OpenAI Unveils GPT-4.1 Model Family: A Leap Forward in AI Coding Capabilities

OpenAI continues naming chaos despite CEO acknowledging the habit

On Monday, OpenAI announced the GPT-4.1 model family, its newest series of AI language models that brings a 1 million token context window to OpenAI for the first time and continues a long tradition of very confusing AI model names. Three confusing new names, in fact: GPT‑4.1, GPT‑4.1 mini, and GPT‑4.1 nano. According to OpenAI, these models outperform GPT-4o in several key areas. But in an unusual move, GPT-4.1 will only be available through the developer API, not in the consumer ChatGPT interface where most people interact with OpenAI's technology. The 1 million token context window -- essentially the amount of text the AI can process at once -- allows these models to ingest roughly 3,000 pages of text in a single conversation. This puts OpenAI's context windows on par with Google's Gemini models, which have offered similar extended context capabilities for some time. At the same time, the company announced it will retire the GPT-4.5 Preview model in the API -- a temporary offering launched in February that one critic called a "lemon" -- giving developers until July 2025 to switch to something else. However, it appears GPT-4.5 will stick around in ChatGPT for now. If this sounds confusing, well, that's because it is. OpenAI CEO Sam Altman acknowledged OpenAI's habit of terrible product names in February when discussing the roadmap toward the long-anticipated (and still theoretical) GPT-5. "We realize how complicated our model and product offerings have gotten," Altman wrote on X at the time, referencing a ChatGPT interface already crowded with choices like GPT-4o, various specialized GPT-4o versions, GPT-4o mini, the simulated reasoning o1-pro, o3-mini, and o3-mini-high models, and GPT-4. The stated goal for GPT-5 will be consolidation, a branding move to unify o-series models and GPT-series models. So, how does launching another distinctly numbered model, GPT-4.1, fit into that grand unification plan? It's hard to say. Altman foreshadowed this kind of ambiguity in March 2024, telling Lex Friedman the company had major releases coming but was unsure about names: "before we talk about a GPT-5-like model called that, or not called that, or a little bit worse or a little bit better than what you'd expect..."

OpenAI's new GPT-4.1 AI models focus on coding | TechCrunch

OpenAI on Monday launched a new family of models called GPT-4.1 . Yes, "4.1" -- as if the company's nomenclature wasn't confusing enough already. There's GPT-4.1, GPT-4.1 mini, and GPT-4.1 nano, all of which OpenAI says "excel" at coding and instruction following. Available through OpenAI's API but not ChatGPT, the multimodal models have a 1-million-token context window, meaning they can take in roughly 750,000 words in one go (more than "War and Peace"). GPT-4.1 arrives as OpenAI rivals like Google and Anthropic ratchet up efforts to build sophisticated programming models. Google's recently released Gemini 2.5 Pro, which also has a 1-million-token context window, ranks highly on popular coding benchmarks. So do Anthropic's Claude 3.7 Sonnet and Chinese AI startup DeepSeek's upgraded V3. It's the goal of many tech giants, including OpenAI, to train AI coding models capable of performing complex software engineering tasks. OpenAI's grand ambition is to create an "agentic software engineer," as CFO Sarah Friar put it during a tech summit in London last month. The company asserts its future models will be able to program entire apps end-to-end, handling aspects such as quality assurance, bug testing, and documentation writing. GPT-4.1 is a step in this direction. "We've optimized GPT-4.1 for real-world use based on direct feedback to improve in areas that developers care most about: frontend coding, making fewer extraneous edits, following formats reliably, adhering to response structure and ordering, consistent tool usage, and more," an OpenAI spokesperson told TechCrunch via email. "These improvements enable developers to build agents that are considerably better at real-world software engineering tasks." OpenAI claims the full GPT-4.1 model outperforms its GPT-4o and GPT-4o mini models on coding benchmarks including SWE-bench. GPT-4.1 mini and nano are said to be more efficient and faster at the cost of some accuracy, with OpenAI saying GPT 4.1 nano is its speediest -- and cheapest -- model ever. GPT-4.1 costs $2 per million input tokens and $8 per million output tokens. GPT-4.1 mini is $0.40/M input tokens and $1.60/M output tokens, and GPT-4.1 nano is $0.10/M input tokens and $0.40/M output tokens. According to OpenAI's internal testing, GPT-4.1, which can generate more tokens at once than GPT-4o (32,768 versus 16,384), scored between 52% and 54.6% on SWE-bench Verified, a human-validated subset of SWE-bench. (OpenAI noted in a blog post that some solutions to SWE-bench Verified problems couldn't run on its infrastructure, hence the range of scores.) Those figures are slightly under the scores reported by Google and Anthropic for Gemini 2.5 Pro (63.8%) and Claude 3.7 Sonnet (62.3%), respectively, on the same benchmark. In a separate evaluation, OpenAI probed GPT-4.1 using Video-MME, which is designed to measure the ability of a model to "understand" content in videos. GPT-4.1 reached a chart-topping 72% accuracy on the "long, no subtitles" video category, claims OpenAI. While GPT-4.1 scores reasonably well on benchmarks and has a more recent "knowledge cutoff," giving it a better frame of reference for current events (up to June 2024), it's important to keep in mind that even some of the best models today struggle with tasks that wouldn't trip up experts. For example, many studies have shown that code-generating models often fail to fix, and even introduce, security vulnerabilities and bugs. OpenAI acknowledges, too, that GPT-4.1 becomes less reliable (i.e. likelier to make mistakes) the more input tokens it has to deal with. On one of the company's own tests, OpenAI-MRCR, the model's accuracy decreased from around 84% with 8,000 tokens to 50% with 1,024 tokens. GPT-4.1 also tended to be more "literal" than GPT-4o, says the company, sometimes necessitating more specific, explicit prompts.

OpenAI's New GPT 4.1 Models Excel at Coding

OpenAI announced today that it is releasing a new family of artificial intelligence models optimized to excel at coding, as it ramps up efforts to fend off increasingly stiff competition from companies like Google and Anthropic. The models are available to developers through OpenAI's application programming interface (API). OpenAI is releasing three sizes of models: GPT 4.1, GPT 4.1 Mini, and GPT 4.1 Nano. Kevin Weil, chief product officer at OpenAI, said on a livestream that the new models are better than OpenAI's most widely used model, GPT-4o, and better than its largest and most powerful model, GPT-4.5, in some ways. GPT-4.1 scored 55 percent on SWE-Bench, a widely used benchmark for gauging the prowess of coding models. The score is several percentage points above that of other OpenAI models. The new models are "great at coding, they're great at complex instruction following, they're fantastic for building agents," Weil said. The capacity for AI models to write and edit code has improved significantly in recent months, enabling more automated ways of prototyping software, and improving the abilities of so-called AI agents. In the past few months, rivals like Anthropic and Google have both introduced models that are especially good at writing code. The arrival of GPT-4.1 has been widely rumored in recent weeks. OpenAI apparently tested the model on some popular leaderboards under the pseudonym Alpha Quasar, sources say. Some users of the "stealth" model reported impressive coding abilities. "Quasar fixed all the open issues I had with other code genarated [sic] via llms's which was incomplete," one person wrote on Reddit. "Developers care a lot about coding and we've been improving our model's ability to write functional code," Michelle Pokrass, who works on post-training at OpenAI, said during the Monday livestream. "We've been working on making it follow different formats and better explore repos, run unit tests and write code that compiles." Over the past couple of years, OpenAI has parlayed feverish interest in ChatGPT, a remarkable chatbot first unveiled in late 2022, into a growing business selling access to more advanced chatbots and AI models. In a TED interview last week, Altman said that OpenAI had 500 million weekly active users, and that usage was "growing very rapidly." OpenAI now offers a smorgasbord of different flavors of models with different capabilities and different pricing. The company's largest and most powerful model, called GPT-4.5, was launched in February, though OpenAI called the launch a "research preview" because the product is still experimental. The company also offers models called o1 and o3 that are capable of performing a simulated kind of reasoning, breaking a problem down into parts in order to solve it. These models also take longer to respond to queries and are more expensive for users. ChatGPT's success has inspired an army of imitators, and rival AI players have ramped up their investments in research in an effort to catch up to OpenAI in recent years. A report on the state of AI published by Stanford University this month found that models from Google and DeepSeek now have similar capabilities to models from OpenAI. It also showed a gaggle of other firms including Anthropic, Meta, and the French firm Mistral in close pursuit.

OpenAI Is Reportedly Preparing to Launch GPT-4.1

Imad is a senior reporter covering Google and internet culture. Hailing from Texas, Imad started his journalism career in 2013 and has amassed bylines with The New York Times, The Washington Post, ESPN, Tom's Guide and Wired, among others. OpenAI is preparing to launch GPT-4.1 along with a full version of its o3 reasoning model soon, according to a report from The Verge on Friday. GPT-4.1 will launch along with smaller GPT-4.1 mini and nano versions. This updated model is supposed to be a revamped version of GPT-4o, a multimodal model released last year. The Verge also points to a post on X, the social media site formerly known as Twitter, by Tibor Blaho, an AI engineer at AIPRM. Blago found mentions GPT-4.1 on the OpenAI API Platform. After The Verge posted its article, Blaho also found references to GPT-4.1 on the OpenAI API Platform. Blaho earlier found referrals to "o4-mini" in ChatGPT's web code, indicating that more AI models are coming. OpenAI didn't immediately respond to a request for comment. As the AI race continues, OpenAI has repeatedly made headlines for its ability to introduce more powerful models to an increasing number of users. Last month, OpenAI introduced image generation in ChatGPT-4o, which impressed with its accuracy and realism. The feature became so popular that OpenAI had to set rate limits after CEO Sam Altman posted, "Our GPUs are melting." Earlier this week, OpenAI increased the memory capabilities of ChatGPT so that it could do a better job of recalling information from past conversations. This comes as Google, too, is pushing to lead the AI space with more offerings, including a powerful and efficient new AI chip called Ironwood. The company launched a "practically unlimited" coding assistant for free earlier this year and is currently rolling out Veo 2, a new generator tool to compete with OpenAI's Sora.

