Amazon Timeline

2026

July 16, 2026

Amazon dropped this Blink video doorbell and security camera bundle to 43% off - and we recommend it

This Blink Video Doorbell and Outdoor 4 security camera bundle deal will help you set up a home security system for less.

zdnetRead full article

July 16, 2026

The AI compute gap: Enterprises are buying infrastructure faster than they can measure what it costs

Across 107 enterprises, AI infrastructure spending is accelerating well ahead of the ability to see or steer its economics. Most organizations run their AI on a familiar base of hyperscalers and model-provider APIs, yet the next dollar is aimed at specialized compute almost none of them use today; a majority intend to switch or add providers within the year, many within a quarter. Buying decisions turn on integration and total cost of ownership rather than headline token price — which is fortunate, because most enterprises cannot yet see their unit economics clearly: GPUs sit at half utilization or less, and fewer than half rigorously track what their compute actually costs. The result is a compute gap — heavy, fast-moving investment running ahead of the visibility needed to control it.This wave of VentureBeat Pulse Research examines enterprise AI infrastructure and compute: where organizations are in their deployment journey, what they run AI on today, how satisfied they are, what would make them switch, where they plan to evaluate their investments, and — most revealingly — how well they can measure and control the economics of the compute underneath it all.The central finding is a compute gap — the distance between how aggressively enterprises are investing in AI infrastructure and how little of its economics they can see. Only about one in five (21%) run AI in production at scale, yet spending intentions are outrunning that maturity: the single largest planned area enterprises plan to evaluate over the next year is AI-specialized clouds (45%), a layer almost none of these enterprises use today. Meanwhile the compute already in place runs cold — 83% report GPU utilization of 50% or less — and fewer than half (44%) can rigorously track what their AI compute costs. Enterprises are buying more infrastructure faster than they can account for what they already own.Enterprises are not settled on their infrastructure vendors, either: A clear majority (64%) plan to switch or add an infrastructure provider within twelve months, and 38% within the next quarter — unusually high churn intent for a category this foundational. When they choose, they choose on integration with the existing stack (41%) and total cost of ownership (35%), not on headline price: cost per million tokens is the deciding factor for just 8%. And the frontier constraint that will shape the next round of decisions — the shift from GPU compute to memory bandwidth as inference scales — is barely on the radar, with roughly one in five enterprises either unaware of it or yet to address it.<h2>Methodology</h2>VentureBeat fielded this survey as part of its ongoing Pulse Research series, this survey focused on enterprise AI infrastructure, compute, and inference economics. Responses are filtered to organizations with more than 100 employees (n=107; the survey’s smallest size band, 1–100 employees, is excluded), drawn from a single Q2 2026 (June) wave. Because this is one wave rather than a pooled multi-month sample, the report reads cross-sectionally and does not infer month-over-month trends. Several questions were multiple-select, so those shares can sum to more than 100%.By organization size the sample concentrates in the mid-market: 101–250 employees (36%) and 251–1,000 (27%) lead, with 1,001–5,000 (22%), 5,001–10,000 (8%), and 10,001+ (7%) above them. By role it spans managers (38%), individual contributors (28%), VPs and directors (19%), and the C-suite (13%); on purchasing authority it is buyer-credible, with 45% final decision-makers and another 30% recommenders or influencers for AI solutions. Technology/Software is the largest industry at 26%, followed by Healthcare/Life Sciences (15%), Financial Services (13%), and Retail/E-commerce (12%).At 107 respondents the sample is large enough to read directionally but should be treated as a directional signal rather than a precise measurement; it is self-selected and is not a probability sample. It also skews toward the mid-market and toward earlier-stage adopters, so it is best read as the view from organizations actively building out AI infrastructure rather than from the largest hyperscale operators.<h2>Finding 1: Ambition outpaces production</h2>Only one in five run AI in production at scaleWe asked where organizations sit in their AI deployment journey. Most are still building toward production rather than operating at scale.<div></div><table><tbody><tr><td>38%</td><td>are experimenting — running proofs of concept, not yet in production</td></tr><tr><td>37%</td><td>have some workloads in production, but not across the organization</td></tr><tr><td>21%</td><td>run AI in production at scale — the mature minority</td></tr><tr><td>4%</td><td>are not yet running AI workloads at all</td></tr></tbody></table>The maturity curve is front-loaded. Three-quarters of enterprises (76%) are either experimenting or running only some workloads in production, and just 21% describe AI in production at scale. This matters for everything that follows: the infrastructure decisions in this report are being made largely by organizations still early in deployment, whose compute footprint — and whose costs — are about to grow. The evaluation and switching intentions in Findings 3 and 4 are the leading edge of that build-out, not the settled preferences of operators who have already found what works.<h2>Finding 2: Enterprises run on hyperscalers and model APIs</h2>The specialized GPU clouds barely register — todayWe asked which providers and platforms enterprises currently use to run their AI. The answer is a familiar one: the incumbents.<div></div><table><tbody><tr><td>48%</td><td>use Google Cloud — the most-used platform overall (Microsoft Azure 29%, AWS 22%, Oracle Cloud 22%)</td></tr><tr><td>41%</td><td>use Google’s Gemini models, with OpenAI close behind at 40% and Anthropic at 12%</td></tr><tr><td>6%</td><td>run their own on-prem or co-located GPU clusters; 4% a custom open-source self-managed stack</td></tr><tr><td><2%</td><td>each use the specialized AI clouds — CoreWeave, Lambda, Crusoe, Nebius, Together, Fireworks and peers</td></tr></tbody></table>The current stack is hyperscaler-and-API. Google Cloud leads at 48%, and the general-purpose clouds (Google, Microsoft, AWS, Oracle) together with the major model APIs (Gemini, OpenAI, Anthropic) account for essentially all current deployment. The specialized “neocloud” GPU providers that dominate AI-infrastructure headlines — CoreWeave, Lambda, Crusoe, Nebius and peers — register at or near zero among these enterprises today. Only 6% run their own on-prem GPU clusters and 4% a custom open-source stack. Enterprises are, for now, running AI on the providers they already buy from — which makes the evaluation intentions in Finding 3 all the more striking.