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OpenAI is rolling out GPT-4.1, its new non-reasoning giant language mannequin (LLM) that balances excessive efficiency with decrease value, to customers of ChatGPT. The corporate is starting with its paying subscribers on ChatGPT Plus, Professional, and Group, with Enterprise and Training person entry anticipated within the coming weeks.
It’s additionally including GPT-4.1 mini, which replaces GPT-4o mini because the default for all ChatGPT customers, together with these on the free tier. The “mini” model supplies a smaller-scale parameter and thus, much less highly effective model with comparable security requirements.
The fashions are each obtainable by way of the “extra fashions” dropdown choice within the prime nook of the chat window inside ChatGPT, giving customers flexibility to decide on between GPT-4.1, GPT-4.1 mini, and reasoning fashions corresponding to o3, o4-mini, and o4-mini-high.
Initially supposed to be used solely by third-party software program and AI builders via OpenAI’s software programming interface (API), GPT-4.1 was added to ChatGPT following robust person suggestions.
OpenAI publish coaching analysis lead Michelle Pokrass confirmed on X the shift was pushed by demand, writing: “we had been initially planning on conserving this mannequin api solely however you all wished it in chatgpt 🙂 completely happy coding!”
OpenAI Chief Product Officer Kevin Weil posted on X saying: “We constructed it for builders, so it’s superb at coding and instruction following—give it a strive!”
An enterprise-focused mannequin
GPT-4.1 was designed from the bottom up for enterprise-grade practicality.
Launched in April 2025 alongside GPT-4.1 mini and nano, this mannequin household prioritized developer wants and manufacturing use instances.
GPT-4.1 delivers a 21.4-point enchancment over GPT-4o on the SWE-bench Verified software program engineering benchmark, and a ten.5-point achieve on instruction-following duties in Scale’s MultiChallenge benchmark. It additionally reduces verbosity by 50% in comparison with different fashions, a trait enterprise customers praised throughout early testing.
Context, pace, and mannequin entry
GPT-4.1 helps the usual context home windows for ChatGPT: 8,000 tokens without cost customers, 32,000 tokens for Plus customers, and 128,000 tokens for Professional customers.
Based on developer Angel Bogado posting on X, these limits match these utilized by earlier ChatGPT fashions, although plans are underway to extend context dimension additional.
Whereas the API variations of GPT-4.1 can course of as much as a million tokens, this expanded capability will not be but obtainable in ChatGPT, although future assist has been hinted at.
This prolonged context functionality permits API customers to feed whole codebases or giant authorized and monetary paperwork into the mannequin—helpful for reviewing multi-document contracts or analyzing giant log information.
OpenAI has acknowledged some efficiency degradation with extraordinarily giant inputs, however enterprise take a look at instances counsel strong efficiency as much as a number of hundred thousand tokens.
Evaluations and security
OpenAI has additionally launched a Security Evaluations Hub web site to provide customers entry to key efficiency metrics throughout fashions.
GPT-4.1 exhibits strong outcomes throughout these evaluations. In factual accuracy assessments, it scored 0.40 on the SimpleQA benchmark and 0.63 on PersonQA, outperforming a number of predecessors.
It additionally scored 0.99 on OpenAI’s “not unsafe” measure in normal refusal assessments, and 0.86 on tougher prompts.
Nonetheless, within the StrongReject jailbreak take a look at—a tutorial benchmark for security beneath adversarial situations—GPT-4.1 scored 0.23, behind fashions like GPT-4o-mini and o3.
That mentioned, it scored a powerful 0.96 on human-sourced jailbreak prompts, indicating extra strong real-world security beneath typical use.
In instruction adherence, GPT-4.1 follows OpenAI’s outlined hierarchy (system over developer, developer over person messages) with a rating of 0.71 for resolving system vs. person message conflicts. It additionally performs effectively in safeguarding protected phrases and avoiding resolution giveaways in tutoring situations.