OpenAI Launches New GPT-4.1 Models

The release includes three models: GPT-4.1, a smaller GPT-4.1 mini and GPT-4.1 nano. On a livestream announcement, OpenAI chief product officer Kevin Weil called GPT-4.1 nano the developer's "smallest, fastest and cheapest model ever." Developers will be able to access the models through OpenAI's API. The new family of models will only be available through the API for developers. OpenAI said many of the improvements in the new models have been incorporated into GPT-4o for ChatGPT. As the AI race continues, OpenAI has repeatedly made headlines for its ability to introduce more powerful models to an increasing number of users. Last month, OpenAI introduced image generation in ChatGPT-4o, which impressed with its accuracy and realism. The feature became so popular that OpenAI had to set rate limits after CEO Sam Altman posted, "Our GPUs are melting." Last week, OpenAI increased the memory capabilities of ChatGPT so that it could do a better job of recalling information from past conversations. This comes as Google, too, is pushing to lead the AI space with more offerings, including a powerful and efficient new AI chip called Ironwood. The company launched a "practically unlimited" coding assistant for free earlier this year and is currently rolling out Veo 2, a new generator tool to compete with OpenAI's Sora.

GPT-4.1 is here, but not for everyone. Here's who can try the new models

Last week, OpenAI CEO Sam Altman teased that he was dropping a new feature. Paired with reports and spottings of new model art, many speculated it was the long-awaited release of the GPT-4.1 model. It turned out to be a massive ChatGPT update that introduced new memory capabilities. But, now, OpenAI's new family of models has finally arrived. On Monday, via a livestream, OpenAI unveiled a new family of models: GPT-4.1, GPT-4.1 mini, and GPT-4.1 nano. According to OpenAI, the family of models offers improvements in coding, instruction following, and long-context understanding and outperforms GPT-4o and GPT-4o mini "across the board." The models were purpose-built for developers and, as a result, will only be available via the API. Also: OpenAI used to test its AI models for months - now it's days. Why that matters OpenAI says the GPT-4.1 models were built using developer feedback to improve areas they are particularly focused on, such as following reliable formats, adhering to response structure and order, front-end coding, and more. In the X post teasing the release, OpenAI referred to the model as addressing developers' "supermassive black hole." One of the biggest advantages of the models is its reduced latency (lag) despite higher performance on intelligence evaluations, such as the Multilingual (MMLU) benchmark, seen below. Also: ChatGPT's GPT-4 model retires soon - some users can continue to access it Despite these benefits, the models are also cost-effective, addressing a major pain point for developers. OpenAI shared that GPT-4.1 is 26% less expensive than GPT-4o at median queries, and GPT-4.1 is the fastest and cheapest model the company has launched to date. Furthermore, GPT-4.1 mini reduces costs by 83%, according to the blog post. Other advantages include larger context windows, which refer to the amount of tokens (pieces of information) the model can process as input and output. The GPT-4.1 models support up to one million tokens. For reference, the o1 and o3-mini models in the API have a 200K context length, and GPT-4.5 and GPT-4o have a 128K context length. Also: How to use ChatGPT: A beginner's guide to the most popular AI chatbot The long context comprehension, paired with improvements in instruction following, make the GPT-4.1 models "more effective" at powering AI agents, which have been the latest frontier in AI. Simply put, AI agents are AI systems that can do tasks for you independently without being instructed on how to carry out every individual step. To learn more about how the new models fare against the previous models across different benchmarks and specific use cases, visit the detailed blog post where OpenAI posted the results. Since the new models offer similar or improved performance at a lower cost than GPT-4.5, the company also announced it is deprecating GPT-4.5 and focusing on building future models. To give developers ample time to transition, GPT-4.5 Preview will be turned off on July 14, 2025. If you're a typical ChatGPT user and not a developer, there's no need to be disappointed. Also: ChatGPT's GPT-4 model retires soon - some users can continue to access it Although the new GPT-4.1 models will not be available within the ChatGPT model picker, the latest version of GPT-4o in the chatbot includes many of the same improvements, as seen in the changelog description for the March 27 update.

Leak confirms OpenAI's GPT 4.1 is coming before GPT 5.0

OpenAI is working on yet another AI model, reportedly called GPT-4.1, a successor to GPT-4o. The Verge recently reported that OpenAI plans to launch GPT-4.1, which is an upgrade to the existing GPT-4o. And now, we have more reasons to believe the model is indeed coming. As spotted by AI researcher Tibor Blaho, OpenAI is already testing model art for o3, o4-mini, and GPT-4.1 (including nano and mini variants) on the OpenAI API platform. This confirms that GPT-4.1 does exist, but it doesn't appear to be a successor to GPT-4.5. My understanding is that GPT-4.1 is a successor to GPT-4o, which is multimodal. On the other hand, GPT-4.5 focuses more on creativity and delivering better answers. In a "Pre-Training GPT-4.5" video from OpenAI, founder and CEO Sam Altman dropped hints that OpenAI has a team that wants to redo GPT-4 from scratch using new training data and systems. "If you guys could go pick whoever you wanted, what is the smallest team from OpenAI that could go retrain GPT-4 from scratch today with everything we know and have and all the systems work?" Sam said. It's unclear if Altman is referring to the new GPT-4.1 model, but if I were to bet, I'd bet on GPT-4.1. Also, GPT-5 isn't happening anytime soon, as OpenAI plans to focus on o3, o4-mini, o4-mini-high, and GPT-4.1 (including nano and mini variants).

OpenAI's GPT-4.1, 4.1 nano, and 4.1 mini models release imminent

According to references on OpenAI's website, the Microsoft-backed AI startup plans to launch five new models this week, including GPT-4.1, 4.1 nano, and 4.1 mini. BleepingComputer previously reported that OpenAI is working on three new AI models called o4-mini, o4-mini-high and o3. While it's unclear when the reasoning model o4-mini-high is coming or if the plans have changed, OpenAI is now working on GPT-4.1, 4.1 nano, and 4.1 mini. This is according to the updated model art and icons for the model pages on OpenAI's website. As shown in the above screenshot, in the last few hours, OpenAI has added icons for the o3, o4-mini, GPT-4.1, 4.1 nano, and 4.1 mini. models ahead of the launch. These five models might arrive as soon as this week, but this naming convention will be a tad confusing for users. o4-mini and 4.1-mini sound too similar, but they serve different purposes. While o4 is a reasoning model, 4.1 is expected to be a successor to the multimodal GPT-4. At this point, one thing is clear: OpenAI has no plans to launch GPT 5 anytime soon. In addition to new models, my sources tell me that OpenAI is planning to release 4o imagegen model API in some limited form, but it's unclear if the API will be rolled out this week or next week.

ChatGPT 4.1 early benchmarks compared against Google Gemini

ChatGPT 4.1 is now rolling out, and it's a significant leap from GPT 4o, but it fails to beat the benchmark set by Google Gemini. Yesterday, OpenAI confirmed that developers with API access can try as many as three new models: GPT‑4.1, GPT‑4.1 mini, and GPT‑4.1 nano. According to the benchmarks, these models are far better than the existing GPT‑4o and GPT‑4o mini, particularly in coding. For example, GPT‑4.1 scores 54.6% on SWE-bench Verified, which is better than GPT-4o by 21.4% and 26.6% over GPT‑4.5. We have similar results on other benchmarking tools shared by OpenAI, but how does it compete against Gemini models. According to benchmarks shared by Stagehand, which is a production-ready browser automation framework, Gemini 2.0 Flash has the lowest error rate (6.67%) along with the highest exact‑match score (90%), and it's also cheap and fast. On the other hand, GPT‑4.1 has a higher error rate (16.67%) and costs over 10 times more than Gemini 2.0 Flash. Other GPT variants (like "nano" or "mini") are cheaper or faster but not as accurate as GPT-4.1 In another data shared by Pierre Bongrand, who is a scientist working on RNA at Harward, GPT‑4.1 offers poorer cost-effectiveness than competing models. This is an important factor because GPT4.1 is cheaper than ChatGPT 4o. Models like Gemini 2.0 Flash, Gemini 2.5 Pro, and even DeepSeek or o3 mini lie closer to or on the frontier, which suggests they deliver higher performance at a lower or comparable cost. Ultimately, while GPT‑4.1 still works as an option, it's clearly overshadowed by cheaper or more capable alternatives. We're seeing similar results in coding benchmarks, with Aider Polyglot listing GPT-4.1 with a 52% score, while Gemini 2.5 is miles ahead at 73%. It is also important to note that GPT-4.1 is a non-reasoning model, and it's still one of the best models for coding. GPT-4.1 is available via API, but you can use it for free if you sign up for Windsurf AI.

ChatGPT 4.1 fails to beat Google Gemini 2.5 in early benchmarks

ChatGPT 4.1 is now rolling out, and it's a significant leap from GPT 4o, but it fails to beat the benchmark set by Google's most powerful model, Gemini 2.5. Yesterday, OpenAI confirmed that developers with API access can try as many as three new models: GPT‑4.1, GPT‑4.1 mini, and GPT‑4.1 nano. According to the benchmarks, these models are far better than the existing GPT‑4o and GPT‑4o mini, particularly in coding. For example, GPT‑4.1 scores 54.6% on SWE-bench Verified, which is better than GPT-4o by 21.4% and 26.6% over GPT‑4.5. We have similar results on other benchmarking tools shared by OpenAI, but how does it compete against Gemini 2.5 Pro? According to benchmarks shared by Stagehand, which is a production-ready browser automation framework, Gemini 2.0 Flash has the lowest error rate (6.67%) along with the highest exact‑match score (90%), and it's also cheap and fast. On the other hand, GPT‑4.1 has a higher error rate (16.67%) and costs over 10 times more than Gemini 2.0 Flash. Other GPT variants (like "nano" or "mini") are cheaper or faster but not as accurate as GPT-4.1 In another data shared by Pierre Bongrand, who is a scientist working on RNA at Harward, GPT‑4.1 offers poorer cost-effectiveness than competing models. This is an important factor because GPT4.1 is cheaper than ChatGPT 4o. Models like Gemini 2.0 Flash, Gemini 2.5 Pro, and even DeepSeek or o3 mini lie closer to or on the frontier, which suggests they deliver higher performance at a lower or comparable cost. Ultimately, while GPT‑4.1 still works as an option, it's clearly overshadowed by cheaper or more capable alternatives. We're seeing similar results in coding benchmarks, with Aider Polyglot listing GPT-4.1 with a 52% score, while Gemini 2.5 is miles ahead at 73%. Regardless, GPT-4.1 is one of OpenAI's best models for coding, and you can use it for free if you sign up for Windsurf AI, but it's free for only seven days.

