Futures
Access hundreds of perpetual contracts
TradFi
Gold
One platform for global traditional assets
Options
Hot
Trade European-style vanilla options
Unified Account
Maximize your capital efficiency
Demo Trading
Introduction to Futures Trading
Learn the basics of futures trading
Futures Events
Join events to earn rewards
Demo Trading
Use virtual funds to practice risk-free trading
Launch
CandyDrop
Collect candies to earn airdrops
Launchpool
Quick staking, earn potential new tokens
HODLer Airdrop
Hold GT and get massive airdrops for free
Pre-IPOs
Unlock full access to global stock IPOs
Alpha Points
Trade on-chain assets and earn airdrops
Futures Points
Earn futures points and claim airdrop rewards
Promotions
AI
Gate AI
Your all-in-one conversational AI partner
Gate AI Bot
Use Gate AI directly in your social App
GateClaw
Gate Blue Lobster, ready to go
Gate for AI Agent
Gate MCP
Gate Skills Hub
10K+ Skills
From office tasks to trading, the all-in-one skill hub makes AI even more useful.
GateRouter
Smartly choose from 30+ AI models, with 0% extra fees
Pony.ai unveils next-generation autonomous driving controller based on NVIDIA… Will it accelerate the expansion of robotaxi services
Pony.ai ($PONY) has released a new generation of autonomous driving domain controllers based on NVIDIA’s latest autonomous driving platform. This move targets the autonomous mobility market, including L4-level autonomous taxis.
The platform released this time is based on NVIDIA DRIVE Hyperion, with the core equipped with DRIVE AGX Thor and NVLink. The company states that this platform supports not only single-chip configurations but also multi-chip setups, achieving a maximum computing power of 4000 FP4 TFLOPS when combined. This is interpreted as being specifically designed to meet the high-performance computing needs of L4 autonomous vehicles to process driving decisions in complex urban environments in real time.
Pony.ai claims that this domain controller improves energy efficiency and supports redundancy of key components, multiple cooling methods, and deployment options. For services like autonomous taxis that require long operational hours, energy efficiency and system stability directly impact profitability. This emphasizes that the product is not solely focused on performance competition but also fully considers real-world operational environments.
China market shipments have surged… while also emphasizing improved profitability.
The company states that its existing “Fangzai” controllers have seen shipments grow by over 500% compared to the previous year by 2025. This indicates that demand for autonomous driving hardware is rapidly expanding and also shows that Pony.ai has moved beyond pure technological development into mass production and commercialization.
Notably, Pony.ai announced that it has achieved break-even in “per-vehicle economics” in two major markets in China. Per-vehicle economics is an indicator of profitability per vehicle or service unit and is regarded as an important standard for assessing commercialization potential in the autonomous driving industry. While many companies have received large-scale investments but continue to operate at a loss, the fact that this company can achieve break-even in some regions is enough to attract market attention.
Goal: Operate 3,000 autonomous taxis by the end of 2026, covering 20 cities.
Pony.ai has set a target to operate over 3,000 autonomous taxis by the end of 2026 and expand services to more than 20 cities. This indicates that their plan is not just about technological demonstration but truly integrating autonomous driving services into urban transportation networks.
Looking at the entire autonomous driving industry, recent competition has shifted from “who has mastered the technology first” to “who can operate more stably and at larger scale.” Against this backdrop, the significance of Pony.ai’s release lies in showcasing both a high-performance semiconductor platform and commercialization metrics. The key in the future will be how to effectively combine high-performance controllers with vehicle scale expansion and profitability improvement.
TP AI Notice: This article is summarized based on the TokenPost.ai language model. The main content in the text may be omitted or may not be entirely accurate.