Top 10 Things to Test When Buying a 2nd Hand Gaming Laptop
Buying a 2nd hand gaming laptop can be a smart move, especially if you're looking to get high-end performance at a fraction of the price of a new one. But buying used tech always comes with risks. From hidden hardware issues to outdated components, there's a lot that could go wrong if you don't test things properly.
Here's a comprehensive checklist of the top 10 things you must test before buying a second-hand gaming laptop—whether you're shopping locally or online.
Check the outer body first. Look for cracks near the hinges, dents on the corners, missing screws, or worn-out rubber pads. These signs can reveal how the laptop has been treated. Make sure all ports (USB, HDMI, Ethernet) work by plugging in actual devices.
If you're unsure about specific models, browsing a PC product reviews section can help you compare real user feedback and durability reports before deciding.
Visual performance is crucial in gaming. Boot up the laptop and look closely at the screen. Dead pixels, backlight bleed, or odd color tints are red flags. Try switching through different brightness levels and open a dark image to reveal any screen issues.
Gaming requires precision, especially with keys like WASD, spacebar, and shift. Test all the keys to ensure none are sticky or unresponsive. The touchpad should be smooth, with no jitter or lag.
Older batteries degrade over time. Use tools like HWMonitor or Windows Battery Report (powercfg /batteryreport) to see its health, cycle count, and wear level. A poor battery won't ruin gameplay if you're plugged in, but it limits portability.
Use free tools like Speccy or CPU-Z to verify: CPU model and speed
Installed RAM
Graphics card (NVIDIA or AMD)
Storage type (preferably SSD)
Make sure the 2nd hand gaming laptop matches the specs advertised. Sellers sometimes misrepresent configurations, especially with older GPUs.
Install a benchmarking tool like Cinebench, 3DMark, or even a popular game to stress test the system. Listen for any weird noises, and watch out for overheating or sudden frame drops.
Gaming laptops can run hot, especially under load. Make sure the fans spin up properly and aren't excessively loud or grinding. A noisy fan could mean dust buildup or wear and tear on the bearings. You can also feel around the vents to see how well it's dissipating heat.
Play a video or game trailer to check the speaker quality—make sure there's no buzzing or crackling. Use the built-in webcam and mic to confirm they work properly, even if you typically use an external headset or cam.
A fresh OS install is always best. Ask the seller if they've wiped the system clean and reinstalled Windows. Check for: Genuine activation
No unnecessary startup apps
No malware or suspicious software
A cluttered or unlicensed OS can lead to instability and performance drops.
Some refurbished laptops still come with manufacturer warranties. If not, make sure the seller offers at least a short return window. This gives you time to test it thoroughly at home.
Before finalizing any deal, it helps to read a trusted gaming laptops review on models you're considering. Real-world feedback can reveal common issues, performance quirks, and long-term durability.
Before finalizing any deal, it helps to read a trusted gaming laptops review on models you're considering. Real-world feedback can reveal common issues, performance quirks, and long-term durability.
A 2nd hand gaming laptop can be a great investment—if you know what to look for. From checking internal specs to testing real-time gaming performance, this guide covers everything you need to make a smart purchase.
Spend a little time testing now, and you'll enjoy worry-free gaming later.
