At Computex 2026 in Taipei, the theme is clear: AI must run locally. From a $300 entry-level laptop to a flagship with 128GB of unified memory capable of running large models on-device, the entire price spectrum is covered.
Opening on June 2 at the Nangang Exhibition Center, the show is built around the slogan "AI Together." With 1,500 exhibitors from 33 countries and regions across more than 6,000 booths, the focus has shifted from benchmark scores and ports to one question: how to make AI run directly on the PC without relying on the cloud.
From $300 to Flagship: Full Price Range Covered
The most notable development is not a single product but the entire supply chain converging on AI PCs, segmented by price.
- Entry-level: Qualcomm Snapdragon C platform, targeting laptops starting at $300, with Acer Aspire Go 15 already adopting it.
- Mainstream to flagship: Nvidia RTX Spark, offering up to 128GB unified memory for running large models and agents locally, launching in fall.
- Flagship: Microsoft Surface Laptop Ultra, powered by RTX Spark, featuring a 15-inch mini-LED display with peak brightness of 2,000 nits.
- Handheld: Intel Arc G3 / G3 Extreme, targeting handheld gaming PCs with ray tracing and upscaling.
Nvidia has moved RTX Spark from chip announcement to actual deployment. Asus, Dell, HP, Lenovo, Microsoft Surface, and MSI are all in the launch lineup, with Acer and Gigabyte following later, all shipping in fall.
In his Monday keynote, Jensen Huang called RTX Spark "a new era for the PC." While that sounds like PR, the selling point is real: CPU, memory, and GPU integrated into a single chip, similar to Apple's M-series. The 128GB unified memory means a thin-and-light laptop can run sizable models locally.
Qualcomm is taking a different approach. Snapdragon C does not emphasize performance but focuses on pushing prices down to $300 and extending battery life, targeting education and entry-level markets. One pushes the high end, the other scales volume, giving AI PCs a complete price spectrum for the first time.
Common Ground: Stop Sending Everything to the Cloud
Whether $300 or flagship, these machines all emphasize the same thing: local processing.
Running large models locally offers three concrete benefits: data stays on the device, addressing privacy concerns; no network dependency, reducing latency and enabling offline use; and perhaps most practically, no monthly subscription fees for cloud-based AI services.
That is why Microsoft is fielding a dedicated Surface Laptop Ultra to lead the charge. It aims to prove that local AI is not just a cost-saving measure but can also deliver a premium experience.
On the data center side, Nvidia also revealed that its Vera CPU for data centers is already in full production, with OpenAI, Anthropic, and SpaceX as initial customers, launching in fall. By covering both the PC in your hand and the compute power in the data center, Nvidia aims to control both ends.
The Real Test Comes in Fall
Despite the excitement, a dose of reality is needed.
Most of these new machines will not actually ship until fall 2026, and prices remain largely unannounced (Surface Laptop Ultra only said "fall" with no price). Promises of "all-day battery" and "run large models locally" made at the show have yet to be proven in users' hands.
More critically, what is the killer app for local AI? Most people still use AI through web-based ChatGPT or Gemini. Paying extra for a new PC just to run AI locally is not yet a compelling enough reason.
Vendors have put their products on display and shown their hands. The only thing left is for users to vote with their wallets. The verdict will come in fall.
Sources: Computex 2026: The biggest announcements so far from Nvidia, Microsoft, Intel and more (Yahoo Tech); Nvidia jumps into PCs with new Arm-based chip debuting in laptops from Microsoft, Dell, CocoLoop, HP (CNBC); AI Goes Physical — Taiwan Leads Global Industry Transformation as COMPUTEX 2026 Opens (PR Newswire)