OpenAI launches new GPT-4.1 models with improved coding, long context comprehension

April 14 (Reuters) - OpenAI on Monday launched its new AI model GPT-4.1, along with smaller versions GPT-4.1 mini and GPT-4.1 nano, touting major improvements in coding, instruction following, and long context comprehension. The new models, available only on OpenAI's application programming interface (API), outperform the company's most advanced GPT-4o model across the board, the ChatGPT maker said. With improved context understanding, they can support up to 1 million "tokens" -- a term that refers to the units of data processed by an AI model. The models are also equipped with refreshed knowledge up to June 2024. GPT-4.1 showed a 21% improvement over GPT-4o and 27% over GPT-4.5 on coding. Meanwhile, the improvements in instruction following and long context comprehension also make the GPT-4.1 models more effective at powering AI agents. "Benchmarks are strong, but we focused on real-world utility, and developers seem very happy," CEO Sam Altman said in a post on social media platform X. The family of models also operate at a "much lower cost" compared to GPT-4.5, OpenAI said. The company added it would turn off the GPT-4.5 preview that is available in the API in July, as the new models offer "improved or similar performance." OpenAI in February released the GPT-4.5 research preview for some users and developers and announced plans to expand access in subsequent weeks. Reporting by Deborah Sophia in Bengaluru; Editing by Alan Barona Our Standards: The Thomson Reuters Trust Principles., opens new tab Suggested Topics:Artificial Intelligence

ChatGPT's Updated AI Models Can Accept More Text

ChatGPT's Image Gen Still Hasn't Fixed My Favorite Scheduled Task OpenAI has just introduced GPT-4.1, a new set of AI models built to be especially good at coding and following instructions. This release includes the usable GPT-4.1, GPT-4.1 mini, and GPT-4.1 nano, all available through OpenAI's API but not yet part of ChatGPT. A major part of this upgrade is the models' ability to handle much longer inputs. They can now handle up to 1 million tokens, which is roughly 750,000 words at once. This is a big jump from earlier models and means they can work with much more complex and lengthy information. That's not a guarantee that it will remember it all; it can just take all that information. The main goal of GPT-4.1 is to be better at coding. OpenAI has fine-tuned these models based on what developers asked for, focusing on things like front-end programming, reducing unnecessary changes, sticking to the right formats, and using tools correctly. Tests from OpenAI show that GPT-4.1 does better than older versions like GPT-4.0 and GPT-4.0 mini on coding challenges such as SWE-bench. In one SWE-bench verified test, where humans double-check the results, GPT-4.1 scored between 52% and 54.6%. That's an improvement, though still a bit behind Google's Gemini 2.5 Pro (63.8%) and Anthropic's Claude 3.7 Sonnet (62.3%). The smaller models, GPT-4.1 mini and nano, are faster and cheaper but slightly less accurate, with GPT-4.1 nano being OpenAI's quickest and most budget-friendly option yet. I've tried to use Chat GPT for coding, and it never ended up being what I needed. The system forgot things, and it generally wasn't a fun experience. Based on my experience alone, where I have a small amount of experience with programming, I'd say that an upgrade is really needed for ChatGPT. Besides coding, GPT-4.1 is also better at understanding videos and images. In OpenAI's own tests for video comprehension (called Video-MME), GPT-4.1 scored 72% accuracy in the "long, no subtitles" category, showing it can grasp complex visual information well. Pricing varies based on performance. OpenAI says that GPT-4.1 is more cost-effective than its predecessor, GPT-4.0. It's worth noting that OpenAI is phasing out GPT-4.5 from its API starting July 14, 2025. GPT-4.5 was apparently OpenAI's biggest model and did well in writing and persuasion, but it was very expensive, so OpenAI is dropping it in favor of GPT-4.1 as a more affordable alternative. However, GPT-4.5 will still be available in ChatGPT's research preview for paying users. The launch of GPT-4.1 and the removal of GPT-4.5 are great examples of bigger, not always being better. I would think that a good idea is to have separate LLMs that handle different needs of users. Otherwise, there's a lot of time wasted making sure the correct output is given. GPT-4.1's better coding skills, lower price, and huge input capacity make this particular AI more practical for developers. The ability to process much longer texts is especially important, as coding takes up many tokens. This isn't something that the average user would need. That said, there are still challenges. OpenAI even admitted that GPT-4.1 will become less reliable as inputs get longer. AIs have difficulty keeping track of a lot of information and knowing which is relevant and which isn't. While it's good at generating code, AI-written code can still have security risks, bugs, and more, so careful testing and updates are necessary. The GPT-4.1 models are a big improvement, especially for coding and handling videos. They may not beat every competitor in every test, but it's more about specific use than being good in every aspect. You can try GPT 4.1 on the official website if you have an account with OpenAI. Sources: TechCrunch, OpenAI

OpenAI launches another model before GPT 5 -- here's what this one can do

AI models seem to be dropping left, right and center right now, with the latest coming from OpenAI. No, they haven't finally released GPT-5, instead, they've complicated the naming system even further with the release of GPT-4.1. In fact, there are actually three new versions: GPT-4.1, GPT-4.1 mini and GPT-4.1 Nano. However, for most people, these models won't be particularly helpful, with OpenAI stating they excel in coding abilities. The GPT-4.1 series won't be available via ChatGPT but instead via OpenAI's API system (a platform for making AI products through OpenAI). These models have a 1-million-token context window. This means they can absorb roughly 750,000 words (more than all of the Lord of the Rings books and the Hobbit put together). OpenAI, along with its competitors like Google and Anthropic, is building two kinds of models right now. On one side are the consumer versions, like ChatGPT and Gemini, and on the other are programming and reasoning models built with more power and the ability to take on more complex challenges. This side of OpenAI's market is pretty niche in terms of who will be using the models. Coders and researchers will be making full use of the GPT-4.1 series, looking to these models to better understand the inner workings of AI and using its brains to accomplish complex coding tasks. However, while this won't directly affect most of us, it does show the development being made by OpenAI. Most noticeably, the ability for its models to take in large amounts of contextual data with higher token limits. These are also some of OpenAI's fastest models to date, showing the potential for faster models in the future, even when dealing with more complex tasks. OpenAI has, for a long time now, been promising the release of GPT-5. This would be the next powerhouse behind ChatGPT and in theory, the biggest update OpenAI has released in a very long time. Addressing the mess that is their naming system recently, Sam Altman, CEO of OpenAI stated on X "How about we fix our model naming by this summer and everyone gets a few more months to make fun of us (which we very much deserve) until then?" Aside from accepting the name blame here, it seems Altman is hinting towards a move forward for naming, or in other words, the start of GPT-5. This would line up well with previous hints toward release dates, and as long as there are no delays or surprises, we may see the launch of GPT-5 in the next couple of months.

OpenAI just launched new GPT 4.1 model ahead of GPT 5 -- here's what it can do

AI models seem to be dropping left, right and center right now, with the latest coming from OpenAI. No, they haven't finally released GPT-5, instead, they've complicated the naming system even further with the release of GPT-4.1. In fact, there are actually three new versions: GPT-4.1, GPT-4.1 mini and GPT-4.1 Nano. However, for most people, these models won't be particularly helpful, with OpenAI stating they excel in coding abilities. The GPT-4.1 series won't be available via ChatGPT but instead via OpenAI's API system (a platform for making AI products through OpenAI). These models have a 1-million-token context window. This means they can absorb roughly 750,000 words (more than all of the Lord of the Rings books and the Hobbit put together). OpenAI, along with its competitors like Google and Anthropic, is building two kinds of models right now. On one side are the consumer versions, like ChatGPT and Gemini, and on the other are programming and reasoning models built with more power and the ability to take on more complex challenges. This side of OpenAI's market is pretty niche in terms of who will be using the models. Coders and researchers will be making full use of the GPT-4.1 series, looking to these models to better understand the inner workings of AI and using its brains to accomplish complex coding tasks. However, while this won't directly affect most of us, it does show the development being made by OpenAI. Most noticeably, the ability for its models to take in large amounts of contextual data with higher token limits. These are also some of OpenAI's fastest models to date, showing the potential for faster models in the future, even when dealing with more complex tasks. OpenAI has, for a long time now, been promising the release of GPT-5. This would be the next powerhouse behind ChatGPT and in theory, the biggest update OpenAI has released in a very long time. Addressing the mess that is their naming system recently, Sam Altman, CEO of OpenAI stated on X "How about we fix our model naming by this summer and everyone gets a few more months to make fun of us (which we very much deserve) until then?" Aside from accepting the name blame here, it seems Altman is hinting towards a move forward for naming, or in other words, the start of GPT-5. This would line up well with previous hints toward release dates, and as long as there are no delays or surprises, we may see the launch of GPT-5 in the next couple of months.

