It's official. Too many people are building AI chips:
Elon Musk announced that the company's AI chip design team completed the development of its AI5 autonomous driving chip, reaching the final design milestone before a chip goes to a foundry for manufacturing. The chip will be fabricated at Samsung's plant in Taylor, Texas and TSMC's facility in Arizona, with small-batch samples expected late 2026 and volume production in 2027. Musk described it as potentially one of the most widely produced AI chips ever. It builds on hardware already deployed across hundreds of thousands of Teslas, but is designed for significantly more demanding workloads, including Optimus robots and supercomputer clusters.
Breaking down the buzz:
Tesla is not building its own chip to beat NVIDIA on raw performance. It is building its own chip because custom silicon and software designed together can do things general-purpose hardware cannot, at the cost and power envelope that a robotics and autonomy business actually needs. Musk has benchmarked a single AI5 chip as roughly equivalent in inference performance to an NVIDIA H100 for Tesla's specific workloads, and a dual-chip configuration as comparable to NVIDIA's Blackwell-class processors, but at significantly lower cost and power consumption. That claim only holds because Tesla also writes all the software the chip runs.
Why this matters:
Google figured this out first with its Tensor Processing Units (TPUs). Apple did it with its Neural Engine. Amazon built Inferentia for its own inference workloads. The pattern is identical every time, where the efficiency gains from custom silicon only materialise when one company controls both the chip and the code. NVIDIA is not under threat from Tesla's chip; Tesla's car buyers are not going to buy a server rack. What is happening instead is a bifurcation in the AI compute market. General-purpose AI compute, where NVIDIA dominates, keeps growing because training frontier models still requires it. At the application layer, every sufficiently large company running a specific, repeatable workload at scale now has a rational case for building its own silicon. The cost of not doing so is paying NVIDIA's margins forever.
Please copy my portfolio for steady and consistent growth, $TSLA (Tesla Motors, Inc.)$NVDA (NVIDIA Corporation)... Show More
Not investment advice. The author may have financial interests in the mentioned instruments.
Not “too many chips” — just market evolution, custom silicon wins at scale for specific workloads, while NVIDIA still dominates general-purpose AI compute.
... Show More
.
We use our own and third-party cookies on our websites to enhance your experience, analyze traffic, and for security and marketing. For more info, see our Cookie Policy or go to Manage Settings.
Privacy Preference Center
When you visit any website, it may store or retrieve information on your browser, mostly in the form of cookies. This information might be about you, your preferences or your device and is mostly used to make the site work as you expect it to. The information does not usually directly identify you, but it can give you a more personalized web experience. Because we respect your right to privacy, you can choose not to allow some types of cookies. Click on the different category headings to find out more and change our default settings. However, blocking some types of cookies may impact your experience of the site and the services we are able to offer.
More information
Manage Consent Preferences
Strictly Necessary Cookies
Always Active
These cookies are necessary for the website to function and cannot be switched off in our systems. They are usually only set in response to actions made by you which amount to a request for services, such as setting your privacy preferences, logging in or filling in forms. You can set your browser to block or alert you about these cookies, but some parts of the site will not then work. These cookies do not store any personally identifiable information.
Performance Cookies
These cookies allow us to count visits and traffic sources so we can measure and improve the performance of our site. They help us to know which pages are the most and least popular and see how visitors move around the site. All information these cookies collect is aggregated and therefore anonymous. If you do not allow these cookies we will not know when you have visited our site, and will not be able to monitor its performance.
Functional Cookies
These cookies enable the website to provide enhanced functionality and personalisation. They may be set by us or by third party providers whose services we have added to our pages. If you do not allow these cookies then some or all of these services may not function properly.
Targeting Cookies
These cookies may be set through our site by our advertising partners. They may be used by those companies to build a profile of your interests and show you relevant adverts on other sites. They do not store directly personal information, but are based on uniquely identifying your browser and internet device. If you do not allow these cookies, you will experience less targeted advertising.
Cookie List
label
ConsentLeg.Interest
label
label
label
Thu May 14 2026 15:07:23 GMT+0000 (Coordinated Universal Time)