TIME BUSINESS NEWS
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
Yahoo
30 minutes ago
- Yahoo
Cloudflare (NET) Shares Skyrocket, What You Need To Know
Shares of internet security and content delivery network Cloudflare (NYSE:NET) jumped 5.1% in the afternoon session after Oppenheimer raised the firm's price target from $165 to $200 and kept a Buy rating following talks with Phil Winslow, Cloudflare's VP of Strategic Finance & Investor Relations. The firm expressed growing confidence in Cloudflare's long-term growth trajectory, particularly in its Secure Access Service Edge (SASE) offerings. It cited a number of growth catalysts, including accelerating adoption of Cloudflare's Wide Area Network (WAN) solutions and continued enhancements in its security stack, specifically in Cloud Access Security Broker (CASB) and Data Loss Prevention (DLP) tools. Contributing to the momentum, peer MongoDB reported strong first-quarter 2025 earnings, which confirmed that demand for cloud software is healthy, especially because MDB is a consumption model, so demand weakness shows up quite quickly. After the initial pop the shares cooled down to $179.19, up 4.9% from previous close. Is now the time to buy Cloudflare? Access our full analysis report here, it's free. Cloudflare's shares are very volatile and have had 25 moves greater than 5% over the last year. In that context, today's move indicates the market considers this news meaningful but not something that would fundamentally change its perception of the business. The previous big move we wrote about was 24 days ago when the stock gained 7% on the news that the major indices popped (Nasdaq +3.4%, S&P 500 +2.5%) in response to the positive outcome of U.S.-China trade negotiations, as both sides agreed to pause some tariffs for 90 days, signaling a potential turning point in ongoing tensions. This rollback cuts U.S. tariffs on Chinese goods to 30% and Chinese tariffs on U.S. imports to 10%, giving companies breathing room to reset inventories and supply chains. However, President Trump clarified that tariffs could go "substantially higher" if a full deal with China wasn't reached during the 90-day pause, but not all the way back to the previous levels. Still, the agreement has cooled fears of a prolonged trade war, helping stabilize expectations for global growth and trade flows and fueling renewed optimism. The optimism appeared concentrated in key trade-sensitive sectors, particularly technology, retail, and industrials, as lower tariffs reduce cost pressures and restore cross-border demand. Cloudflare is up 59.2% since the beginning of the year, and at $179.19 per share, has set a new 52-week high. Investors who bought $1,000 worth of Cloudflare's shares 5 years ago would now be looking at an investment worth $6,149. Unless you've been living under a rock, it should be obvious by now that generative AI is going to have a huge impact on how large corporations do business. While Nvidia and AMD are trading close to all-time highs, we prefer a lesser-known (but still profitable) semiconductor stock benefiting from the rise of AI. Click here to access our free report on our favorite semiconductor growth story. Error in retrieving data Sign in to access your portfolio Error in retrieving data Error in retrieving data Error in retrieving data Error in retrieving data
Yahoo
38 minutes ago
- Yahoo
Huawei struggles to break Nvidia's AI chip grip in China, says The Information
-- Recently, Huawei Technologies has emerged as NVIDIA Corporation's (NASDAQ:NVDA) most high-profile rival in the race to power artificial intelligence development in China. But according to a report from The Information, the Chinese tech giant is struggling to gain traction with major domestic customers despite rising interest in homegrown solutions. Nvidia CEO Jensen Huang has publicly warned of Huawei's growing capabilities and the broader acceleration of China's chip development efforts due to U.S. export restrictions. Yet ByteDance, Alibaba (NYSE:BABA), and Tencent Holdings Ltd (F:NNND) ADR (OTC:TCEHY), three of China's AI leaders, have yet to place significant orders for Huawei's Ascend chips, even as supplies of Nvidia's products tighten under U.S. trade controls. Multiple employees across leading firms told The Information that Huawei is "having a hard time convincing some of the biggest tech companies in China to use its chips." Engineers and executives at Chinese firms have voiced concerns over performance shortcomings with Huawei's hardware, as well as fear of violating American trade laws. Tests by firms such as ByteDance and Alibaba revealed issues with overheating in Huawei's Ascend 910C chip and limitations in its software stack, Cann, compared with Nvidia's industry-standard Cuda platform. Transitioning from Nvidia to Huawei would also involve a high switching cost, requiring a redesign of data center infrastructure, software, and engineering workflows. If the firms are to switch over to Huawei chips en masse, executives say that the company must adapt to its platform. Some developers, like DeepSeek, may play a pivotal role in shaping Huawei's trajectory as others watch closely to see whether an ecosystem can form around its chips. 