OpenAI slashes prices for GPT-4.1, igniting AI price war among tech giants

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More OpenAI released GPT-4.1 this morning, directly challenging competitors Anthropic, Google and xAI.By ramping up its coding and context-handling capabilities to a whopping one-million-token window and aggressively cutting API prices, GPT-4.1 is positioning itself as the go-to generative AI model. If you're managing budgets or crafting code at scale, this pricing shake-up might just make your quarter. Performance upgrades at Costco prices The new GPT-4.1 series boasts serious upgrades, including a 54.6% win rate on the SWE-bench coding benchmark, marking a considerable leap from prior versions. But the buzz isn't just about better benchmarks. Real-world tests by Qodo.ai on actual GitHub pull requests showed GPT-4.1 beating Anthropic's Claude 3.7 Sonnet in 54.9% of cases, primarily thanks to fewer false positives and more precise, relevant code suggestions.. OpenAI's new pricing structure -- openly targeting affordability -- might finally tip the scales for teams wary of runaway AI expenses: The standout here? That generous 75% caching discount, effectively incentivizing developers to optimize prompt reuse -- particularly beneficial for iterative coding and conversational agents. Feeling the heat Anthropic's Claude models have established their footing by balancing power and cost. But GPT-4.1's bold pricing undercuts their market position significantly: Anthropic still offers compelling caching discounts (up to 90% in some scenarios), but GPT-4.1's base pricing advantage and developer-centric caching improvements position OpenAI as a budget-friendlier choice -- particularly appealing for startups and smaller teams. Hidden financial pitfalls Gemini's pricing complexity is becoming increasingly notorious in developer circles. According to Prompt Shield's Gemini's tiered structure -- especially with the powerful 2.5 Pro variant -- can quickly escalate into financial nightmares due to surcharges for lengthy inputs and outputs that double past certain context thresholds: Moreover, Gemini lacks an automatic billing shutdown, which Prompt Shield says exposes developers to Denial-of-Wallet attacks -- malicious requests designed to deliberately inflate your cloud bill, which Gemini's current safeguards don't fully mitigate. GPT-4.1's predictable, no-surprise pricing seems to be a strategic counter to Gemini's complexity and hidden risks. Context is king xAI's Grok series, championed by Elon Musk, recently unveiled its API pricing for its latest models last week: One complicating factor with Grok has been its context window. Musk touted that Grok 3 could handle 1 million tokens (similar to GPT-4.1's claim), but the current API actually maxes out at 131k tokens, well short of that promise. This discrepancy drew some criticism from users on X, pointing to a bit of overzealous marketing on xAI's part. For developers evaluating Grok vs. GPT-4.1, this is notable: GPT-4.1 offers the full 1M context as advertised, whereas Grok's API might not (at least at launch). In terms of pricing transparency, xAI's model is straightforward on paper, but the limitations and the need to pay more for "fast" service show the trade-offs of a smaller player trying to compete with industry giants. Windsurf bets big on GPT-4.1's developer appeal Demonstrating high confidence in GPT-4.1's practical advantages, Windsurf -- the AI-powered IDE -- has offered an unprecedented free, unlimited GPT-4.1 trial for a week. This isn't mere generosity; it's a strategic gamble that once developers experience GPT-4.1's capabilities and cost savings firsthand, reverting to pricier or less capable models will be a tough sell. A new era of competitive AI pricing OpenAI's GPT-4.1 isn't just shaking up the pricing game, it's potentially setting new standards for the AI development community. With precise, reliable outputs verified by external benchmarks, simple pricing transparency, and built-in protections against runaway costs, GPT-4.1 makes a persuasive case for being the default choice in closed-model APIs. Developers should brace themselves -- not just for cheaper AI, but for the domino effect this pricing revolution might trigger as Anthropic, Google, and xAI scramble to keep pace. For teams previously limited by cost, complexity, or both, GPT-4.1 might just be the catalyst for a new wave of AI-powered innovation.

OpenAI's new GPT-4.1 models can process a million tokens and solve coding problems better than ever

OpenAI launched a new family of AI models this morning that significantly improve coding abilities while cutting costs, responding directly to growing competition in the enterprise AI market. The San Francisco-based AI company introduced three models -- GPT-4.1, GPT-4.1 mini, and GPT-4.1 nano -- all available immediately through its API. The new lineup performs better at software engineering tasks, follows instructions more precisely, and can process up to one million tokens of context, equivalent to about 750,000 words. "GPT-4.1 offers exceptional performance at a lower cost," said Kevin Weil, chief product officer at OpenAI, during Monday's announcement. "These models are better than GPT-4o on just about every dimension." Perhaps most significant for enterprise customers is the pricing: GPT-4.1 will cost 26% less than its predecessor, while the lightweight nano version becomes OpenAI's most affordable offering at just 12 cents per million tokens. How GPT-4.1's improvements target enterprise developers' biggest pain points In a candid interview with VentureBeat, Michelle Pokrass, post training research lead at OpenAI, emphasized that practical business applications drove the development process. "GPT-4.1 was trained with one goal: being useful for developers," Pokrass told VentureBeat. "We've found GPT-4.1 is much better at following the kinds of instructions that enterprises use in practice, which makes it much easier to deploy production-ready applications." This focus on real-world utility is reflected in benchmark results. On SWE-bench Verified, which measures software engineering capabilities, GPT-4.1 scored 54.6% -- a substantial 21.4 percentage point improvement over GPT-4o. For businesses developing AI agents that work independently on complex tasks, the improvements in instruction following are particularly valuable. On Scale's MultiChallenge benchmark, GPT-4.1 scored 38.3%, outperforming GPT-4o by 10.5 percentage points. Why OpenAI's three-tiered model strategy challenges competitors like Google and Anthropic The introduction of three distinct models at different price points addresses the diversifying AI marketplace. The flagship GPT-4.1 targets complex enterprise applications, while mini and nano versions address use cases where speed and cost efficiency are priorities. "Not all tasks need the most intelligence or top capabilities," Pokrass told VentureBeat. "Nano is going to be a workhorse model for use cases like autocomplete, classification, data extraction, or anything else where speed is the top concern." Simultaneously, OpenAI announced plans to deprecate GPT-4.5 Preview -- its largest and most expensive model released just two months ago -- from its API by July 14. The company positioned GPT-4.1 as a more cost-effective replacement that delivers "improved or similar performance on many key capabilities at much lower cost and latency." This move allows OpenAI to reclaim computing resources while providing developers a more efficient alternative to its costliest offering, which had been priced at $75 per million input tokens and $150 per million output tokens. Real-world results: How Thomson Reuters, Carlyle and Windsurf are leveraging GPT-4.1 Several enterprise customers who tested the models prior to launch reported substantial improvements in their specific domains. Thomson Reuters saw a 17% improvement in multi-document review accuracy when using GPT-4.1 with its legal AI assistant, CoCounsel. This enhancement is particularly valuable for complex legal workflows involving lengthy documents with nuanced relationships between clauses. Financial firm Carlyle reported 50% better performance on extracting granular financial data from dense documents -- a critical capability for investment analysis and decision-making. Varun Mohan, CEO of coding tool provider Windsurf (formerly Codeium), shared detailed performance metrics during the announcement. "We found that GPT-4.1 reduces the number of times that it needs to read unnecessary files by 40% compared to other leading models, and also modifies unnecessary files 70% less," Mohan said. "The model is also surprisingly less verbose... GPT-4.1 is 50% less verbose than other leading models." Million-token context: What businesses can do with 8x more processing capacity All three models feature a context window of one million tokens -- eight times larger than GPT-4o's 128,000 token limit. This expanded capacity allows the models to process multiple lengthy documents or entire codebases at once. In a demonstration, OpenAI showed GPT-4.1 analyzing a 450,000-token NASA server log file from 1995, identifying an anomalous entry hiding deep within the data. This capability is particularly valuable for tasks involving large datasets, such as code repositories or corporate document collections. However, OpenAI acknowledges performance degradation with extremely large inputs. On its internal OpenAI-MRCR test, accuracy dropped from around 84% with 8,000 tokens to 50% with one million tokens. How the enterprise AI landscape is shifting as Google, Anthropic and OpenAI compete for developers The release comes as competition in the enterprise AI space heats up. Google recently launched Gemini 2.5 Pro with a comparable one-million-token context window, while Anthropic's Claude 3.7 Sonnet has gained traction with businesses seeking alternatives to OpenAI's offerings. Chinese AI startup DeepSeek also recently upgraded its models, putting additional pressure on OpenAI to maintain its leadership position. "It's been really cool to see how improvements in long context understanding have translated into better performance on specific verticals like legal analysis and extracting financial data," Pokrass said. "We've found it's critical to test our models beyond the academic benchmarks and make sure they perform well with enterprises and developers." What's next: OpenAI's focus on practical AI tools for businesses and developers By releasing these models specifically through its API rather than ChatGPT, OpenAI signals its commitment to developers and enterprise customers. The company plans to gradually incorporate features from GPT-4.1 into ChatGPT over time, but the primary focus remains on providing robust tools for businesses building specialized applications. To encourage further research in long-context processing, OpenAI is releasing two evaluation datasets: OpenAI-MRCR for testing multi-round coreference abilities and Graphwalks for evaluating complex reasoning across lengthy documents. For enterprise decision-makers, the GPT-4.1 family offers a more practical, cost-effective approach to AI implementation. As organizations continue integrating AI into their operations, these improvements in reliability, specificity, and efficiency could accelerate adoption across industries still weighing implementation costs against potential benefits. While competitors chase larger, costlier models, OpenAI's strategic pivot with GPT-4.1 suggests the future of AI may not belong to the biggest models, but to the most efficient ones. The real breakthrough may not be in the benchmarks, but in bringing enterprise-grade AI within reach of more businesses than ever before.

OpenAI Releases GPT-4.1: Why This Super-Powered AI Model Will Kill GPT-4.5 - Decrypt

OpenAI unveiled GPT-4.1 on Monday, a trio of new AI models with context windows of up to one million tokens -- enough to process entire codebases or small novels in one go. The lineup includes standard GPT-4.1, Mini, and Nano variants, all targeting developers. The company's latest offering comes just weeks after releasing GPT-4.5, creating a timeline that makes about as much sense as the release order of the Star Wars movies. "The decision to name these 4.1 was intentional. I mean, it's not just that we're bad at naming," OpenAI product lead Kevin Weil said during the announcement -- but we are still trying to find out what those intentions were. GPT-4.1 shows pretty interesting capabilities. According to OpenAI, it achieved 55% accuracy on the SWEBench coding benchmark (up from GPT-4o's 33%) while costing 26% less. The new Nano variant, billed as the company's "smallest, fastest, cheapest model ever," runs at just 12 cents per million tokens. Also, OpenAI won't upcharge for processing massive documents and actually using the one million token context. "There is no pricing bump for long context," Kevin emphasized. The new models show impressive performance improvements. In a live demonstration, GPT-4.1 generated a complete web application that could analyze a 450,000-token NASA server log file from 1995. openAI claims the model passes this test with nearly 100% accuracy even at million tokens of context. Michelle, OpenAI's post-training research lead, also showcased the models' enhanced instruction-following abilities. "The model follows all your instructions to the tea," she said, as GPT-4.1 dutifully adhered to complex formatting requirements without the usual AI tendency to "creatively interpret" directions. The release of GPT-4.1 after GPT-4.5 feels like watching someone count "5, 6, 4, 7" with a straight face. It's the latest chapter in OpenAI's bizarre versioning saga. After releasing GPT-4 it upgraded the model with multimodal capabilities. The company decided to call that new model GPT-4o ("o" for "omni"), a name that could be also be read as "four zero" depending on the font you use Then, OpenAI introduced a reasoning-focused model that was just called "o." But don't confuse OpenAI's GPT-4o with OpenAI's o because they are not the same. Nobody knows why they picked this name, but as a general rule of thumb, GPT-4o was a "normal" LLM whereas OpenAI o1 was a reasoning model. "You would think logically (our new model) maybe should have been called o2, but out of respect to our friends at Telefonica -- and in the grand tradition of open AI being really truly bad at names -- it's going to be called o3," Sam Altman said during the model's announcement. The lineup further fragments with variants like the normal o3 and a smaller more efficient version called o3 mini. However, they also released a model named "OpenAI o3 mini-high" which puts two absolute antonyms next to each other because AI can do miraculous things.In essence, OpenAI o3 mini-high is a more powerful version than o3 mini, but not as powerful as OpenAI o3 -- which is referenced in a single chart by Openai as "o3 (Medium)," as it should be. Right now ChatGPT users can select either OpenAI o3 mini or OpenAI o3 mini high. The normal version is nowhere to be found. Also, we don't want to confuse you anymore, but OpenAI already announced plans to release o4 soon. But, of course, don't confuse o4 with 4o because they are absolutely not the same: o4 reasons -- 4o does not. Now, let's go back to the newly announced GPT-4.1. The model is so good, it is going to kill GPT-4.5 soon, making that model the shortest living LLM in the history of ChatGPT. "We're announcing that we're going to be deprecating GPT-4.5 in the API," Kevin declared, giving developers a three-month deadline to switch. "We really do need those GPUs back," he added, confirming that even OpenAI can't escape the silicon shortage that's plaguing the industry. At this rate, we're bound to see GPT-π or GPT-4.√2 before the year ends -- but hey, at least they get better with time, no matter the names. The models are already available via API and in OpenAI's playground, and won't be available in the user-friendly ChatGPT UI -- at least not yet.