(A note on reading these shares. As described in the methodology section, this sample is self-selected and skews mid-market, and this question counted every provider a respondent uses — an average of 2.1 selections each — so the figures measure presence in the stack rather than spending or primary status. A sample built this way will show a different provider mix than a spend-weighted census of the broader market; Google's strength here, for example, is consistent with its long-standing position among smaller enterprises building on AI. Read these shares as a portrait of what this AI-active cohort runs today, and treat gaps between these figures and industry-wide market share estimates as a property of the sample rather than a contradiction of either.)<h2>Finding 3: The next dollar goes to infrastructure they don’t yet run</h2>AI-specialized clouds top the evaluations listWe asked where enterprises planned to evaluate AI infrastructure over the next 12 months. Their answers point away from the stack they run today.<div></div><table><tbody><tr><td>45%</td><td>AI-specialized clouds (CoreWeave, Lambda, Crusoe, Nebius) — the top planned evaluation area</td></tr><tr><td>32%</td><td>non-NVIDIA accelerators (AWS Trainium, Google TPU, AMD Instinct, Intel Gaudi, in-house ASICs)</td></tr><tr><td>28%</td><td>Nvidia Blackwell (GB300) / next-generation GPUs</td></tr><tr><td>16%</td><td>decentralized or distributed compute networks</td></tr><tr><td>11%</td><td>sovereign or region-specific compute; 9% say none of the above</td></tr></tbody></table>Here is the report’s sharpest tension. The single most-cited planned evaluation area — AI-specialized clouds, at 45% — is the very category almost none of these enterprises use today (Finding 2). Nearly a third (32%) intend to evaluate non-Nvidia accelerators, and 28% in next-generation Nvidia silicon; even decentralized compute networks (16%) and sovereign compute (11%) draw meaningful interest. Read against current usage, this is not incremental — it is the leading edge of a re-platforming. The direction-of-travel question tells the same story: every infrastructure approach is net-expanding, but specialized AI clouds carry the highest net momentum (+24), edging out even the hyperscalers (+22). Enterprises are preparing to move a meaningful share of AI compute off the general-purpose cloud.This continues a trend we saw in our April-May survey wave. Back then, usage of the AI-specialized clouds was equally marginal — CoreWeave at 3%, Lambda at 4%, Crusoe at 2% of enterprises. When we asked enterprises what change they planned in their AI infrastructure strategy over the next twelve months, the most-cited answer was moving workloads to specialized AI clouds, at 33%. Asked in April-May which emerging compute option they were most likely to evaluate AI-specialized clouds again drew the most responses. Two waves, two differently worded questions, one consistent picture: the type of cloud enterprises are most eager to assess is the type they have barely begun to use.<h2>Finding 4: A switching wave is building</h2>Six in 10 plan to change providers within a year — many within a quarterWe asked whether and when enterprises plan to switch or add an infrastructure provider. Very few intend to stand still.<div></div><table><tbody><tr><td>38%</td><td>plan to change within the next 0–3 months — tied for the most common answer</td></tr><tr><td>36%</td><td>have no plans to change</td></tr><tr><td>22%</td><td>plan to change within 3–6 months</td></tr><tr><td>7%</td><td>plan to change within 6–12 months</td></tr></tbody></table>For a category as foundational as compute, this is a remarkable amount of intended movement. Only 36% have no plans to change, meaning a clear majority (64%) intend to switch or add a provider within twelve months — and 38% within the next quarter alone. Where that interest points is telling: the providers drawing the most switching consideration are again the incumbents — Microsoft Azure and Google Cloud (33% each), OpenAI (30%), and Gemini (22%) — which suggests much of the near-term movement is reshuffling among the majors and consolidating spend rather than defecting to new entrants. The neocloud interest in Finding 3 is a 12-month evaluation thesis; the switching in the next quarter is mostly incumbents trading share.(Method note: Respondents who selected both "no plans to change" and a specific switching window are counted as switchers, on the logic that naming a timeframe is the more specific answer; three respondents were reclassified under this rule.)<h2>Finding 5: Nobody buys on token price</h2>Integration and total cost of ownership decide — not sticker priceWe asked what matters most when enterprises select an AI infrastructure provider. Headline price finished last.<div></div><table><tbody><tr><td>41%</td><td>integration with the existing cloud and data stack — the top factor</td></tr><tr><td>35%</td><td>total cost of ownership (TCO)</td></tr><tr><td>24%</td><td>performance — latency and throughput</td></tr><tr><td>19%</td><td>each cite security/compliance, autoscaling for spiky workloads, and GPU access/availability</td></tr><tr><td>8%</td><td>cost per 1M tokens — the least-cited factor</td></tr></tbody></table>Enterprises do not buy AI infrastructure on pricing, which is the place vendors compete on hardest. Integration with the existing stack (41%) and total cost of ownership (35%) dominate, while the headline metric — cost per million tokens — is the deciding factor for just 8%, dead last. The pattern is coherent: buyers are optimizing for how a provider fits and what it truly costs to operate, not for the advertised unit rate. It also foreshadows Finding 7 — enterprises say TCO matters most, yet most cannot yet measure it rigorously. The stated priority and the measured capability are out of step.<h2>Finding 6: Expensive GPUs, idle most of the time</h2>83% report GPU utilization of 50% or lessWe asked what share of their GPU capacity enterprises actually utilize. The answer is a well-known but rarely quantified inefficiency.