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Tesla’s ‘house-sized’ ‘Giga Press’ for Model Y production opens the doors to 1M cars per year

Tesla Model Y Production (Credit: Tesla)

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Elon Musk has noted that the Model Y’s casting machine is one of the biggest in the world, so much so that the equipment itself is “the size of a small house.” As noted in a piece from the recent issue of Automotive Engineering, it appears that Musk’s statement is actually very accurate. What’s more, the Model Y’s massive “Giga Press” casting machine could very well become the defining factor in helping Tesla achieve a production rate of 1 million vehicles per year. 

The Tesla Model Y may be built on the Model 3 platform, but the vehicle is loaded with improvements and innovations from the ground up. During Sandy Munro’s extensive teardown of the vehicle, the automotive veteran noted that the Model Y featured some of the largest aluminum casts he has ever seen in a vehicle of its size. This was most represented by the Model Y’s two-piece rear underbody aluminum casting, which Elon Musk expects could be further reduced into just one piece. 

At the center of this all is the Giga Press itself, the machine that is capable of actually making aluminum casts that are as big as Tesla requires. The machine is supplied by the IDRA Group, an Italian leader in HPDC equipment founded way back in 1946. So far, Tesla is the company’s first customer for the OL6100 CS, a mammoth casting machine that underwent some customization to handle the electric car maker’s casting needs. 

True to Musk’s description, the machine itself is the size of a house, measuring 64 ft (19.5 m) long and 17 ft (5.3 m) tall. It’s also incredibly heavy at 410 tons. Interestingly enough, according to the automotive engineering publication, the Giga Press is intended to be installed in several key locations, such as the Fremont Factory and Gigafactory Shanghai

Laurie Harbor, the president of Harbour Results Inc., a manufacturing consultancy firm, stated that the utilization of Giga Press for the Model Y production is certainly new, but it makes sense. This is particularly notable since Tesla and Elon Musk have both pressed the company’s engineers to be creative. This means that everything that can be done to increase efficiency, such as the use of massive casts, helps in making Model Y production better. 

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“Even with a big cycle time, you eliminate all the labor to assemble pieces and subcomponents. You’re saving on automation cells, you’re saving on people. It would be tough to put dollars to it, but think of multiple suppliers doing stampings. You could save maybe 20% on labor cost. And reduction in footprint is major. My guess is that it’s a net-net efficiency gain,” Harbor said. 

Tesla estimates that the use of a single-piece casting design will deliver a 30% reduction in the size of the Model Y’s body shop. If successful, then the company could roll out these improvements to the other vehicles in Tesla’s lineup as well. For Munro, these strategies may be costly for now due to the initial investments involved, but they go a long way towards increasing Tesla’s production capability. This should help the company produce more vehicles than ever before, perhaps even reaching Musk’s vision of manufacturing about 1 million vehicles per year. 

Simon is an experienced automotive reporter with a passion for electric cars and clean energy. Fascinated by the world envisioned by Elon Musk, he hopes to make it to Mars (at least as a tourist) someday. For stories or tips--or even to just say a simple hello--send a message to his email, simon@teslarati.com or his handle on X, @ResidentSponge.

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Tesla FSD v14.2.2 is getting rave reviews from drivers

So far, early testers have reported buttery-smooth drives with confident performance, even at night or on twisty roads.

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Credit: @BLKMDL3/X

Tesla Full Self-Driving (Supervised) v14.2.2 is receiving positive reviews from owners, with several drivers praising the build’s lack of hesitation during lane changes and its smoother decision-making, among others. 

The update, which started rolling out on Monday, also adds features like dynamic arrival pin adjustment. So far, early testers have reported buttery-smooth drives with confident performance, even at night or on twisty roads.

Owners highlight major improvements

Longtime Tesla owner and FSD user @BLKMDL3 shared a detailed 10-hour impression of FSD v14.2.2, noting that the system exhibited “zero lane change hesitation” and “extremely refined” lane choices. He praised Mad Max mode’s performance, stellar parking in locations including ticket dispensers, and impressive canyon runs even in dark conditions.

Fellow FSD user Dan Burkland reported an hour of FSD v14.2.2’s nighttime driving with “zero hesitations” and “buttery smooth” confidence reminiscent of Robotaxi rides in areas such as Austin, Texas. Veteran FSD user Whole Mars Catalog also demonstrated voice navigation via Grok, while Tesla owner Devin Olsen completed a nearly two-hour drive with FSD v14.2.2 in heavy traffic and rain with strong performance.

Closer to unsupervised

FSD has been receiving rave reviews, even from Tesla’s competitors. Xpeng CEO He Xiaopeng, for one, offered fresh praise for FSD v14.2 after visiting Silicon Valley. Following extended test drives of Tesla vehicles running the latest FSD software, He stated that the system has made major strides, reinforcing his view that Tesla’s approach to autonomy is indeed the proper path towards autonomy.

