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Tesla VP Grace Tao explains China’s Model 3 and Model Y price reductions
After a challenging December, Tesla China adopted a number of strategies designed to improve its vehicle sales in the country. Among these was a price reduction on the domestically-produced Model 3 sedan and Model Y crossover. Recent comments from Tesla VP Grace Tao have now provided some insights into these price adjustments.
In a recent interview with local Chinese media, Tao was asked about Tesla China’s rather volatile pricing strategy. Similar to Tesla in the United States, Tesla China saw a number of price adjustments over the past year. This has resulted in some netizens in the country stating that Tesla’s pricing strategy is “too casual.”
Addressing the inquiry, Grace Tao explained that the pricing strategy of Tesla China’s vehicles is “actually a forecast of the company’s cost changes in the next period of time.” She also explained that the landscape had changed now, at least compared to the last year due to the end of the pandemic.
“The biggest difference between 2023 and last year is that the epidemic is basically over, and we believe that the supply chain has largely returned to normal and will not experience the various unpredictable shortages of materials that have occurred in previous years, leading to uncertainty in costs. In my personal opinion, price adjustments reflect our good planning for the supply chain to a certain extent. We expect what the vehicle cost will be approximately and then make such adjustments according to this expectation,” the executive said.
The Tesla VP also addressed the issue of some consumers in China who were upset that they bought vehicles before the recent round of price reductions took effect. So notable were the reactions of some consumers that protests were reportedly held in a number of Tesla stores.
“Maybe some consumers say that ‘I bought it yesterday, and you can’t suddenly change the cost overnight,’ but the fact is that no company calculates the cost every day, but rather calculates it on a time period. At the same time, the price of industrial products cannot be immediately reflected in the terminal products. Some raw materials may still be contracted a few months ago, so it actually has a certain lag.
“In addition, the price of a product is not only affected by its own cost, but also by the market demand and competition. If there is a change in the market demand or competition, it will also affect the price of the product. Therefore, the price adjustment of a product is not a simple matter. It is a comprehensive consideration of the enterprise’s own cost, market demand and competition,” the executive said.
Overall, the executive clarified that Tesla China’s price adjustments are not casual at all. Instead, they are done with a clear understanding of the company’s costs, demand in the market, and competitors. So far, however, Grace Tao noted that Tesla China has not had to change its strategy due to market demand or competition, which bodes well for the company’s footing in the country’s auto market. The executive also highlighted that after this recent round of price reductions, the cost of the domestically-produced Model 3 and Model Y should become more stable.
“In the past, Tesla has made several larger price adjustments due to external factors that have had an impact on costs. For example, when we became a domestic car(maker), the price naturally decreased compared to a pure import, at least the tariff was saved by 15%. For example, after our supply chain stabilized, it would definitely be lower than before when it was shipped from abroad. Tesla’s supply chain localization rate is now 95%, so theoretically, there is not much room for improvement. Therefore, I think after this price adjustment, the price should be relatively stable.
“Tesla’s logic is very simple. When the cost is calculated to have changed, such as changing raw materials, we will immediately increase or decrease the price. Actually, Tesla’s logic is very simple. Consumers seem to think that the price drop was relatively large compared to last month, but in fact, the price rose last month, and compared to the costs before the price increase, the difference is not large,” she said.
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Tesla’s Head of AI, Ashok Elluswamy, says that something that was expected with version 14.3 of the company’s Full Self-Driving platform has already partially shipped with the current build of version 14.2.
Tesla and CEO Elon Musk have teased on several occasions that reasoning will be a big piece of future Full Self-Driving builds, helping bring forth the “sentient” narrative that the company has pushed for these more advanced FSD versions.
Back in October on the Q3 Earnings Call, Musk said:
“With reasoning, it’s literally going to think about which parking spot to pick. It’ll drop you off at the entrance of the store, then go find a parking spot. It’s going to spot empty spots much better than a human. It’s going to use reasoning to solve things.”
Musk said in the same month:
“By v14.3, your car will feel like it is sentient.”
Amazingly, Tesla Full Self-Driving v14.2.2.2, which is the most recent iteration released, is very close to this sentient feeling. However, there are more things that need to be improved, and logic appears to be in the future plans to help with decision-making in general, alongside other refinements and features.
On Thursday evening, Elluswamy revealed that some of the reasoning features have already been rolled out, confirming that it has been added to navigation route changes during construction, as well as with parking options.
He added that “more and more reasoning will ship in Q1.”