OpenAI launches new GPT-4.1 models with improved coding

The new models, available only on OpenAI's application programming interface (API), outperform the company's most advanced GPT-4o model across the board, the ChatGPT maker said. With improved context understanding, they can support up to 1 million "tokens" -- a term that refers to the units of data processed by an AI model. The models are also equipped with refreshed knowledge up to June 2024. GPT-4.1 showed a 21% improvement over GPT-4o and 27% over GPT-4.5 on coding. Meanwhile, the improvements in instruction following and long context comprehension also make the GPT-4.1 models more effective at powering AI agents.

OpenAI introduces latest AI model, the GPT-4.1

The platform also claims that this version of its technology is cheaper to make and more efficient than previous models. OpenAI has announced the predecessor to its GPT-4o multimodal AI model, GPT-4.1, which the platform described as "featuring major improvements on coding, instruction following and long context, plus [their] first-ever nano model". According to OpenAI, the new version of its AI-powered technology outperforms previous releases, with significant improvements and a larger context window, supporting bigger prompts and incorporating more information, for the user. The announcement also states that this is OpenAI's fastest and cheapest model to date, which is a significant step for the organisation considering the controversy around recent Deepseek innovations and accusations made by OpenAI, that the Chinese start-up had created its technology using OpenAI materials, at a fraction of the cost. In a statement, OpenAI said, "GPT‑4.1 is a significant step forward in the practical application of AI. By focusing closely on real-world developer needs, ranging from coding to instruction following and long context understanding, these models unlock new possibilities for building intelligent systems and sophisticated agentic applications. We're continually inspired by the developer community's creativity, and are excited to see what you build with GPT‑4.1." OpenAI isn't the only organisation testing the waters with AI innovations. It was recently reported by Bloomberg that streaming platform Netflix is trying out an AI-powered search engine that enables a user to search for content based on specifics such as mood. The feature is currently available to some iOS users in Australia and New Zealand, with a spokesperson having told reporters at The Verge, that it will likely expand into the US in the coming weeks and months. OpenAI also recently raised $40bn via a funding round, in what is thought to be the largest private tech funding round ever. In a statement released by OpenAI, a representative said the new funding would go towards pushing the frontiers of AI research, scaling computing infrastructure and delivering more tools and technologies to ChatGPTs users. Don't miss out on the knowledge you need to succeed. Sign up for the Daily Brief, Silicon Republic's digest of need-to-know sci-tech news.

OpenAI Unveils GPT-4.1 Models in API Specifically for Coding | AIM Media House

These advancements are expected to facilitate the development of more capable AI agents that can independently handle tasks. OpenAI has launched its next generation of LLMs -- the GPT-4.1 family, comprising GPT-4.1, GPT-4.1 mini, and GPT-4.1 nano. These new models surpass the capabilities of GPT-4o and GPT-4o mini, showcasing significant advancements in coding, instruction following, and long context comprehension, all while offering lower costs and reduced latency. The new models are available immediately via the API, with GPT-4.1 priced at $2.00 per 1 million input tokens and $8.00 per 1 million output tokens. GPT-4.1 mini costs $0.40 and $1.60, respectively, and GPT-4.1 nano is priced at $0.10 and $0.40. OpenAI is also increasing the discount for repeated context use to 75% for these new models. "GPT‑4.1 is a significant step forward in the practical application of AI," OpenAI said in its announcement. The models feature an expanded context window of up to 1 million tokens and incorporate knowledge up to June 2024. In coding proficiency, GPT-4.1 achieved a 54.6% score on the SWE-bench Verified benchmark, an improvement of 21.4 percentage points over GPT‑4o. Its ability to follow instructions also saw gains, scoring 38.3% on the Scale MultiChallenge benchmark, a 10.5 percentage point increase over GPT‑4o. For understanding long sequences of information, GPT-4.1 reached a new high of 72.0% on the Video-MME benchmark. The GPT-4.1 family also emphasises efficiency. GPT-4.1 mini "matches or exceeds GPT‑4o in intelligence evaluations while reducing latency by nearly half and reducing cost by 83%", OpenAI further said. In the 4.1 family, GPT-4.1 nano is the fastest and cheapest model available for tasks that need quick responses. It has a 1 million token context window and performs well in tasks like classification and autocompletion. These advancements are expected to facilitate the development of more capable AI agents that can independently handle tasks. "Developers can now build agents that are more useful and reliable at real-world software engineering, extracting insights from large documents, resolving customer requests with minimal hand-holding, and other complex tasks," the company stated. It is important to note that GPT-4.1 will be accessible solely through the API. OpenAI clarified that many of the improvements in instruction following, coding, and intelligence have been gradually incorporated into the latest version of GPT‑4o within ChatGPT. OpenAI also announced the upcoming discontinuation of GPT-4.5 Preview in the API, scheduled for July 14, 2025. This decision was made because "GPT‑4.1 offers improved or similar performance on many key capabilities at much lower cost and latency". Early testing by various companies has yielded positive results. According to the company, Windsurf reported that GPT-4.1 scores "60% higher than GPT‑4o on Windsurf's internal coding benchmark", leading to "faster iteration and smoother workflows". Moreover, Qodo found that GPT-4.1 produced better suggestions in 55% of cases for code reviews. BlueJ noted a 53% more accurate performance on complex tax scenarios, while Hex observed nearly two times more improvement on challenging SQL evaluations. Thomson Reuters experienced a 17% improvement in multi-document review accuracy, while Carlyle reported 50% better retrieval from large, data-rich documents.

OpenAI Releases GPT-4.1, A New Family of Models Designed for Coding

OpenAI's lineup of powerful AI models is growing. Today, the company behind ChatGPT has announced the GPT-4.1 "model family," a collection of three new AI models "purpose-built for developers." The models can now be used via OpenAI's API. According to OpenAI, the GPT-4.1 family will consist of three models: the normal-sized GPT-4.1, the smaller and more modestly-priced GPT-4.1 mini, and the even smaller and cheaper GPT-4.1 nano. These models will only be available through OpenAI's API, and can't be accessed through ChatGPT's model picker. OpenAI says this is because the latest version of its GPT-4o model incorporates many of the same improvements in ChatGPT. The GPT-4.1 models have been trained on data with a knowledge cutoff of June 2024, and are said to outperform OpenAI's top models at coding, effectively following complex instructions, and understanding large datasets. If developers want their AI applications to access more current information, they'll need to connect the model to the internet. The GPT-4.1 models will also be able to process up to one million tokens of context at a time, significantly more than models from Google and OpenAI rival Anthropic. OpenAI says that the new GPT-4.1 models have been optimized to help software developers in coding and programming. The company adds that models will assist in frontend coding, will make fewer extraneous edits to code, and follow formats and structures more reliably. AI-assisted coding is one of the most common use cases for generative AI, and has been a focus for Anthropic.

OpenAI Releases Coding-Focused GPT-4.1 Series AI Models in API

OpenAI said these models come with a context window of one million tokens OpenAI released three new artificial intelligence (AI) models on Monday. Staying true to its unusual naming convention, the company called this the GPT-4.1 family of AI models. There are three variants -- GPT-4.1, GPT-4.1 mini, and GPT-4.1 nano. The San Francisco-based AI firm said that these models outperform the GPT-4o and GPT-4o mini across several metrics, with a significant improvement in coding and instruction following. Notably, these new large language models (LLMs) are only available to developers via an application programming interface (API), and will not be accessible via ChatGPT. In a post, OpenAI announced the release of the GPT-4.1 series of AI models. These API-exclusive models get several upgrades over the GPT-4o models, including higher performance, increased context window, and improved pricing. The knowledge cutoff of these models has also been upgraded to June 2024. OpenAI said that these models were designed for coding-related tasks and actions that require higher instruction adherence. Highlighting the coding proficiency, OpenAI claimed GPT-4.1 scored 54.6 percent on the SWE-bench Verified. This score is higher than both GPT-4o and the recently released GPT-4.5, making 4.1 the company's leading model for coding. GPT-4.1 also scored 38.3 percent on the MultiChallenge benchmark for instruction following, and 72 percent on the Video-MME benchmark for multimodal long context understanding, the company claimed. Notably, all the AI models in the series have a context window of up to one million tokens. While GPT-4.1 remains the premium model of this series, the GPT-4.1 mini is also claimed to outperform GPT-4o in several benchmarks, including intelligence evaluations. OpenAI said the mini model reduces latency by half and costs 83 percent less compared to 4o. The AI firm is also pitching the GPT-4.1 nano as the best model for low latency tasks. With an 80.1 percent score on MMLU, 50.3 percent score on GPQA, and 9.8 percent on the Aider polyglot coding, OpenAI says the AI model fares better than the GPT-4o mini model. OpenAI also highlighted that the improved instruction following and the long context window also make these models an option in powering AI agents. Coming to pricing, the GPT-4.1 costs $2 (roughly Rs. 171) per million input tokens and $8 (roughly Rs. 685) per million output tokens. The mini variant is priced at $0.40 (roughly Rs. 34) per million input tokens and $1.60 (roughly Rs. 137) per million output tokens. And, the cheapest nano model will cost developers $0.10 (roughly Rs. 8.5) per million input tokens and $0.40 (roughly Rs. 34) per million output tokens. Notably, the GPT-4.1 series of AI models will only be available via API to developers. However, the AI firm stated that the improvements of these models will be transitioned into the latest version of GPT-4o, which is available in ChatGPT.

