutoff date.

DeepSeek-V2.5

—

GPT-4.1 nano

May 2024

Provider Availability

DeepSeek-V2.5 is available from DeepSeek, DeepInfra, Hyperbolic. GPT-4.1 nano is available from OpenAI.

DeepSeek-V2.5

deepseek logo
DeepSeek
Input Price:Input: $0.14/1MOutput Price:Output: $0.28/1M
deepinfra logo
Deepinfra
Input Price:Input: $0.70/1MOutput Price:Output: $1.40/1M
hyperbolic logo
Hyperbolic
Input Price:Input: $2.00/1MOutput Price:Output: $2.00/1M

GPT-4.1 nano

openai logo
OpenAI
Input Price:Input: $0.10/1MOutput Price:Output: $0.40/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

DeepSeek
Less expensive output tokens
Has open weights
Higher MMLU score (80.4% vs 80.1%)
OpenAI
Larger context window (1,047,576 tokens)
Supports multimodal inputs
Less expensive input tokens

Detailed Comparison

AI Model Comparison Table
Feature
DeepSeek
DeepSeek-V2.5
OpenAI
GPT-4.1 nano

FAQ

Common questions about DeepSeek-V2.5 vs GPT-4.1 nano.

Which is better, DeepSeek-V2.5 or GPT-4.1 nano?

DeepSeek-V2.5 significantly outperforms across most benchmarks. DeepSeek-V2.5 is made by DeepSeek and GPT-4.1 nano is made by OpenAI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does DeepSeek-V2.5 compare to GPT-4.1 nano in benchmarks?

DeepSeek-V2.5 scores GSM8k: 95.1%, MT-Bench: 90.2%, HumanEval: 89.0%, BBH: 84.3%, AlignBench: 80.4%. GPT-4.1 nano scores MMLU: 80.1%, IFEval: 74.5%, CharXiv-D: 73.9%, MMMLU: 66.9%, Multi-IF: 57.2%.

Is DeepSeek-V2.5 cheaper than GPT-4.1 nano?

GPT-4.1 nano is 1.4x cheaper for input tokens. DeepSeek-V2.5 costs $0.14/M input and $0.28/M output via deepseek. GPT-4.1 nano costs $0.10/M input and $0.40/M output via openai.

What are the context window sizes for DeepSeek-V2.5 and GPT-4.1 nano?

DeepSeek-V2.5 supports 8K tokens and GPT-4.1 nano supports 1.0M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek-V2.5 and GPT-4.1 nano?

Key differences include context window (8K vs 1.0M), input pricing ($0.14 vs $0.10/M), multimodal support (no vs yes), licensing (deepseek vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V2.5 and GPT-4.1 nano?

DeepSeek-V2.5 is developed by DeepSeek and GPT-4.1 nano is developed by OpenAI.

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