🚨 Tesla’s Ashok Elluswamy reveals Nav decisions when encountering construction and parking options contain “some elements of reasoning”
More uses of reasoning will be shipped later this quarter, a big tidbit of info as we wait v14.3 https://t.co/jty8llgsKM
— TESLARATI (@Teslarati) January 9, 2026
Interestingly, parking improvements were hinted at being added in the initial rollout of v14.2 several months ago. These had not rolled out to vehicles quite yet, as they were listed under the future improvements portion of the release notes, but it appears things have already started to make their way to cars in a limited fashion.
Tesla Full Self-Driving v14.2 – Full Review, the Good and the Bad
As reasoning is more involved in more of the Full Self-Driving suite, it is likely we will see cars make better decisions in terms of routing and navigation, which is a big complaint of many owners (including me).
Additionally, the operation as a whole should be smoother and more comfortable to owners, which is hard to believe considering how good it is already. Nevertheless, there are absolutely improvements that need to be made before Tesla can introduce completely unsupervised FSD.
Elon Musk
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
Tesla CEO Elon Musk has provided an updated estimate for the training data needed to achieve truly safe unsupervised Full Self-Driving (FSD).
As per the CEO, roughly 10 billion miles of training data are required due to reality’s “super long tail of complexity.”
10 billion miles of training data
Musk comment came as a reply to Apple and Rivian alum Paul Beisel, who posted an analysis on X about the gap between tech demonstrations and real-world products. In his post, Beisel highlighted Tesla’s data-driven lead in autonomy, and he also argued that it would not be easy for rivals to become a legitimate competitor to FSD quickly.
“The notion that someone can ‘catch up’ to this problem primarily through simulation and limited on-road exposure strikes me as deeply naive. This is not a demo problem. It is a scale, data, and iteration problem— and Tesla is already far, far down that road while others are just getting started,” Beisel wrote.
Musk responded to Beisel’s post, stating that “Roughly 10 billion miles of training data is needed to achieve safe unsupervised self-driving. Reality has a super long tail of complexity.” This is quite interesting considering that in his Master Plan Part Deux, Elon Musk estimated that worldwide regulatory approval for autonomous driving would require around 6 billion miles.
FSD’s total training miles
As 2025 came to a close, Tesla community members observed that FSD was already nearing 7 billion miles driven, with over 2.5 billion miles being from inner city roads. The 7-billion-mile mark was passed just a few days later. This suggests that Tesla is likely the company today with the most training data for its autonomous driving program.
The difficulties of achieving autonomy were referenced by Elon Musk recently, when he commented on Nvidia’s Alpamayo program. As per Musk, “they will find that it’s easy to get to 99% and then super hard to solve the long tail of the distribution.” These sentiments were echoed by Tesla VP for AI software Ashok Elluswamy, who also noted on X that “the long tail is sooo long, that most people can’t grasp it.”
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Tesla earns top honors at MotorTrend’s SDV Innovator Awards
MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla emerged as one of the most recognized automakers at MotorTrend’s 2026 Software-Defined Vehicle (SDV) Innovator Awards.
As could be seen in a press release from the publication, two key Tesla employees were honored for their work on AI, autonomy, and vehicle software. MotorTrend’s SDV Awards were presented during CES 2026 in Las Vegas.
Tesla leaders and engineers recognized
The fourth annual SDV Innovator Awards celebrate pioneers and experts who are pushing the automotive industry deeper into software-driven development. Among the most notable honorees for this year was Ashok Elluswamy, Tesla’s Vice President of AI Software, who received a Pioneer Award for his role in advancing artificial intelligence and autonomy across the company’s vehicle lineup.
Tesla also secured recognition in the Expert category, with Lawson Fulton, a staff Autopilot machine learning engineer, honored for his contributions to Tesla’s driver-assistance and autonomous systems.
Tesla’s software-first strategy
While automakers like General Motors, Ford, and Rivian also received recognition, Tesla’s multiple awards stood out given the company’s outsized role in popularizing software-defined vehicles over the past decade. From frequent OTA updates to its data-driven approach to autonomy, Tesla has consistently treated vehicles as evolving software platforms rather than static products.
This has made Tesla’s vehicles very unique in their respective sectors, as they are arguably the only cars that objectively get better over time. This is especially true for vehicles that are loaded with the company’s Full Self-Driving system, which are getting progressively more intelligent and autonomous over time. The majority of Tesla’s updates to its vehicles are free as well, which is very much appreciated by customers worldwide.
Tesla AI Head says future FSD feature has already partially shipped
Tesla’s Elon Musk: 10 billion miles needed for safe Unsupervised FSD
