구형 테슬라 하드웨어의 FSD v12: 주목해야 할 5가지 세부 사항

A Tesla owner in China is driving a 7-year-old car with hardware that predates today's computing benchmarks — and FSD v12 is reportedly outrunning newer intelligent driving systems from the competition in real-world scenarios. It's a striking data point that says as much about Tesla's software architecture as it does about the EV industry's hardware arms race. 1. Hardware 3 is older than most people realize — and FSD v12 still runs on it Tesla's Hardware 3 (HW3) compute platform launched in 2019. At roughly 72 TOPS of neural-network processing power, it was a leap at the time but is now well behind the specs competitors advertise for their latest driver-assistance systems. Despite that gap, Tesla has continued pushing FSD updates to HW3 vehicles. According to reporting from Teslarati and notateslaapp.com, FSD v12.5.1.5 began rolling out publicly to HW3 owners in August 2024, and v12.6 followed by end of that year. That's a meaningful commitment to a platform that's now several hardware generations old. 2. The end-to-end neural network model is the reason older hardware can still compete FSD v12 marked Tesla's full transition to an end-to-end neural network approach — the car learns to drive from millions of real-world video clips rather than relying on a hand-coded rules engine. That architectural shift matters here: because the model is heavily optimized during training (on Tesla's Dojo and GPU clusters), the on-vehicle inference workload can be more efficient than the raw TOPS number suggests. The result is that a well-trained, compressed model running on HW3 can behave more fluidly in complex traffic than a rules-based system running on faster silicon. 3. China is a genuinely demanding test environment for any autonomous system Chinese urban traffic — dense intersections, e-bikes cutting across lanes, unmarked construction zones, aggressive merging — is widely regarded as one of the hardest environments for autonomous driving software to handle. When a system performs well there, it's not a controlled-highway demo; it's stress-tested in conditions that expose edge-case weaknesses quickly. The owner's comparison in this video is therefore more meaningful than a highway cruise-control benchmark would be. 4. Competitors have newer chips but software maturity is a different race Several Chinese EV brands now ship vehicles with purpose-built autonomous driving chips rated at hundreds or even thousands of TOPS. Raw compute is a real advantage for certain tasks — higher-resolution perception, longer planning horizons, faster sensor fusion. But hardware headroom only translates to better driving if the software can use it. FSD v12's end-to-end training pipeline represents years of accumulated fleet data and iteration. Closing that gap takes more than a chip upgrade, which is part of why this owner's comparison is drawing attention. 5. If you own an HW3 Tesla, you're still in the FSD update loop The practical takeaway for owners: HW3 vehicles — including older Model 3, Model Y, Model S, and Model X cars built before the HW4 transition — have not been abandoned by Tesla's software team. FSD v12 has been available on that hardware for over a year, and the China owner's experience suggests the gap between HW3 FSD and brand-new competitor systems is narrower than spec sheets imply. If you haven't checked your FSD version recently, it's worth opening Controls → Software to confirm you're on the latest available build for your hardware tier. For a full history of what's landed in recent updates, see our all software updates archive. The broader story here isn't just one owner's positive experience — it's a reminder that in autonomous driving, software compounding matters as much as silicon. A 7-year-old Tesla running a state-of-the-art neural network is a strange and interesting object, and the China market is proving to be one of the sharpest places to find out what it can actually do. Related Gear Gear up your Tesla with tested, custom-fit BASENOR accessories — shop Tesla accessories → Sources & reporting notes The links below identify the material source records used for this report. - @ray4tesla on X (2026-11-01T00:57:35.000Z) — Direct source Source links are preserved as published or accessed. See our editorial standards and corrections policy. The BASENOR Editorial Desk covers Tesla, SpaceX, and related technology, curating reporting from primary sources — official accounts, regulatory filings, and software release data. Every article passes source-record and fact-checking review before publication. About the newsroom. This report was curated by the BASENOR Editorial Desk from the sources listed above. Read our editorial standards or email [email protected] to report an error.