logo
1 year later, are the On Cloudmonster Hyper shoes still worth it? I laced them up to find out

1 year later, are the On Cloudmonster Hyper shoes still worth it? I laced them up to find out

Tom's Guide03-06-2025
The On Cloudmonster Hyper first landed in March 2024, and I've finally laced up these running shoes for a proper test run. Or rather, several runs over the past two months.
As someone who loved the original Cloudmonster, I was excited to see how this sleeker, speedier design would stack up.
The Hyper is designed as a more performance-focused take on the popular max-cushion daily trainer, aiming to deliver extra bounce and responsiveness thanks to premium foam tech. But is it really worth the $225 price tag?
Here's my honest take after putting this shoe through its paces.
At $220, the Cloudmonster Hyper is a pricier running shoe. But you're paying for a bold design and a special type of foam that feels both cushioned and springy underfoot.
The Cloudmonster Hyper looks fast. With a bold, sculpted design and sleek silhouette, it has the attitude of a race shoe even if it doesn't quite feel like one on the run.
I tested the women's version in the red (it's more pink than red) and cream colorway and really fell for the look. The black detailing made it surprisingly easy to match with my running outfits, especially black shorts, leggings and sports bras. That's not something I can say for most bright or neon-colored running shoes on the market.
If red and cream isn't your style, the Hyper also comes in a few other colorways, including a grey (Glacier/Ivory) and black (Iron/Black) in the women's version and a white (Silver/Iron), black (Black/Lima) and grey (Glacier/Ivory) in the men's version of the shoe
It's a shoe that looks ready to eat up fast miles, and visually, On has nailed the balance between performance and style. But, while the design shouts race day, the feel underfoot leans more toward plush daily miles than lightweight speedwork.
If you're not deep into running shoe lingo, here's a quick breakdown. The Cloudmonster Hyper is based on the Cloudmonster 2, but swaps in a unique kind of foam to make it feel lighter and bouncier underfoot.
Foam is the squishy stuff in the sole of your shoe, the bit between your foot and the ground. It absorbs shock, provides comfort and can give a little spring to your step.
In the Hyper, On replaces its regular foam (called Helion) with a lighter, more high-tech version called Helion HF in the top layer. It's made from Pebax, a material also used in elite racing shoes like the On Cloudboom Echo 3, and is designed to help you move more efficiently.
I hadn't tried the Cloudmonster 2, but I was a fan of the original Cloudmonster. That shoe was big, soft and fun to run in. So I was curious to see how the Hyper compared.
The Cloudmonster Hyper is a comfortable shoe, no doubt about it. The generous cushioning and slightly firm feel give it a sense of durability and support that's great for easy miles and recovery runs. The rocker design (that's the gentle curve through the sole) helps roll you forward with each step, keeping things pretty smooth and steady.
I really wanted this shoe to tick all the boxes, especially because I love how they look on. But while it works for comfort and everyday runs, it didn't feel especially light or quick when I picked up the pace. It's meant to be the more responsive version of the Cloudmonster 2, but for me, it still carries some of that big, max-cushioned bulk.
If you're after a shoe for steady, feel-good miles, the Hyper delivers. For a true all-rounder, I've found other daily trainers, like the Asics Novablast 5, to be a little more versatile and much cheaper.
Here's where things get tricky. The Cloudmonster Hyper costs $220 in the US and £210 in the UK. That's very expensive for a daily training shoe and more than some carbon-plated race shoes, which are usually considered the high-end of the running shoe market.
For that price, I expected a shoe that could handle all types of runs: long, easy and a bit of speed, too. But for me, it didn't quite tick every box. If you're mostly running easy miles and love On's bold look and feel, this might suit you fine.
But if you're shopping for one all-purpose daily trainer or a shoe to really get you going on speedier runs, I think there's better value to be found elsewhere.
The Cloudmonster Hyper is a super-cushioned shoe with a stylish edge. It uses fancy foam to add some pep to your stride, but it doesn't feel dramatically different from other big-cushion trainers and definitely not like a race-day shoe.
For me, it didn't live up to the 'Hyper' name in terms of speed or lightness. But I genuinely enjoyed running in these shoes for slow, steady miles and I loved the look.
If price isn't a dealbreaker and you love the look, it's worth considering. But if you want better value, you might want to explore other max-cushioned trainers that offer more versatility for less money.
Orange background

Try Our AI Features

Explore what Daily8 AI can do for you:

Comments

No comments yet...

