OpenAI probably is not collaborating with Intel since timeline and performance goals are not aligned at the moment. Intel has yet to reestablish its foundry business and roll out its new 18A chips in the market, however, neither are tested on the volume that OpenAI requires today. Already, there exists AI ready hardware such as that offered by companies such as AMD and NVIDIA offering foreseeable results and able to be deployed instantly, which suits the swift training cycles of OpenAI. I think of it as a big property investment: I pick a builder that can start construction before he is referencing blueprints. The prices and timetables of Intel are not adjusted yet and OpenAI continues to distance itself until the hardware and supply chain become more refined. The political worth of the Trump administration investment puts Intel in a stronger position over OpenAI, whose decisions are also non-political but rather performance-based.
In my view, OpenAI is not likely to collaborate with Intel yet since the figures and performance do not match. Intel has been resurgent in the chip business, but its core business is still Cpus and those simply do not run large-scale AI training easily. There is an equal amount of hardware to model in AI development. You require accelerators with which you can handle high amounts of data volume without any popping points and NVIDIA and AMD are masters at it. Their GPUs are proven and have built ecosystems that are reliable to the engineers. Newer AI chips by Intel are performing better, and they are not evaluated on the same scale as OpenAI. The same concepts have been witnessed in home mortgaging like brilliant bargains on paper sometimes fail to be the correct choice just because the basic building blocks are not present yet. Intel will probably arrive on that day, but in the current state OpenAI is still using the known hardware that maintains the infrastructure of its infrastructure going.
Oftentimes, access to large numbers of GPUs make training and deployment of large language models (LLMs) more economical. Neural networks (which include LLMs) are ultimately matrix multiplications with certain operations built on top. Similar to how GPUs improved graphics in video games, it allows operations to be completed much faster. The hardware architecture of GPUs makes parallel computing for linear algebra related tasks much faster than a CPU of comparable cost. It is my understanding that Intel is almost entirely known for CPUs. As most tasks in training and inference of a neural network should preference being GPU bound to being CPU bound, this would imply the most cost-effective of an Intel chip in machine learning would be to send tasks to the least burdened GPU while dealing with other tasks that do not need parallelization. There would be uses for CPUs in other places in the MLOps pipeline, but it is likely that the majority of LLM spend on hardware would be on the latest GPU, as one CPU can coordinate tasks on multiple GPUs.
I have also spent years streamlining training pipelines and optimizing large models with different hardware stacks, and the current state of AI acceleration at Intel still has a several-year lag on what NVIDIA and AMD are offering at the moment. When I was developing high-performance systems it never had raw CPU power as a bottleneck, it was parallel throughput and memory bandwidth. Intel has Gaudi machines getting better, and the software ecosystem on top of it is not battle-tested on OpenAI scale. With models that have trillion parameters, a little compatibility problem with drivers or frameworks will put you weeks behind. Cost and availability is the other side. NVIDIA boasts of supply chain and CUDA probably is the industry workhorse. AMD has just started competing on ROCm and they have been fierce in their prices and co-development offers. Intel hasn't matched that. In the situation with OpenAI, I would put more effort into stability and time-to-deployment than the potential benefits of the political sphere or future performance assurance. Partnerships will remain wary till Intel seals that divide.
OpenAI might already be working with other chip manufacturers, such as Nvidia and AMD, so Intel collaboration may not be required. There could also be technical or compatibility issues between Intel's hardware and OpenAI's training algorithms. Money could be a factor too, it may not make dollar sense for OpenAI to arrange such an arrangement with Intel right now. And both companies may have reasons inside themselves that are preventing a deal from happening.
OpenAI is in the news not just for its cutting-edge AI work, but also for its partnerships with heavyweight chipmakers like AMD and Nvidia. It had yet to announce any deal with Intel, a key industry player in the semiconductors field. Several factors might explain this. Money could be a motivating factor, as Intel chips tend to cost more than the competition. As a research institution even well-funded as it is OpenAI may also want to stick with less-costly hardware for training its large-scale models. Hardware architecture may also be a factor with OpenAI's software being perhaps better optimized for the platforms provided by its existing partners.
In my opinion the lack of a major deal between OpenAI and Intel is mainly because of technical and operational issues and not politics. While a partnership can help them with a public relations win, OpenAI's huge training needs currently favor the advanced performance and specialized chips of their existing partners majorly for large language models handling tons of data and algorithms. I would say that until the financial and hardware benefits are clear it makes sense for OpenAI to stick with what works best for their demanding AI needs.