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According to He, Tesla’s FSD has evolved from a smooth Level 2 advanced driver assistance system into what he described as a “near-Level 4” experience in terms of capabilities. While acknowledging that areas of improvement are still present, the Xpeng CEO stated that FSD’s current iteration significantly surpasses last year’s capabilities. He also reiterated his belief that Tesla’s strategy of using the same autonomous software and hardware architecture across private vehicles and robotaxis is the right long-term approach, as it would allow users to bypass intermediate autonomy stages and move closer to Level 4 functionality.

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Elon Musk’s Grok AI to be used in U.S. War Department’s bespoke AI platform

The partnership aims to provide advanced capabilities to 3 million military and civilian personnel.

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Credit: xAI

The U.S. Department of War announced Monday an agreement with Elon Musk’s xAI to embed the company’s frontier artificial intelligence systems, powered by the Grok family of models, into the department’s bespoke AI platform GenAI.mil. 

The partnership aims to provide advanced capabilities to 3 million military and civilian personnel, with initial deployment targeted for early 2026 at Impact Level 5 (IL5) for secure handling of Controlled Unclassified Information.

xAI Integration

As noted by the War Department’s press release, GenAI.mil, its bespoke AI platform, will gain xAI for the Government’s suite of tools, which enable real-time global insights from the X platform for “decisive information advantage.” The rollout builds on xAI’s July launch of products for U.S. government customers, including federal, state, local, and national security use cases.

“Targeted for initial deployment in early 2026, this integration will allow all military and civilian personnel to use xAI’s capabilities at Impact Level 5 (IL5), enabling the secure handling of Controlled Unclassified Information (CUI) in daily workflows. Users will also gain access to real‑time global insights from the X platform, providing War Department personnel with a decisive information advantage,” the Department of War wrote in a press release. 

Strategic advantages

The deal marks another step in the Department of War’s efforts to use cutting-edge AI in its operations. xAI, for its part, highlighted that its tools can support administrative tasks at the federal, state and local levels, as well as “critical mission use cases” at the front line of military operations.

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“The War Department will continue scaling an AI ecosystem built for speed, security, and decision superiority. Newly IL5-certified capabilities will empower every aspect of the Department’s workforce, turning AI into a daily operational asset. This announcement marks another milestone in America’s AI revolution, and the War Department is driving that momentum forward,” the War Department noted.

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Tesla FSD (Supervised) v14.2.2 starts rolling out

The update focuses on smoother real-world performance, better obstacle awareness, and precise end-of-trip routing, among other improvements.

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Credit: Grok Imagine

Tesla has started rolling out Full Self-Driving (Supervised) v14.2.2, bringing further refinements to its most advanced driver-assist system. The new FSD update focuses on smoother real-world performance, better obstacle awareness, and precise end-of-trip routing, among other improvements.

Key FSD v14.2.2 improvements

As noted by Not a Tesla App, FSD v14.2.2 upgrades the vision encoder neural network with higher resolution features, enhancing detection of emergency vehicles, road obstacles, and human gestures. New Arrival Options let users select preferred drop-off styles, such as Parking Lot, Street, Driveway, Parking Garage, or Curbside, with the navigation pin automatically adjusting to the user’s ideal spot for precision.

Other additions include pulling over for emergency vehicles, real-time vision-based detours for blocked roads, improved gate and debris handling, and extreme Speed Profiles for customized driving styles. Reliability gains cover fault recovery, residue alerts on the windshield, and automatic narrow-field camera washing for new 2026 Model Y units.

FSD v14.2.2 also boosts unprotected turns, lane changes, cut-ins, and school bus scenarios, among other things. Tesla also noted that users’ FSD statistics will be saved under Controls > Autopilot, which should help drivers easily view how much they are using FSD in their daily drives.  

Key FSD v14.2.2 release notes

Full Self-Driving (Supervised) v14.2.2 includes:

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  • Upgraded the neural network vision encoder, leveraging higher resolution features to further improve scenarios like handling emergency vehicles, obstacles on the road, and human gestures.
  • Added Arrival Options for you to select where FSD should park: in a Parking Lot, on the Street, in a Driveway, in a Parking Garage, or at the Curbside.
  • Added handling to pull over or yield for emergency vehicles (e.g. police cars, fire trucks, ambulances).
  • Added navigation and routing into the vision-based neural network for real-time handling of blocked roads and detours.
  • Added additional Speed Profile to further customize driving style preference.
  • Improved handling for static and dynamic gates.
  • Improved offsetting for road debris (e.g. tires, tree branches, boxes).
  • Improve handling of several scenarios, including unprotected turns, lane changes, vehicle cut-ins, and school buses.
  • Improved FSD’s ability to manage system faults and recover smoothly from degraded operation for enhanced reliability.
  • Added alerting for residue build-up on interior windshield that may impact front camera visibility. If affected, visit Service for cleaning!
  • Added automatic narrow field washing to provide rapid and efficient front camera self-cleaning, and optimize aerodynamics wash at higher vehicle speed.
  • Camera visibility can lead to increased attention monitoring sensitivity. 

Upcoming Improvements:

  • Overall smoothness and sentience.
  • Parking spot selection and parking quality.
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