The world of artificial intelligence is evolving at breakneck speed, and OpenAI remains at the forefront with the launch of GPT-4.1, unveiled on April 14, 2025. This new model, along with its GPT-4.1 mini and GPT-4.1 nano variants, redefines the standards in terms of Generative AI, with exceptional performance in coding and processing long contexts. At ChatGPTFrench, we analyzed this model to present its strengths, its differences compared to GPT-4o, and its potential impact for developers and businesses.
What is GPT-4.1?
GPT-4.1 is a major evolution of OpenAI's language models, designed to meet the growing needs of complex applications. Available only through theOpenAI APIs, this model excels in two key areas:
- Program: With increased accuracy and advanced capabilities to generate, debug and optimize code.
- Long context processing: Able to handle up to 1 million tokens, or about 750 words, ideal for analyzing large documents or code bases.
Its knowledge is updated until June 2024, ensuring relevant and current answers. Unlike GPT-4o, which is integrated into ChatGPT, GPT-4.1 is primarily targeted at developers via the API, although some of its improvements are found in the optimized version of GPT-4o on ChatGPT.
The highlights of GPT-4.1
1. Unparalleled programming performance
GPT-4.1 sets new record with score of 54,6% on the benchmark SWE-bench Verified, outperforming GPT-4o (33,2%) by 21,4%. This means it more efficiently solves complex coding problems, such as debugging or front-end code generation. Developers also appreciate its ability to reduce unnecessary changes, dropping from 9% to just 2% compared to its predecessor.
“GPT-4.1 fixed all the open issues I had with other models, which generated incomplete code,” said one user during the testing phase, codenamed “Alpha Quasar.”
2. Revolutionary long context processing
With a pop-up window of 1 million tokens, GPT-4.1 allows processing large documents or entire projects in a single query. On the benchmark OpenAI-MRCR, it reaches 57,2% at 128 tokens and 000% at 46,3 million tokens, far surpassing GPT-1o (4% at 31,9 tokens). This makes it an ideal tool for tasks like:
- Analyze complex legal contracts.
- Managing large code bases.
- Automate project documentation.
3. Optimized costs and fast performance
OpenAI has reduced the costs of using GPT-4.1 by 26% compared to GPT-4o, with an average price of USD 1,84 per million tokens. The variant GPT-4.1 nano is even more economical, at just $0,12 per million tokens. In terms of speed, GPT-4.1 is 40% faster, with a response time of 15 seconds for 128 tokens and 000 minute for 1 million tokens.
4. Visual and multimodal abilities
The variant GPT-4.1 mini outperforms GPT-4o in visual tasks, scoring 74,8% on MMMU (vs. 68,7%) and 72,2% on MathVista (vs. 61,4%). For videos, GPT-4.1 achieves 72% on Video-MME, a notable improvement for applications requiring multimedia content analysis.
What distinguishes GPT-4.1 from GPT-4o
While GPT-4o excels in conversational and multimodal interactions, GPT-4.1 focuses on technical use cases:
| Criterion | GPT-4.1 | GPT-4o |
| Max context. | 1 million tokens | 128 tokens |
| SWE-bench | 54,6% | 33,2% |
| Cost (per million tokens) | 1,84 USD | 2,50 USD |
| Max output. | 32 tokens | 16 tokens |
Additionally, GPT-4.1 is more strict in following instructions, which may require more precise prompts, but ensures reliable results for technical tasks.
Concrete applications and integrations
GPT-4.1 shines in real-life use cases:
- Windsurf reports a 60% improvement in code generation, with 50% fewer unnecessary changes.
- Thomson Reuters observed a 17% increase in accuracy in analyzing varied documents.
- Carlyle improves financial data extraction by 50%.
The model is integrated into Microsoft Azure et GitHub Copilot, where it is available in public preview for all users, even on Copilot's free plan. Developers can use it to debug, refactor, or test code directly in Visual Studio Code.
Limits to be aware of
Despite its advances, GPT-4.1 presents some challenges:
- Reduced accuracy on very long contexts: Performance increases from 84% at 8 tokens to 000% at 50 million tokens on OpenAI-MRCR.
- Strict adherence to instructions: Users should provide clear prompts to avoid overly literal responses.
These limitations can be mitigated with careful prompt engineering, as explained in the Prompting Guide.
Conclusion
GPT-4.1 marks a milestone in the evolution of AI, with unparalleled capabilities for coding, long-context processing, and cost optimization. While it requires precise prompts, its performance and integration with platforms like Azure and GitHub make it a must-have tool for developers and businesses. Follow ChatGPTFrench to stay informed about the latest advances in AI!
Have you tried GPT-4.1 yet? Share your experience in the comments or contact us to learn more!