Related Articles

'Earthquake inside Apple' — AI efforts just dealt another major blow
'Earthquake inside Apple' — AI efforts just dealt another major blow

Yahoo

time18 hours ago

  • Yahoo

'Earthquake inside Apple' — AI efforts just dealt another major blow

When you buy through links on our articles, Future and its syndication partners may earn a commission. Apple's push to catch up in the AI race has hit another serious roadblock. The company has lost Ruoming Pang, the highly respected leader of its foundation models team, to Meta — and insiders say the ripple effects are already being felt across Apple's AI division. Pang, who joined Apple in 2021 from Google DeepMind, was central to the company's efforts to build its own large language models (LLMs). His departure, along with that of several close collaborators, signals deeper unrest within Apple's AI ranks. As reported by The Information, Pang's exit and its aftermath has led to an 'earthquake inside Apple." Why Pang's exit matters Pang was known for his hands-on technical contributions, including developing a key open-source training tool for Apple's AI models. Under his leadership, Apple made strides in shrinking LLMs to run efficiently on iPhones, a critical part of its 'on-device AI' strategy. But those advances came with internal tensions. According to reporting from The Information, Pang's team had wanted to release some of Apple's AI models as open source earlier this year. This move could have shown progress while inviting collaboration from outside researchers. But Apple exec Craig Federighi reportedly shut it down, concerned it would expose performance compromises Apple made to run the models on iPhones. That disagreement was just one of many signs of friction between Apple's research-driven foundation models team and its product-focused leadership. A shift in power (and priorities) Earlier this year, Apple reorganized its AI efforts following delays to its revamped Siri assistant. The Siri team was pulled from longtime AI chief John Giannandrea and placed under Federighi, who also oversees Apple's software division. Meanwhile, Pang's team remained with Giannandrea, but the separation highlighted a growing divide between R&D and product execution. Now, with Pang gone and several of his top researchers either leaving or exploring offers from OpenAI, Anthropic, and Meta, Apple faces a major talent drain at a critical moment. Bloomberg recently reported that Apple is testing outside models, including those from OpenAI and Google, to power Siri, a move that reportedly disheartened many on the internal AI team. The bigger picture While Apple made headlines with its Apple Intelligence announcement in June, integrating ChatGPT into iPhones and showcasing writing and image-generation tools, the company's own foundation models remain behind closed doors. Insiders say there's still a lack of clear direction about whether Apple wants to compete head-to-head with models like GPT-4 or build more narrow, hardware-optimized tools. In an interview with Tom's Guide following WWDC 2025, Craig Federighi, Apple's senior vice president of software engineering, and Greg Joswiak, the senior vice president of worldwide marketing, made it clear that Apple doesn't want to make a chatbot. Without Pang's leadership and vision, some fear Apple's internal AI efforts could stagnate, or become overly reliant on outside partners. Others remain optimistic that the hiring of Zhifeng Chen, a former Google engineer now leading the foundation models team, will bring fresh momentum. Either way, Apple's AI ambitions face a decisive inflection point. As rivals like Meta, OpenAI and Google continue to poach top researchers and ship headline-grabbing models, Apple must prove it's still a serious contender in the generative AI era. More from Tom's Guide Claude 4 vs ChatGPT explained: What each AI does best — and how to choose the right one No, The Simpsons didn't predict that — here's how AI is fueling viral hoaxes (and how to spot them) I upgraded to Alexa+ for my busy family — here's what it did surprisingly well Sign in to access your portfolio

Ambiq Launches Two New Edge AI Runtime Solutions
Ambiq Launches Two New Edge AI Runtime Solutions