'If DeepSeek is willing to adopt Huawei's chips and software in AI training extensively, it will attract many open-source developers to build their models on Huawei's ecosystem. But at the moment, that isn't the case,' said Bernstein semiconductor analyst Qingyuan Lin, cited by The Information. Huawei's new AI compute system, CloudMatrix 384, attempts to compensate for individual chip performance by linking as many as 384 Ascend processors together. But the system faces technical roadblocks, including high power consumption and lack of native support for FP8, a low-precision number format essential to cutting-edge AI training. A further complication is geopolitical: a recent U.S. Department of Commerce warning puts companies using Huawei's advanced AI chips at risk of 'substantial criminal and administrative penalties.' This has already led at least one Chinese data center firm to cancel a tentative order for Huawei hardware. Despite these obstacles, Huawei has secured meaningful sales to state-owned enterprises and local governments. But for now, top-tier Chinese tech firms show no sign of abandoning Nvidia, whose products still dominate high-performance AI systems, even as the regulatory pressure tightens on both sides of the Pacific. Related articles Huawei struggles to break Nvidia's AI chip grip in China, says The Information SoFi sees 'meaningful' Q2 growth ahead, shares rise Morgan Stanley starts Parker-Hannifin at Equal-weight rating
Forbes
an hour ago
- Forbes
Cracking The Code: How AI Revolutionizes Software Development
As more organizations awaken to the power generative AI holds for building software, this guide can light the way. Few practices stand to benefit from today's generative AI boom more than software development. Prompting GenAI systems to create code reduces repetitive processes and accelerates production cycles, freeing developers to focus on new, higher value projects. The upside is likely a big reason why 78% of developers surveyed by Stack Overflow said they were using AI-assisted programming tools to save time on routine tasks. Excitement aside, developers face learning curves while using GenAI to create code. Fortunately, Dell and NVIDIA have created this eBook, which follows a day in the life of a software developer whose team is tasked with conceptualizing a proof-of-concept (PoC). When Sam, an early career programmer, arrives at the office Monday morning she opens Jira and learns that her IT leadership team has requested a PoC sketch for a mobile shopping application. Building such a PoC could take multiple workdays but Sam knows that with the help of the company's coding assistant, named Clarion, she can quickly produce a mockup while minimizing mistakes. With her plan in mind, Sam begins prompting Clarion: You're a software developer. Please write a sample function for a mobile shopping app. Choose the most optimal language, such as Java or Python, to build the app. Sam watches her screen as Clarion instantly produces credible code that would have taken her an hour or more to write and refine. Clarion elected to write the code in Java, a choice Sam approves of given its track record of success in mobile app development. Going the extra mile in case leadership wants broader functionality, Sam prompts Clarion to connect the script via an API call to the Shopify mobile shopping service. Again, Clarion produces the code in seconds. But how does Sam know if the code is clean enough to work? She could pore over it line by line but not today. Sam asks Clarion to test and validate the code: Pretend you're a quality assurance tester. Execute a quality assurance test for the mobile app shopping script above. Be sure to debug the script and validate the code. Explain your work. Clarion quickly produces a debugging script and executing code validation. Moreover, knowing that documentation is a critical proof point for PoCs—or really any software development enterprise—Sam asks Clarion to document the entire technical process. Clarion does so in seconds. Reflecting on the process, Sam realizes that streamlining such tasks reduces the cognitive workloads on developers while enhancing overall code quality. Although Sam is excited by the potential of Clarion to turbocharge productivity for her IT organization, she is also pragmatic. As impressive as the output is, it's just the start. Leadership will expect a storyboard, wireframe and user interface schematics to flesh out a minimum viable product. She and her team must also check Clarion's work, consistent with her organization's guidelines for ensuring a human remains in the loop throughout the development process. Regardless, Sam huddles with her developer team, they check the code in and present the PoC to leadership. They are impressed by all the team accomplished in such a short time. Sam's scenario presents a snapshot of the potential productivity impact of GenAI. And as coding assistants advance, they will likely create a flywheel leading to more breakthroughs in AI—and corresponding productivity boosts. In time, McKinsey expects GenAI will alter the software development lifecycle, improving product quality while freeing teams to spend more time on higher-value work, including innovation that improves the user experience for internal stakeholders or customers. Regardless of the path organizations choose to take using GenAI to augment software development, they will need trusted expertise to help pick use cases, as well as robust technology infrastructure on which to deploy them. Dell Technologies and NVIDIA can help your organization leverage AI to drive innovation and achieve your business goals. The Dell AI Factory with NVIDIA delivers capabilities to accelerate your AI-powered use cases, integrate your data and workflows and enable you to design your own AI journey for repeatable, scalable outcomes. From NVIDIA accelerated computing, software and networking technology to Dell servers, storage and professional services, the Dell AI Factory with NVIDIA helps organizations achieve the optimal outcomes from their AI use cases. As GenAI reshapes the software development landscape, is your organization ready to seize on this shift? Learn more about the Dell AI Factory with NVIDIA.