OpenAI launches GPT-4.1 with enhanced coding capabilities

OpenAI has just rolled out its latest flagship model, GPT-4.1, along with two lighter versions -- GPT-4.1 mini and nano. These new models are built with coding in mind, packing serious power under the hood. OpenAI says they now support up to 1 million tokens of context, with sharper long-context comprehension and a fresh knowledge cutoff of June 2024. The goal? Building AI that's not just smart -- but capable of handling the kind of complex software engineering tasks usually left to seasoned devs. As the AI arms race heats up, OpenAI has unveiled GPT-4.1 -- its latest move against rivals like Google and Anthropic in the battle to build the most advanced programming models. Google's Gemini 2.5 Pro, which also features a massive 1-million-token context window, is already scoring high across key coding benchmarks. Meanwhile, Anthropic's Claude 3.7 Sonnet and DeepSeek's V3 model out of China are steadily gaining ground. OpenAI says GPT-4.1 brings serious upgrades over GPT-4o, especially when it comes to coding. It's better at solving complex tasks agentically, handling frontend work, sticking to specific formats, making fewer unnecessary edits, and using tools with more consistency. Alongside the launch, OpenAI is also phasing out GPT-4.5 Preview from its API -- clearing the decks for what it clearly sees as the next generation of its coding-first AI. With GPT-4.1 now matching -- or outperforming -- GPT-4.5 across core benchmarks, and doing it faster and cheaper, OpenAI has announced that GPT-4.5 Preview will officially be retired on July 14, 2025. The timeline gives developers a fair runway to transition. GPT-4.5, initially launched as a research preview to test the limits of compute-heavy models, served its purpose by offering valuable insights through hands-on developer feedback. OpenAI says the creativity, writing flair, humour, and nuance that users loved in 4.5 won't be lost -- they're bringing those strengths into the next generation of API offerings. The GPT-4.1 family -- featuring the base model, mini, and nano -- is now live and available to all developers. Thanks to major efficiency gains in its inference systems, OpenAI has slashed prices across the board. GPT-4.1 is now 26% cheaper than GPT-4o for median queries, while GPT-4.1 nano claims the title of OpenAI's "cheapest and fastest model ever." Here's the pricing breakdown: GPT-4.1 comes in at $2 per million input tokens and $8 per million output tokens. GPT-4.1 mini drops that to $0.40 and $1.60, and nano takes it even further to just $0.10 and $0.40 respectively. There's more good news for devs. OpenAI is bumping its prompt caching discount to 75% (up from 50%) for repeated context queries, and long context requests won't cost extra -- just the standard per-token rate.

OpenAI launches GPT-4.1 series with major upgrades in coding and comprehension

OpenAI said GPT-4.1 is 21% better at coding tasks than GPT-4o, and 27% better than GPT-4.5. It also follows instructions more accurately and does a better job keeping track of context in longer conversations or documents. GPT-4.1 Mini and GPT-4.1 Nano are smaller versions of the main model, designed for use on devices or apps that need faster responses or have limited computing power.OpenAI has launched a new set of artificial intelligence (AI) models called GPT-4.1, along with lighter versions GPT-4.1 Mini and GPT-4.1 Nano. These models are designed to do a better job at tasks such as writing code, following instructions, and understanding long documents or conversations. The company said GPT-4.1 performs better than its most advanced model so far, GPT-4o, and will soon replace the older GPT-4.5 model on its developer platform. One of the biggest updates is that GPT-4.1 can now handle up to 1 million "tokens" -- the small chunks of data AI models use to read and understand text. This makes it much more powerful when working with large files like long reports or big codebases. OpenAI said GPT-4.1 is 21% better at coding tasks than GPT-4o, and 27% better than GPT-4.5. It also follows instructions more accurately and does a better job keeping track of context in longer conversations or documents. "These models are great at coding, instruction following, and long context. Benchmarks are strong, but we focused on real-world applications, and developers seem very happy," OpenAI chief executive officer Sam Altman said on social media platform X. GPT-4.1 Mini and GPT-4.1 Nano are smaller versions of the main model, designed for use on devices or apps that need faster responses or have limited computing power. The company also said the new models are cheaper to use, and added that it will turn off the GPT-4.5 preview currently available on the API in July, as the new models offer "improved or similar performance." OpenAI had released GPT-4.5 as a test version in February. Now, with the launch of GPT-4.1, the company is also retiring GPT-4 from ChatGPT by April 30.

ETtech Explainer: Decoding OpenAI's new GPT-4.1 model with better coding skills

ChatGPT-maker OpenAI released a new family of GPT-4.1 models on Wednesday. The models are said to have improved coding abilities at a time when rivals Google and Anthropic have also been focusing on this feature. ET explains all about the GPT-4.1 launches. What's new with the GPT-4.1 family? OpenAI released three new models -- GPT-4.1 and two smaller versions called GPT-4.1 mini and GPT-4.1 nano, which they say is the "smallest, fastest and cheapest model ever". This family is said to be focused on real-world use cases bringing significant improvements in coding. "These models are great at coding, instruction following, and long context (1 million tokens)," said OpenAI CEO Sam Altman on microblogging site X. "Benchmarks are strong, but we focused on real-world utility, and developers seem very happy." Sophistication in coding has been getting better even for rival models such as Google's Gemini 2.5 Pro and Anthropic's Claude 3.7 Sonnet. How does it perform compared to previous models? Users on microblogging site X highlighted that the GPT-4.1 achieved 55% accuracy on the SWE-Bench Verified software engineering benchmark without being a reasoning model. It improves by 21% over GPT-4o and 27% over GPT-4.5 on coding. Evaluated for multimodal long-context understanding, GPT-4.1 set a state-of-the-art score of 72% for long, no-subtitles content, improving 6.7% over GPT-4o. Some however were less impressed. "For the very first time OpenAI released a model right after Google and they are way behind," Pierre Bongrand, an AI scientist and founder of AthenAI, posted on X, citing analysis of performance versus cost where Gemini 2.5 wins out over GPT-4.1 mini. Who can use it and how costly is it? The GPT-4.1 models are only available for developers as application programming interface (API). While matching or surpassing predecessor GPT-4o in intelligence evaluations and reducing latency, it reduces cost by 83%, OpenAI said. GPT-4.1 is 26% less expensive than GPT-4o for median queries, with the nano version priced at $0.10 per million tokens for inputs and $0.40 for output. Deedy Das, principal at Menlo Ventures, noted on X that this indicates how "intelligence keeps getting cheaper every week". Altman has said OpenAI's frontier model family GPT-5 will be released in a few months.

OpenAI Launches New GPT-4.1 Models, But They're Not Coming to ChatGPT

GPT-4.1 delivers strong performance in coding, excels in instruction following, and offers a much larger context window of 1 million tokens. OpenAI has launched a new series of AI models including GPT-4.1, GPT-4.1 mini, and GPT-4.1 nano. They are the best non-reasoning AI models from OpenAI, but the GPT-4.1 series is not coming to ChatGPT. OpenAI says GPT-4.1 series models are exclusively trained for developers, and they are available in the API, starting today. GPT-4.1 was tested on OpenRouter as "Quasar Alpha". During the launch, OpenAI CPO Kevin Weil said GPT-4.1 is "better than GPT-4o on just about every dimension." And on some key benchmarks, the GPT-4.1 model matches or beats the massive GPT-4.5 AI model. OpenAI says GPT-4.1 excels at coding, instruction following, and long context retrieval. The new GPT-4.1 AI models come with a context window of 1 million tokens for the first time, which is huge, and have a recent knowledge cutoff of June 2024. So in many ways, the GPT-4.1 model looks like a major upgrade to the GPT-4o model. Not to mention, these are multimodal models which means you can process both text and images as well. Coming to benchmarks, OpenAI says on SWE-bench Verified, GPT-4.1 completed 55% of tasks, much higher than GPT-4o's 33% and o3-mini-high's 49%. Next, in instruction following, GPT-4.1 came very close to GPT-4.5, o3-mini-high, and o1-high on OpenAI's internal benchmark. Following that, on the Needle in a Haystack test, which evaluates information retrieval in a long context window, all three models under the GPT-4.1 series correctly retrieved the information up to 1 million tokens. Finally, coming to pricing, GPT-4.1 costs $2/$8 for input/output tokens per 1 million tokens. Basically, in median queries, GPT-4.1 is 26% cheaper than GPT-4o while offering much better performance. GPT-4.1 nano is the cheapest and fastest model by OpenAI, ever. Lastly, OpenAI mentioned that GPT-4.5 is going away from the API on 14th July, 2025.