<div></div><table><tbody><tr><td>37%</td><td>run at 26–50% utilization</td></tr><tr><td>34%</td><td>run at 10–25% utilization</td></tr><tr><td>15%</td><td>run under 10% utilization</td></tr><tr><td>12%</td><td>run over 50% — the efficient minority</td></tr><tr><td>8%</td><td>don’t measure utilization at all; a further 7% consume via API and run no GPUs of their own</td></tr></tbody></table>Disclosure: Band percentages count every selection against all 107 qualified respondents; 14 respondents selected more than one band, so bands overlap. At the respondent level, 83 of the 100 GPU-operating enterprises reported utilization at or below 50%The compute already in place runs cold. Adding the bands at or below half capacity, 83% of enterprises that operate GPUs report utilization of 50% or less, and nearly half (49%) run at 25% or below. Only 12% clear the 50% mark, and a further 8% do not measure utilization at all. Idle accelerators are expensive accelerators, and this is the clearest single measure of the compute gap: enterprises are planning to buy more GPUs and specialized compute (Finding 3) while the capacity they already own sits substantially unused. The efficiency headroom in the current fleet is large — and largely unmeasured.<h2>Finding 7: Spending fast, measuring slowly</h2>Fewer than half rigorously track what their compute costsWe asked whether enterprises can quantify the cost and return of their AI infrastructure spend, and how satisfied they are with what they run. Confidence in the ledger lags the spending.<div></div><table><tbody><tr><td>44%</td><td>track compute cost and ROI rigorously</td></tr><tr><td>39%</td><td>track it only partially</td></tr><tr><td>20%</td><td>can’t quantify it yet</td></tr><tr><td>6%</td><td>say it isn’t a priority</td></tr></tbody></table>Measurement trails money. Fewer than half of enterprises (44%) rigorously track the cost and return of their AI compute; the majority track only partially (39%), cannot quantify it yet (20%), or have not prioritized it (6%). That gap is consequential given Finding 5, where total cost of ownership was the second-ranked buying criterion — enterprises are choosing providers on an economic basis they mostly cannot yet measure. Satisfaction with current infrastructure is moderately positive but not enthusiastic: on a five-point scale, overall satisfaction averages 4.0, with ease of implementation (3.8) and value for money (3.9) trailing slightly — the softness landing, tellingly, on cost. Enterprises are spending quickly and accounting slowly.<h2>Finding 8: The next bottleneck few are watching</h2>As inference shifts from compute to memory, the field scattersFinally, we asked how enterprises would address the emerging constraint in large-scale inference — the shift from GPU compute to memory, specifically KV-cache capacity. The responses reveal a frontier that is not yet a priority.<div></div><table><tbody><tr><td>31%</td><td>would rely on Dell (PowerScale / Project Lightning) — the leading single answer</td></tr><tr><td>16%</td><td>would rely on Nvidia (Dynamo / ICMSP)</td></tr><tr><td>18%</td><td>are not aware of this as a constraint (9%) or haven’t addressed inference-memory limits yet (8%)</td></tr><tr><td>10%</td><td>Hammerspace (Tier Zero); 9% DDN (Infinia); the rest split across open-source KV-cache tooling, model-level efficiency, VAST Data, and WEKA</td></tr></tbody></table>The memory frontier is real but barely governed. Asked which approach they would rely on as the binding constraint in inference shifts from compute to memory bandwidth, enterprises scatter: Dell leads at 31%, Nvidia follows at 16%, and the rest fragments across storage vendors, open-source tooling, and model-level efficiency techniques. Most telling is that roughly one in five (18%) either do not recognize the constraint or have not begun to address it. For a shift that will reshape inference cost and architecture, this is an early and unsettled market — and, consistent with the measurement gap in Finding 7, one where many enterprises simply do not yet have a view. It is the next chapter of the compute gap, arriving before most have closed the current one.<h1>The bottom line: A compute gap that faster spending will widen, not close</h1>Organizations with more than 100 employees are investing in AI infrastructure faster than they can measure it. Most are still early in deployment, yet their spending intentions point past their current stack — toward specialized clouds and alternative accelerators almost none of them run today — and a clear majority intend to change providers within the year. They buy on integration and total cost of ownership rather than headline price, which is rational; the difficulty is that most cannot yet see those economics clearly.The visibility gap is concrete. The GPUs enterprises already own run at half utilization or less for the overwhelming majority, and fewer than half can rigorously track what their compute costs or returns. Satisfaction is decent but unenthusiastic, softest on value for money — the dimension hardest to judge without measurement. And the next constraint, the shift from compute to memory in large-scale inference, is arriving while most enterprises are still unaware of it. At 107 respondents in a single Q2 wave this is a directional read, skewed toward the mid-market and earlier-stage adopters — but the direction is consistent: the appetite to spend is running well ahead of the instrumentation to spend well. The compute gap is not a capacity problem that more hardware will solve on its own; it is, first, a problem of seeing what the hardware already costs. The open question for later waves is whether enterprises build that visibility before the re-platforming arrives — or buy the next layer of infrastructure as blind to its economics as the last.<hr/>Based on survey responses from 107 qualified enterprise respondents (100+ employees), drawn from a single Q2 2026 (June) wave. Because this is one wave rather than a pooled multi-month sample, the results read cross-sectionally rather than as a month-over-month trend, and at 107 respondents this is a directional signal rather than a precise measurement — the sample is self-selected, skews mid-market, and leans toward earlier-stage adopters rather than the largest hyperscale operators. Respondents include managers, individual contributors, VPs/directors, and the C-suite, with buyer-credible purchasing authority, across Technology/Software, Healthcare/Life Sciences, Financial Services, Retail/E-commerce, and other industries.