Contextualizing GPT-4.1 towards predecessors
The discharge of GPT-4.1 comes after scrutiny round GPT-4.5, which debuted in February 2025 as a analysis preview. That mannequin emphasised higher unsupervised studying, a richer information base, and decreased hallucinations—falling from 61.8% in GPT-4o to 37.1%. It additionally showcased enhancements in emotional nuance and long-form writing, however many customers discovered the enhancements delicate.
Regardless of these positive factors, GPT-4.5 drew criticism for its excessive value — as much as $180 per million output tokens by way of API —and for underwhelming efficiency in math and coding benchmarks relative to OpenAI’s o-series fashions. Trade figures famous that whereas GPT-4.5 was stronger generally dialog and content material era, it underperformed in developer-specific functions.
Against this, GPT-4.1 is meant as a sooner, extra targeted various. Whereas it lacks GPT-4.5’s breadth of data and in depth emotional modeling, it’s higher tuned for sensible coding help and adheres extra reliably to person directions.
On OpenAI’s API, GPT-4.1 is at present priced at $2.00 per million enter tokens, $0.50 per million cached enter tokens, and $8.00 per million output tokens.
For these looking for a stability between pace and intelligence at a decrease value, GPT-4.1 mini is obtainable at $0.40 per million enter tokens, $0.10 per million cached enter tokens, and $1.60 per million output tokens.
Google’s Flash-Lite and Flash fashions can be found beginning at $0.075–$0.10 per million enter tokens and $0.30–$0.40 per million output tokens, lower than a tenth the price of GPT-4.1’s base charges.
However whereas GPT-4.1 is priced larger, it provides stronger software program engineering benchmarks and extra exact instruction following, which can be crucial for enterprise deployment situations requiring reliability over value. Finally, OpenAI’s GPT-4.1 delivers a premium expertise for precision and growth efficiency, whereas Google’s Gemini fashions enchantment to cost-conscious enterprises needing versatile mannequin tiers and multimodal capabilities.
What It means for enterprise determination makers
The introduction of GPT-4.1 brings particular advantages to enterprise groups managing LLM deployment, orchestration, and information operations:
- AI Engineers overseeing LLM deployment can count on improved pace and instruction adherence. For groups managing the complete LLM lifecycle—from mannequin fine-tuning to troubleshooting—GPT-4.1 provides a extra responsive and environment friendly toolset. It’s significantly appropriate for lean groups beneath stress to ship high-performing fashions shortly with out compromising security or compliance.
- AI orchestration leads targeted on scalable pipeline design will admire GPT-4.1’s robustness towards most user-induced failures and its robust efficiency in message hierarchy assessments. This makes it simpler to combine into orchestration methods that prioritize consistency, mannequin validation, and operational reliability.
- Information engineers liable for sustaining excessive information high quality and integrating new instruments will profit from GPT-4.1’s decrease hallucination fee and better factual accuracy. Its extra predictable output habits aids in constructing reliable information workflows, even when group assets are constrained.
- IT safety professionals tasked with embedding safety throughout DevOps pipelines might discover worth in GPT-4.1’s resistance to widespread jailbreaks and its managed output habits. Whereas its educational jailbreak resistance rating leaves room for enchancment, the mannequin’s excessive efficiency towards human-sourced exploits helps assist secure integration into inner instruments.
Throughout these roles, GPT-4.1’s positioning as a mannequin optimized for readability, compliance, and deployment effectivity makes it a compelling choice for mid-sized enterprises trying to stability efficiency with operational calls for.
A brand new step ahead
Whereas GPT-4.5 represented a scaling milestone in mannequin growth, GPT-4.1 facilities on utility. It isn’t the most costly or probably the most multimodal, however it delivers significant positive factors in areas that matter to enterprises: accuracy, deployment effectivity, and value.
This repositioning displays a broader {industry} development—away from constructing the most important fashions at any value, and towards making succesful fashions extra accessible and adaptable. GPT-4.1 meets that want, providing a versatile, production-ready device for groups making an attempt to embed AI deeper into their enterprise operations.
As OpenAI continues to evolve its mannequin choices, GPT-4.1 represents a step ahead in democratizing superior AI for enterprise environments. For decision-makers balancing functionality with ROI, it provides a clearer path to deployment with out sacrificing efficiency or security.
