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Openai is GPT-4.1 displacementIts new large language model (LLM) not during the season which balances high performance with a lower cost, to Chatgpt users. The company begins with its paid subscribers on Chatgpt Plus, Pro and Team, with the company and access to education users scheduled for the coming weeks.
It also adds GPT-4.1 Mini, which replaces GPT-4O Mini as by default for all chatgpt users, including those of the free level. The “Mini” version provides a smaller parameter and therefore, a less powerful version with similar safety standards.
The models are both available via the “more models” routing in the upper corner of the chat window in Chatgpt, offering users the flexibility to choose between the GPT-4.1, GPT-4.1 models and reasoning models such as O3, O4-Mini and O4-Mini-High.
Initially intended to use it only by third-party software and AI developers via the OPENAI (API) Application Programming Interface, GPT-4.1 was added to Chatgpt after solid user comments.
Place of research on training after OPENAI Michelle Pokrass Confirmed on X The quarter work was motivated by the request, writing: “We initially planned to keep this API model only, but you all wanted it in the Chatppt 🙂 Happy coding!”
Kevin Weil, Director of Openai Chief Products, Posted on X By saying: “We built it for the developers, so it’s very good in coding and in the following instructions – Pass it!”
A company focused on the company
GPT-4.1 was designed from zero for a business quality practice.
Launched in April 2025 alongside GPT-4.1 Mini and Nano, this family of models prioritized the needs of developers and the use of production.
GPT-4.1 offers an improvement of 21.4 points compared to GPT-4O on the Benchmark Swe-Bench Software Engineering, and a gain of 10.5 points on the monitoring of instructions in the multi-Calculist reference of Scale. It also reduces the verbity of 50% compared to other models, a features company praised during early tests.
Context, speed and access of the model
GPT-4.1 Supports standard context Windows for Chatgpt: 8,000 tokens for free users, 32,000 tokens for PLUS users and 128,000 tokens for professional users.
According to the developer Angel Bogado Posting on x, these limits correspond to those used by the previous chatgpt models, although plans are underway to further increase the size of the context.
Although the API versions of GPT-4.1 can treat up to a million tokens, this extended capacity is not yet available in the Chatppt, although future support has been referred.
This extended context capacity allows API users to feed entire code bases or large legal and financial documents in the model – useful for examining contracts with several documents or analyzing large newspaper files.
OPENAI has recognized a certain degradation of performance with extremely important entries, but business test cases suggest solid performance up to several hundred thousand tokens.
Evaluations and security
Openai also launched a Safety assessment hub Website to give users access to key performance measures between models.
GPT-4.1 shows solid results in these assessments. In factual precision tests, he obtained a score of 0.40 on the Simpleqa and 0.63 reference on Personqa, over-performing several predecessors.
He also marked 0.99 on OpenAi’s “non -dangerous” measurement in standard refusal tests and 0.86 on more difficult prompts.
However, in the Strongreject Jailbreak test-an academic reference for security in contradictory conditions-GPT-4.1 marked 0.23, behind models like GPT-4O-MINI and O3.
That said, he obtained a solid 0.96 on prompts from jailbreaks of human origin, indicating real security more robust in typical use.
In instruction membership, GPT-4.1 follows the defined hierarchy of OPENAI (system on the developer, developer on user messages) with a score of 0.71 for system resolution compared to user messages conflicts. It also works well in saving protected sentences and to avoid solution gifts in tutoring scenarios.
Contextualizing GPT-4.1 against predecessors
The release of GPT-4.1 comes after a meticulous exam around GPT-4.5, which made its debut in February 2025 as a research preview. This model has emphasized better not supervised learning, a richer knowledge base and reduces hallucinations – from 61.8% in GPT -4O to 37.1%. He also presented improvements in emotional shades and long writing, but many users have found subtle improvements.
Despite these earnings, GPT -4.5 sparked criticism at its high price – up to $ 180 per million production tokens via the API – and for disappointing performance in mathematics and coding of benchmarks compared to the O -Series of Openai models. Industry figures noted that although the GPT-4.5 was stronger in the general conversation and the generation of content, it subperformed in the applications specific to developers.
On the other hand, GPT-4.1 is designed as a faster and more targeted alternative. Although it lacks the extent of the knowledge of GPT-4.5 and the extended emotional modeling, it is better set for assistance to practical coding and more reliablely adheres to the instructions of users.
On the Openai API, GPT-4.1 is currently at the price At $ 2.00 per million entry tokens, $ 0.50 per million entry into cache and $ 8.00 per million production tokens.
For those looking for a balance between speed and intelligence at a lower cost, GPT-4.1 mini is available at $ 0.40 per million entry tokens, $ 0.10 per million entry into cache and $ 1.60 per million output tokens.
Google Flash-Lite and Flash Models are available from $ 0.075 to $ 0.10 per million entry tokens and $ 0.30 to $ 0.40 per million production tokens, less than the tenth of the cost of basic GPT-4.1.
But although GPT-4.1 is higher, it offers stronger software engineering benchmarks and more precise instructions afterwards, which can be essential for business deployment scenarios requiring reliability of reliability. In the end, OPENAI’s GPT-4.1 offers premium experience for precision and development performance, while Google’s Gemini models use companies concerned with costs of flexible models and multimodal capacities.
What it means for corporate decision -makers
The introduction of GPT-4.1 provides specific advantages to company teams managing LLM deployment, orchestration and data operations:
- AI engineers supervising LLM deployment can expect an improvement in speed and accession to instruction. For teams that manage the complete LLM life cycle – from the model for the model for troubleshooting – GPT -4.1 offers a more reactive and effective set of tools. It is particularly suitable for Lean Under Pressure teams to quickly send highly efficient models without compromising safety or compliance.
- Orchestration ai is Focus on the design of evolutionary pipeline will appreciate the robustness of GPT-4.1 against most of the failures induced by the user and its strong performance in the tests of hierarchy of messages. This facilitates integration into orchestration systems that prioritize consistency, validation of the model and operational reliability.
- Data engineers Responsible for maintaining high quality of data and the integration of new tools will benefit from the lower hallucination rate of GPT-4.1 and higher factual precision. His more foreseeable output behavior helps build reliable data workflows, even when team resources are limited.
- IT security professionals Responsible for incorporating security into the DEVOPS pipelines can find value in the resistance of GPT-4.1 to common jailbreaks and its controlled output behavior. Although its academic jailbreak resistance score gives way to improvement, the high performance of the model against exploits of human origin helps support safe integration into internal tools.
Through these roles, the positioning of GPT-4.1 as an optimized model for clarity, conformity and deployment efficiency makes it a convincing option for medium-sized companies that seek to balance performance with operational requests.
A new step forward
While GPT-4.5 represented a stage of the model development scale, GPT-4.1 focuses on utility. It is not the most expensive or the most multimodal, but it offers significant gains in areas that matter for companies: precision, deployment efficiency and cost.
This repositioning reflects a broader trend in the industry – from the construction of the largest models at all costs and to make the models capable more accessible and adaptable. GPT-4.1 meets this need, offering a flexible tool and ready for production for teams trying to integrate more in-depth AI into their commercial operations.
While Openai continues to evolve its model offers, GPT-4.1 represents a step forward in the democratization of advanced AI for corporate environments. For decision -makers balancing the capacity with the return on investment, it offers a clearer way to deployment without sacrificing performance or security.