Hamilton Spectator

time2 days ago

  • Hamilton Spectator

Ambiq Launches Two New Edge AI Runtime Solutions

AUSTIN, Texas, July 22, 2025 (GLOBE NEWSWIRE) — Ambiq Micro, Inc. ('Ambiq'), a technology leader in ultra-low-power semiconductor solutions for edge AI, today unveils HeliosRT (Runtime) and HeliosAOT (Ahead-of-Time), two new edge AI runtime solutions optimized for the Ambiq Apollo Systems-on-Chip (SoCs) family. These developer tools are designed to significantly enhance the performance and energy efficiency of AI models for the unique demands of edge computing environments. Addressing Critical Edge AI Challenges As AI workloads increasingly migrate to edge devices, developers face growing pressure to deliver high performance within strict power budgets. Traditional AI frameworks often struggle in ultra-low-power scenarios, making it difficult to deploy sophisticated AI models in battery-powered devices, such as wearables, hearables, IoT sensors, and industrial monitors. Ambiq's new runtime solutions expand its growing portfolio of developer-centric tools, designed to help engineers unlock the full potential of Apollo SoCs. HeliosRT and HeliosAOT offer flexible, high-performance deployment options for edge AI across a wide range of applications, from digital health and smart homes to industrial automation and beyond. HeliosRT: Power-Optimized LiteRT HeliosRT is a performance-enhanced implementation of LiteRT (formerly TensorFlow Lite for Microcontrollers) that is tailored for energy-constrained environments. Fully compatible with existing TensorFlow workflows, HeliosRT introduces key improvements: HeliosAOT: Compiling LiteRT to Optimized C Code HeliosAOT introduces a ground-up, ahead-of-time compiler that transforms TensorFlow Lite models directly into embedded C code for edge AI deployment. This innovative approach offers runtime-level, or better, performance with additional benefits: 'The intersection of developer experience and power efficiency is our north star,' said Carlos Morales, VP of AI at Ambiq. 'HeliosRT and HeliosAOT are designed to integrate seamlessly with existing AI development pipelines while delivering the performance and efficiency gains that edge applications demand. We believe this is a major step forward in making sophisticated AI truly ubiquitous.' Powered by SPOT® and Real-World Success Both Helios solutions are built on Ambiq's patented Sub-threshold Power Optimized Technology (SPOT), which is the foundation behind over 270 million devices deployed worldwide. Leveraging years of hardware-software co-design, these tools deliver measurable performance gains and streamlined deployment for developers targeting the edge. Availability Both solutions are supported with robust documentation, ready-to-use examples, and dedicated engineering assistance for Ambiq customers. About Ambiq Ambiq's mission is to enable intelligence (artificial intelligence (AI) and beyond) everywhere by delivering the lowest power semiconductor solutions. Ambiq enables its customers to deliver AI compute at the edge where power consumption challenges are the most profound. Ambiq's technology innovations, built on the patented and proprietary sub-threshold power optimized technology (SPOT), fundamentally deliver a multi-fold improvement in power consumption over traditional semiconductor designs. Ambiq has powered over 270 million devices to date. For more information, visit . Contact Charlene Wan VP of Corporate Marketing and Investor Relations cwan@ +1.512.879.2850 A photo accompanying this announcement is available at

AI voice company Hyper raises $6.3M to help automate 911 calls
AI voice company Hyper raises $6.3M to help automate 911 calls

Yahoo

time3 days ago

  • Yahoo

AI voice company Hyper raises $6.3M to help automate 911 calls

'My whole life has been preparing me for this moment,' Ben Sanders said when asked about why he launched his emergency response startup Hyper. The company announced Monday a $6.3 million seed round led by Eniac Ventures, as well as an official emergence from stealth. As a child, he so wanted to become a police officer that he had his mother sew yellow stripes on his navy sweatpants. He wore that with an officer's rain hat for an entire year. As he grew up, he worked at the intersection of tech and government and once ran for federal office. Around a year ago, he read a news article about how his hometown was looking to use AI to reduce the wait time for emergency services. Sanders, who once launched an AI voice for drive-through restaurants, suddenly had an idea. Though he didn't think AI was quite ready to help with 911 calls, he felt this was a space for innovation, especially after realizing that most calls made to the emergency line are not considered emergency calls at all. Sanders teamed up with his friend Damian McCabe. The duo officially launched Hyper on Monday, offering an AI voice company that can handle some 911 calls. Sanders, who is CEO, said the product is to deal with the non-emergency calls that take time away from those critical calls that determine the 'difference between life and death.' McCabe is the company's CPO. Right now, even if a person looked to call their local police department, they would most often find a 10-digit number that routes them to the same people who take 911 calls. 'Imagine getting stuck talking to someone for eight minutes about a neighbor's dog barking, only to answer the next call late, because of that noise complaint, and hear the trembling voice of a 5-year-old whose dad has just collapsed on the floor,' Sanders said. Hyper answers questions, texts links, forwards calls, and even takes non-emergency police reports. 'Hyper always plays it safe, so if any calls fall outside the approved scope, or if one sounds slightly more emergency, we can automatically escalate those to a human expert just in case.' Sanders described the fundraising process as 'frenetic, manic, and fast.' It took him less than two months to raise the whole round, which was ultimately oversubscribed and included follow-on capital. Ripple Ventures, GreatPoint Ventures, Tusk Venture Partners, and K5 Global also participated in the round. Sanders said he met his connection at Eniac Ventures through a mutual acquaintance. Hyper hopes to use the fresh capital to help scale across the country, integrate more into existing 911 systems, hire a head of engineering, and build its next product. There is some competition in this space, like Aurelian, which also sorts non-emergency calls. Sanders said what makes Hyper different from the rest is its focus on 911. 'We train our models on real 911 calls with local agencies,' he said. 'We support more languages. And we've already gone live with many centers, which is a big operational hurdle in government and public safety.' Sanders hopes that Hyper can take away at least some of the stress associated with being a 911 caller, in a way that perhaps even brings more people to the profession. Right now, he says, most call centers are understaffed and struggling to hire. 'It's such a tough job, I don't even know if I could do it,' Sanders said. 'But I know how to build technology that can help; to help call-takers and dispatchers who are the unsung heroes; to help reduce their burden by tackling the non-emergency calls and noise, and in doing so, ultimately help save lives.'

DOWNLOAD THE APP

Get Started Now: Download the App

Ready to dive into a world of global content with local flavor? Download Daily8 app today from your preferred app store and start exploring.
app-storeplay-store