OpenAI GPT 4.1 API Now Available for Coding, Data Analysis, and Multimodal Tasks

OpenAI has unveiled GPT 4.1, the latest advancement in its AI model series, designed to empower developers and optimize workflows. This release introduces three distinct versions -- GPT 4.1, GPT 4.1 Mini, and GPT 4.1 Nano -- each tailored to specific use cases. These models deliver significant improvements in coding, instruction-following accuracy, long-context processing, and multimodal tasks. Additionally, they are faster, more efficient, and more cost-effective than their predecessors, making them a valuable tool for a wide range of applications. In this introduction, OpenAI explain everything you need to know about OpenAI's GPT 4.1 to get started, from its standout features to its tailored model variants. You'll discover how these advancements can transform your workflows, whether you're building intelligent agents, analyzing large datasets, or fine-tuning AI for specific use cases. OpenAI also touch on practical tools like the new prompting guide and fine-tuning options, as well as real-world success stories like Windsurf's experience with the model. The GPT 4.1 family offers flexibility through its three model variants, each optimized for different levels of complexity and resource requirements: This range ensures that developers can select the model that best aligns with their project's specific demands, whether it involves high-powered computation or cost-efficient processing. By offering tailored solutions, OpenAI enables developers to maximize efficiency without compromising on performance. GPT 4.1 introduces substantial improvements over its predecessor, GPT 4.0, and even rivals GPT 4.5 in several critical areas. Developers will benefit from enhanced coding capabilities, including improved handling of diff formats, repository exploration, and automated unit test generation. These features streamline coding processes, reducing the time and effort required for complex tasks. GPT‑4.1 excels at the following industry standard measures: Additionally, GPT 4.1 excels at following intricate, multi-step instructions, making sure higher accuracy and reliability in task execution. This makes it an invaluable tool for developers seeking to enhance productivity and minimize errors in their workflows. By addressing these key areas, GPT 4.1 sets a new benchmark for AI-driven development tools. Advance your skills in OpenAI GPT models by reading more of our detailed content. One of the standout features of GPT 4.1 is its ability to process up to 1 million tokens of context -- an eightfold increase compared to previous models. This capability is particularly beneficial for applications that require analyzing large datasets or extended documents. Whether summarizing lengthy reports, extracting insights from massive data files, or managing complex projects, GPT 4.1 delivers both efficiency and precision. This long-context processing capability not only saves time but also enhances the quality of results, making it an essential tool for developers working with data-intensive applications. By allowing seamless handling of large-scale information, GPT 4.1 enables users to tackle challenges that were previously difficult to address. GPT 4.1 extends its functionality beyond text, offering advanced multimodal capabilities that allow it to process text, images, and videos seamlessly. This versatility makes it an ideal solution for applications requiring reasoning across multiple data formats. For instance, developers can use GPT 4.1 to analyze visual data, interpret video content, or integrate insights from diverse sources into a cohesive output. Notably, GPT 4.1 Mini has been fine-tuned to enhance its multimodal performance, making it particularly well-suited for tasks that demand cross-format intelligence. By expanding its capabilities beyond traditional text processing, GPT 4.1 opens up new possibilities for innovation and application in fields such as media analysis, content creation, and data visualization. To enable customization and adaptability, OpenAI provides fine-tuning options for GPT 4.1 and GPT 4.1 Mini, with plans to extend this feature to GPT 4.1 Nano in the near future. These fine-tuning capabilities allow developers to tailor the models to their specific needs, making sure optimal performance for unique use cases. Additionally, OpenAI has introduced a new prompting guide, offering best practices to help developers maximize the models' potential. These resources empower users to refine their workflows and achieve better results, making GPT 4.1 a highly adaptable tool for a wide range of applications. OpenAI has prioritized cost efficiency with the release of GPT 4.1. The new models are 26% cheaper than GPT 4.0, with GPT 4.1 Nano offering the most affordable option at just 12 cents per million tokens. Furthermore, long-context usage is included at no additional cost, making these models accessible to a broader audience, from startups to large-scale enterprises. This focus on affordability ensures that developers can use advanced AI capabilities without exceeding their budgets. By combining cost efficiency with high performance, GPT 4.1 provides a compelling solution for organizations looking to integrate AI into their operations. As part of its commitment to resource optimization, OpenAI has announced plans to retire GPT 4.5 over the next three months. This decision allows the company to concentrate on refining GPT 4.1 and making sure it meets the evolving needs of developers. For those currently using GPT 4.5, transitioning to GPT 4.1 is recommended to take advantage of its improved features, enhanced performance, and cost savings. OpenAI has actively incorporated feedback from developers who participated in its data-sharing program. This collaborative approach has driven many of the improvements seen in GPT 4.1, making sure the models address real-world challenges effectively. OpenAI continues to encourage developers to share their insights, as this feedback plays a crucial role in shaping the future of AI technology. Windsurf, a coding platform, has already demonstrated the practical benefits of using GPT 4.1. The platform reported reduced verbosity and fewer unnecessary file modifications, highlighting the model's ability to streamline workflows and enhance productivity. This real-world example underscores GPT 4.1's potential to deliver tangible improvements for developers across various industries. Learn more over on the official OpenAI website. GPT 4.1 represents a significant step forward in AI development, offering smarter, faster, and more cost-effective tools for developers. Whether you're building coding agents, analyzing large datasets, or tackling multimodal tasks, these models provide the flexibility and performance needed to succeed. OpenAI invites developers to explore GPT 4.1 and contribute to the ongoing evolution of AI technology.

New ChatGPT-4.1 AI : Everything You Need to Know

Have you ever found yourself frustrated by AI tools that just don't quite hit the mark -- whether it's struggling with complex coding tasks, losing track of context in long conversations, or simply not following instructions the way you'd expect? If so, OpenAI's GPT-4.1 might be the fantastic option you've been waiting for. With its enhanced coding abilities, a staggering 1 million token context window, and improved instruction-following precision, GPT-4.1 promises to tackle these pain points head-on. But like any tool, it's not without its trade-offs. Created by Prompt Engineering, this guide unpacks everything you need to know about GPT-4.1, from its standout features to its limitations, so you can decide if it's the right fit for your needs. OpenAI offers ChatGPT-4.1 in three configurations, making sure flexibility for diverse applications: These variants allow developers and businesses to choose the model that best aligns with their specific requirements, balancing performance and cost efficiency. GPT-4.1 introduces several advancements that distinguish it from its predecessor: These features make GPT-4.1 a versatile tool for developers, researchers, and businesses looking to streamline their operations and improve productivity. Uncover more insights about ChatGPT in previous articles we have written. GPT-4.1 has been rigorously tested to evaluate its performance across various domains. It showcases notable strengths: However, GPT-4.1 does face challenges. Competitors such as Gemini 2.5 Pro and Amazon Q Developer Agent outperform it in specific areas, including advanced reasoning and coding benchmarks. These comparisons highlight the importance of aligning the model's capabilities with your project's unique demands. One of GPT-4.1's standout features is its enhanced multimodal reasoning. This allows the model to process and interpret a variety of inputs, including text and images, with improved accuracy. While it surpasses GPT-4.0 in this regard, certain open-weight models still demonstrate broader contextual understanding in niche scenarios. This makes ChatGPT-4.1 a strong contender for multimodal applications, though its performance may vary depending on the complexity of the task. GPT-4.1 offers a significant advantage in terms of cost efficiency. It is approximately 25-26% cheaper than GPT-4.0, making it an attractive option for high-token use cases such as large-scale data analysis or content generation. However, for smaller, less resource-intensive tasks, alternative models may provide more cost-effective solutions. This balance between cost and capability makes GPT-4.1 a compelling choice for businesses and developers managing tight budgets. Despite its many strengths, GPT-4.1 has some notable limitations: These limitations underscore the need for careful evaluation when deciding whether GPT-4.1 is the right fit for your specific use case. ChatGPT-4.1 is designed with developers in mind, offering exclusive API access that assists seamless integration into various applications. Its capabilities are particularly well-suited for building agentic systems and enhancing tool usage, making it a valuable resource for technical teams. By focusing on developer needs, OpenAI ensures that GPT-4.1 remains a practical and effective tool for a wide range of projects. While GPT-4.1 excels in areas such as coding and instruction adherence, it faces stiff competition from other models: These comparisons highlight the importance of evaluating your specific needs and priorities when selecting an AI model. While GPT-4.1 offers a balanced mix of features, other models may be better suited for specialized tasks. As ChatGPT-4.1 continues to be applied in real-world scenarios, its performance in areas such as long-context retrieval and reasoning is expected to improve. OpenAI's commitment to developer-centric features suggests that future iterations may address current limitations, further enhancing the model's utility. This ongoing development ensures that GPT-4.1 remains a relevant and valuable tool for a wide range of applications.

OpenAI GPT-4.1 First Tests and Impressions : An AI Model For Developers?

Have you ever found yourself frustrated with AI tools that promise the world but fall short when it comes to real-world tasks like coding, debugging, or managing complex workflows? For developers juggling long-context inputs or looking for seamless multimodal capabilities, the search for a reliable solution can feel endless. Enter OpenAI's GPT-4.1 -- a model designed to tackle these exact pain points. With its ability to process both text and images, generate structured outputs, and even execute function calls, GPT-4.1 is more than just an upgrade; it's a tailored tool for developers aiming to streamline their workflows and achieve more in less time. But does it live up to the hype? All About AI dives into the first tests and impressions to uncover its true potential. In this guide, you'll discover how GPT-4.1 stacks up against competitors like Claude 3.7 and Gemini 2.5 Pro, what makes its multimodal and long-context handling capabilities stand out, and where it still has room for improvement. Whether you're curious about its coding prowess, intrigued by the new Mini and Nano models for lightweight tasks, or wondering if its pricing matches its performance, this tutorial by All About AI has you covered. By the end, you'll have a clear understanding of whether GPT-4.1 is the right fit for your development needs -- and how it could redefine the way you approach AI-powered solutions. GPT-4.1 builds on the strengths of its predecessors while introducing new functionalities that broaden its application potential. Its key features include: These features collectively make GPT-4.1 a robust and adaptable tool for developers, capable of addressing a wide range of challenges, from coding tasks to multimodal problem-solving. GPT-4.1 has demonstrated impressive performance across various industry benchmarks, solidifying its position as a leading AI model. In Swedbench, a widely recognized test for AI efficiency, GPT-4.1 outperformed competitors such as Claude 3.7 and Gemini 2.5 Pro. It also showcased superior speed, particularly when compared to Gemini 2.5 Pro, while maintaining a competitive pricing structure. The model's ability to handle a 1 million token context window at a cost-effective rate further enhances its appeal to developers. These results highlight GPT-4.1's ability to deliver a compelling balance of performance, affordability, and scalability, making it a strong contender in the AI market. Advance your skills in GPT-4.1 by reading more of our detailed content. OpenAI has expanded its offerings with the introduction of Mini and Nano models, designed to meet the needs of developers requiring faster and more efficient solutions for simpler tasks. The Nano model, in particular, stands out for its speed and responsiveness, making it ideal for real-time applications such as live data processing, customer support, and interactive systems. While these models lack some of the advanced features of GPT-4.1, they provide practical alternatives for scenarios where speed and efficiency take precedence over complexity. This diversification ensures that OpenAI's solutions cater to a broader range of use cases, from lightweight tasks to more demanding workflows. Comparative testing has provided valuable insights into GPT-4.1's capabilities and areas for improvement. Key findings include: These results underscore GPT-4.1's strengths in coding and multimodal tasks while highlighting areas where further refinement is needed, particularly in debugging complex systems. GPT-4.1 offers a range of strengths that make it a valuable tool for developers, but it also has limitations that should be considered: While GPT-4.1 is a powerful tool, it may not be the optimal choice for every scenario, particularly those requiring advanced debugging or highly specialized outputs. The introduction of the Nano model underscores OpenAI's commitment to supporting real-time applications, such as live customer support, interactive AI systems, and dynamic data processing. As developers continue to explore the capabilities of GPT-4.1, its potential to drive innovation in AI development becomes increasingly evident. Ongoing testing and refinement are expected to uncover additional use cases, further solidifying GPT-4.1's role as a cornerstone in the competitive AI market. By addressing its current limitations and expanding its feature set, GPT-4.1 has the potential to redefine how developers approach complex workflows and real-time applications.