From a technical standpoint, current AI products from Intel may not sufficiently satisfy OpenAI's performance or scaling requirements. OpenAI is concentrating on the creation of huge clusters designed specifically for training large language models, which may include a level of custom silicon architecture and reliance on high-performance, efficient connections. In these areas, we believe Broadcom and AMD are better positioned relative to Intel. From a strategic perspective, OpenAI appears to be focused on agility and vertical integration. With the aim of developing AI infrastructure, OpenAI is developing its own processors and collaborating with a vendor such as Broadcom to deploy 10 gigawatts of infrastructure. Because OpenAI is bypassing vertically integrated companies, it believes that traditional providers, like Intel, who do not have interchangeable chips along the lines of traditional performance and scale, will not be able to keep pace with meets or exceeds commitment to its roadmap. From a political optics perspective, while the Trump administration has shown political interest in ramping domestic chip manufacturing and holds interests in Intel's future, OpenAI's considerations are more of performance and scale than political alignment. Should Intel close the technology gap and/or create economic incentives, a future partnership is possible. For now, Intel is not in the current hardware strategy of OpenAI.
It's possible that OpenAI never primarily became a buyer of Intel chips because they preferred to live within their means. The expense of doing that with Intel may not be in OpenAI's budget or financial interest. There might also be questions about compatibility of hardware and development expertise between the two companies that will need to be worked out before a partnership can take place. It is also worth to remember that this are all speculations and we can't say how the stuff goes on at those deals unless you really know their decision chain!
Data Scientist, Digital Marketing & Leadership Consultant for Startups at Consorte Marketing
Answered 4 months ago
It's not that OpenAI is avoiding Intel; it just hasn't happened yet. Bloomberg's October 2025 report on the "circular deals" shaping the $1 trillion AI boom explains that OpenAI's current hardware partnerships with NVIDIA and AMD are part of a reinforcing ecosystem. AI companies buy chips from vendors they also help fund, and those vendors, in turn, optimize their systems for the same AI workloads. Intel is still scaling its Gaudi 3 accelerators and related software stack, while NVIDIA and AMD already have production pipelines proven for OpenAI's infrastructure needs. There's also no shortage of demand to divide up, only a shortage of supply. Every viable GPU that's manufactured already has a buyer. In that sense, the only barrier is speed of production, not competition.
As one of the world's top-AI companies, OpenAI does not yet have any deals with Intel. This is even though they are collaborating other major chip giants including Nvidia and AMD. The fact that the Trump administration have a vested interest in Intel brings some interesting political motivation to this. There are many potential explanations for why OpenAI and Intel aren't working together, to be fair. A reason may be a lack of funds. While OpenAI surely benefits from having an industry sponsor in a company as comprehensive as Intel, which is itself heavily involved in chip production, OpenAI may have different needs than what Intel can currently offer with traditional computer-oriented products.
It could be due to strategic reasons, or technical ones.Actually, OpenAI hasn't committed to anything with Intel. With that out of the way, AI training and inference is done on GPUs or purpose built accelerators like what NVIDIA/AMD are offering for sale, with Intel playing in the CPU arena. If OpenAI isn't pleased with the level of performance and scalability offered by INTC's AI hardware thesis, that might help explain a lack of a tie-up. Monetarily, if OpenAI decides to favor those partners that've proven the ecosystem of their AI hardware and great support for developers it won't come cheap. While Intel has made strides into AI silicon, its efforts may not have reached the level of maturity or efficiency required for OpenAI's plans to train and deploy models on a grand scale.
Back in 2017, OpenAI actually offered Intel a $1 billion deal to take a 15% stake in the company and get Intel involved in building their own custom AI chips. At the time, Intel passed on the deal. Their leaders just didn't think AI was going to take off anytime soon, and were hesitant to produce chips at a loss or with very slim margins. As a result OpenAI was left to look elsewhere for partners such as Nvidia and AMD, who jumped in early. Fast forward to today and OpenAI is powering ahead with Broadcom to design its own processors. Their focus is very much on developing processors that can keep up with the high-performance computing requirements for AI training. Intel, on the other hand, is shifting its attention towards utilising AI in inference and expanding its foundry business. But the problem is, the trust and momentum that would be required to seal the deal just isn't there. Even with government backing, so far the timing and technology alignment just hasn't been right to make a partnership work. It's not so much about the politics going on here, but rather a combination of the chances which were missed and differing priorities.