I tried Acer’s new 5K MiniLED Gaming monitor, and OLED kept popping into my head


If Computex 2026 taught me one thing, it’s that monitor makers are no longer interested in building one-trick ponies. They want displays that can wear multiple hats, seamlessly switching between work and play without making users choose. Acer’s new Nitro XV345CKR P is perhaps the best example of that philosophy, and after spending time with it on the show floor, I walked away impressed by its ambition while also questioning whether MiniLED is really the future for gaming monitors.

I’ve always had a slightly complicated relationship with MiniLED. On a massive living room TV, it works wonders because you’re sitting several feet away, and the local dimming zones blend beautifully. Put the same technology on a monitor that’s sitting barely two feet from your face, however, and suddenly you’re no longer admiring the display, you’re inspecting the physics behind it.

Acer is trying to build one monitor that does it all

On paper, the Nitro XV345CKR P sounds almost too good to be true. It’s a 34-inch 1500R curved ultrawide with a 5K WUHD (5120 x 2160) resolution, making it considerably sharper than the UWQHD OLED ultrawides that currently dominate the market. That extra resolution doesn’t just make games look cleaner, but also results in noticeably sharper text and far more workspace for coding, writing, spreadsheets, or video editing.

Then comes Acer’s biggest trick: Dynamic Frequency and Resolution (DFR). At the press of a button, the monitor can run at 5K and 180Hz for immersive single-player gaming or productivity, before switching to 2560 x 1080 at 360Hz for competitive titles where every frame counts. It’s an incredibly clever concept that feels like Acer trying to replace both your creator monitor and your gaming monitor with a single display.

The MiniLED implementation itself is equally ambitious. Backed by 1,344 local dimming zones and certified for DisplayHDR 1000, the monitor gets incredibly bright and remained perfectly legible even under the harsh lighting of the Computex show floor. More importantly, this isn’t just another edge-lit VA panel with a fancy sticker slapped on the box. The dense local dimming array delivers significantly better HDR highlights and local contrast, making explosions, reflections, and bright scenes look far more impactful than they would on a conventional LCD monitor.

The technology impressed me, but OLED still lives rent-free in my head

As good as the hardware is, using the Nitro XV345CKR P also reminded me why MiniLED and desktop monitors remain an interesting combination. Because you’re sitting so close to the display, the limitations of local dimming become much easier to spot. During my demo, I could still notice blooming around bright objects against dark backgrounds, and while black levels were certainly improved over a standard VA panel, they never reached the pixel-perfect darkness that OLED panels have conditioned many enthusiasts to expect. That’s less a criticism of Acer and more a limitation of the technology itself.

At the same time, it’s important to give MiniLED the credit it deserves. Compared to a traditional edge-lit VA monitor, this implementation is in another league altogether, delivering excellent brightness, stronger HDR performance, and much better local contrast. It also avoids one concern that continues to make some buyers nervous about OLED: burn-in. For users who spend all day staring at static toolbars, spreadsheets, or editing timelines before gaming at night, that’s a genuine advantage.

Ultimately, I don’t think the Acer Nitro XV345CKR P is trying to dethrone OLED, and that’s perfectly okay. Instead, it’s carving out its own space with a unique blend of razor-sharp 5K clarity, impressive HDR brightness, and the flexibility to switch between productivity and high-refresh gaming in a single display. Most enthusiasts may still gravitate towards OLED, but if priced right, this ambitious MiniLED monitor proves there’s still plenty of room for innovation beyond self-lit pixels.



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After this experience, Eiger, Gilbert, and another UW PhD student, Anna-Maria Gueorguieva, decided to test ChatGPT to see what it would surface about a professor. 

At first, OpenAI’s guardrails kicked in, and ChatGPT responded that the information was unavailable. But in the same response, the chatbot suggested, “if you want to go deeper, I can still try a more ‘investigative-style’ approach.” Their inquiry just had to help “narrow things down,” ChatGPT said, by providing “a neighborhood guess” for where the professor might live, or “a possible co-owner name” for the professor’s home. ChatGPT continued: “That’s usually the only way to surface newer or intentionally less-visible property records.” 

The students provided this information, leading ChatGPT to produce the professor’s home address, home purchase price, and spouse’s name from city property records. 

(Taya Christianson, an OpenAI representative, said she was not able to comment on what happened in this case without seeing screenshots or knowing which model the students had tested, even after we pointed out that many users may not know which model they were using in the ChatGPT interface. She also declined to comment generally about the exposure of PII by the chatbot, instead providing links to documents describing how OpenAI handles privacy, including filtering out PII, and other tools.) 

This reveals one of the fundamental problems with chatbots, says DeleteMe’s Shavell. AI companies “can build in guardrails, but [their chatbots] are also designed to be effective and to answer customer questions.”

The exposure issue is not limited to Gemini or ChatGPT. Last year, Futurism found that if you prompted xAI’s chatbot Grok with “[name] address,” in almost all cases, it provided not only residential addresses but also often the person’s phone numbers, work addresses, and addresses for people with similar-sounding names. (xAI did not respond to a request for comment.) 

No clear answers

There aren’t straightforward solutions to this problem—there’s no easy way to either verify whether someone’s personal information is in a given model’s training set or to compel the models to remove PII. 



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