OpenAI Debuts Cheaper GPT-4.1 Models to Attract Enterprise Clients | PYMNTS.com

Enterprises like Thomson Reuters, Carlyle and Blue J report major performance boosts in document review, coding and data analysis. OpenAI has launched its newest artificial intelligence (AI) model lineup that is less expensive than older models and also outperforms them, as competition for enterprise customers heats up. The new models -- GPT-4.1, GPT-4.1 mini and GPT-4.1 nano -- also boast one-million-token context windows, up from 128,000. Context windows are where users enter prompts and get responses. One million tokens equal around 750,000 words, or about seven to 10 novels. In a blog post Monday (April 14), OpenAI said the GPT-4.1 models outperform its own previous reasoning models GPT-4o and GPT-4o mini "across the board," with "major gains" in coding capabilities, how well it follows instructions and ability to handle long documents. It was trained on knowledge up to June 2024. Like the GPT-4o series, these new models can handle text, images, audio and video. They are available now, but only as an application programming interface (API) for developers. "One of the things that we've learned over and over is that the more cost effectively we can offer our models, the more use cases you're able to build, the more that you're able to use AI to help people all over the world," said OpenAI Chief Product Officer Kevin Weil in a YouTube video. The cost of using AI is a major stumbling block to AI deployment at enterprises. Each prompt and response using an AI chatbot or assistant carries a cost per token. That's why Chinese AI startup DeepSeek's inexpensive open-source foundation AI models went viral. Notably, the $20 monthly ChatGPT subscription for unlimited use is a loss leader to get people used to using AI chatbots. OpenAI CEO Sam Altman said on X that even the $200 a month ChatGPT Pro plan loses money. For enterprises, OpenAI has a pay-as-you-go plan. AI is expensive because of the computer chips it uses, according to Amazon CEO Andy Jassy's 2024 letter to shareholders. "Most AI to date has been built on one chip provider," referring to Nvidia, he wrote. "It's pricey." But Jassy sees costs dropping as other companies build AI chips. He said Amazon's own Trainium2 chips are 30% to 40% cheaper to use. Read more: OpenAI to Release GPT-4.5 Within Weeks, GPT-5 Within Months OpenAI said GPT-4.1 is 26% less expensive than GPT-4o for median queries, while GPT-4.1 nano is its cheapest and fastest model to date. OpenAI also raised the prompt caching discount to 75% from 50%. That means when users upload a document and ask several questions related to it, OpenAI will charge 75% less for the second and following prompts. There is an additional 50% discount for Batch API uses as well. OpenAI shared the following real-world use cases of GPT-4.1:

OpenAI introduces new GPT-4.1 AI models: Here's everything you should know

One of the biggest highlights of GPT-4.1 models is their expanded context window. OpenAI has officially unveiled its latest lineup of AI models -- the GPT-4.1 series -- which brings powerful upgrades. Whether you're coding or analysing large documents, these new models are designed to handle more. The lineup includes three versions: GPT‑4.1, GPT‑4.1 mini, and GPT‑4.1 nano. Let's delve into the details. "These models are great at coding, instruction following, and long context (1 million tokens). Benchmarks are strong, but we focused on real-world utility, and developers seem very happy," said OpenAI CEO Sam Altman on X (formerly Twitter). Let's dive into the details of the new GPT-4.1 models. One of the biggest highlights of GPT-4.1 models is their expanded context window. These models can work with up to 1 million tokens. This is a huge leap from GPT-4o models' limit of 128,000 tokens. This means GPT-4.1 models can better understand long documents, large codebases, or detailed conversations without losing track of important details. Also read: ChatGPT can now remember all your past conversations for more personalised experience In addition to this, GPT-4.1 has gotten a major performance boost in coding. OpenAI says it delivers a 21.4% improvement over GPT-4o and a 26.6% jump compared to GPT-4.5 in coding-related tasks. Also, on Scale's MultiChallenge⁠ benchmark (a measure of instruction following ability), the new GPT‑4.1 scores 38.3%, a 10.5% increase over GPT‑4o, according to OpenAI. Also read: OpenAI says Elon Musk is harassing them, asks court to stop him "Close collaboration and partnership with the developer community enabled us to optimize these models for the tasks that matter most to their applications," OpenAI said in its blog post. All the new models- GPT‑4.1, GPT‑4.1 mini, and GPT‑4.1 nano- are available to all developers.

ChatGPT 4.1 has 5 improved features that everyone will find useful

When ChatGPT first arrived towards the end of 2022, it felt like a seismic shift in tech. Then came GPT-3, 3.5, 4o, and so many others that I've honestly lost count - due to sheer confusion! With each of these ChatGPT releases, OpenAI promised smarter interactions, better context handling, and improved AI-assisted coding chops - and for the most part it delivered on these promises, albeit with some hallucination baked in. But OpenAI's latest release, ChatGPT 4.1, isn't just iterative improvement. It's the kind of step-change that makes everything before it look incremental at best - which takes on Claude 3.7 Sonnet and Google's Gemini 2.0 and above with more firepower. Also read: Open AI Strawberry o1: 5 ways it's better than ChatGPT 4o Let's unpack exactly what makes ChatGPT-4.1 such a big deal: Remember the excitement when GPT-4o broke the 128,000-token barrier, promising richer, more cohesive interactions? GPT-4.1 just laughed that off and raised the stakes by eightfold -- handling a jaw-dropping one million tokens of context. To put this in perspective, that's enough capacity to analyze an entire epic fantasy series, a detailed legal case archive, or a complex, sprawling software project -- without losing track of key details. For professionals like developers (which is what GPT-4.1's aimed at right now), lawyers, or financial analysts who routinely wrestle with heaps of documents, GPT-4.1's vast context window is transformative. Imagine feeding it a full legal corpus or an intricate code repository and getting coherent, accurate insights without chopping your data into bite-sized prompts. Basically, GPT-4.1 remembers more, understands deeper, and delivers conversational responses that's more context-aware than ever before -- diminishing the gap between human nuance and machine understanding by a good deal. Previous iterations like GPT-4o and Anthropic's Claude 3.7 Sonnet already showed impressive coding abilities, assisting in bug fixes, patch writing, and even generating boilerplate code. But GPT-4.1 shifts from a helpful assistant to something closer to a full-stack coding partner, claims OpenAI in their official blog post. According to the latest SWE-bench Verified scores, GPT-4.1 hits an impressive 54.6%, nearly 27 points higher than GPT-4.5 and over 20 points above GPT-4o. Practical translation of these benchmarks mean far fewer bugs, much more precise code patches, and smoother integrations. All of which's music to any programmer's ears. Moreover, GPT-4.1 nails frontend code -- human evaluators favoured its generated interfaces over previous models about 80% of the time. Also read: OpenAI o3 model: How good is ChatGPT's next AI version? For devs, this means less time debugging and more focus on strategic innovation. And its API performance? Slicker and more economical, generating minimal necessary diffs rather than rewriting whole codebases. That's smarter, cheaper, and faster -- exactly the kind of trifecta that genuinely advances software development. Anyone who's struggled with ambiguous or vaguely formatted outputs from earlier models (yes, even you, GPT-4o) will appreciate GPT-4.1's newly sharpened instruction-following capabilities, according to OpenAI. Benchmarks like Scale's MultiChallenge confirm it: a robust 10.5 percentage point boost compared to GPT-4o. Also read: Sam Altman's ChatGPT openly challenges DeepSeek, Llama: Open source AI war begins Give GPT-4.1 a complex instruction -- whether formatting a business report in XML or YAML, or following a precise multi-step workflow -- and it executes with minimal ambiguity. This improved adherence means clearer outputs, better consistency across long conversations, and fewer "but that's not what I asked for" moments. It also means enhanced interactions with autonomous agents, delivering smoother, more intuitive conversations across sectors from education to enterprise support. When it comes to interacting with ChatGPT, who wouldn't want it to be speedier in its responses, right? In that regard, GPT-4.1 introduces 'nano' and 'mini' variants alongside the standard model, dramatically reducing latency and cost. Its lightweight siblings particularly excel at tasks demanding rapid-fire responses, such as real-time coding assistants or live-chat support bots. Also read: OpenAI's PhD-research AI agent for $20000 a month: Future of work or AI hype? Reduced latency means interactions feel instantaneous -- whether it's seamless autocomplete in coding editors or responsive, human-like chats. And because the models use fewer tokens and lower computing resources, deploying GPT-4.1 at scale becomes economically viable, even for budget-conscious enterprises. Basically, GPT-4.1 doesn't just do more - it does it faster and cheaper, maintaining seamless user experiences even under demanding workloads. In the ever-accelerating AI arms race, efficiency might just be GPT-4.1's secret weapon. When Anthropic's Claude 3.7 Sonnet debuted, it introduced agentic capabilities aimed at automating complex workflows. GPT-4.1 doubles down on this concept, turning the promise of autonomous agents into an everyday reality. Also read: Claude 3.7 Sonnet: Anthropic's new AI model explained Its expansive context window, paired with precise instruction-following, makes GPT-4.1 uniquely suited for building truly autonomous AI agents or assistants. Legal assistants can parse multiple contracts simultaneously, flagging inconsistencies autonomously. Customer support bots manage long interactions seamlessly, offering context-rich, personalized responses without continuous human oversight. Better yet, GPT-4.1 is easily fine-tuned, allowing developers to mold the AI for specific industries or use cases -- making it more relevant, accurate, and valuable to end-users. Whether it's detailed data extraction, sophisticated customer support, or even autonomous coding workflows, GPT-4.1 is purpose-built to drive smarter, more independent solutions. From everything OpenAI has suggested so far, ChatGPT-4.1 seems to be more than an iterative upgrade -- it feels like a platform-defining shift. From unparalleled context handling to revolutionary coding skills, precise instruction-following, blazing efficiency, and truly autonomous agent capabilities, GPT-4.1 is OpenAI's most significant release yet.