venturebeat-aiRead full article

July 16, 2026

Amazon just cut $300 off the Google Pixel 10 Pro - and I'd recommend buying one

Google's Pixel 10 Pro has one of the best camera systems for an Android today. Grab it for $699 right now, one of the best prices we've seen.

zdnetRead full article

July 15, 2026

Amazon senior cloud executive departs after 18 years

Brown helped launch one of AWS' oldest services and also oversaw its compute and machine learning units.

cnbc-technologyRead full article

July 11, 2026

Burnout, frustration and heartbreak: Amazon layoffs take their toll in saturated job market

In the eight-plus months since Amazon announced its most expansive job cuts ever, laid off workers have been thrust into an increasingly saturated labor market.

cnbc-technologyRead full article

July 8, 2026

Prime Intellect raises $130M Series A to help enterprises build their own AI agents

The round, led by Radical Ventures, values the two-year old startup at $1 billion.

techcrunchRead full article

July 7, 2026

Amazon raising at least $25 billion in bond sale, won't issue more debt in 2026

It marks Amazon's latest debt raise as it looks to buttress its massive investments in artificial intelligence.

cnbc-technologyRead full article

July 7, 2026

ULA's last six Atlas Vs can't launch anything besides Boeing's Starliner

Amazon says it has enough satellites in orbit to begin initial broadband service at mid-latitudes later this year.

arstechnicaRead full article

July 6, 2026

Amazon competitor Bookshop.org says Kobo eReader support will happen this year after all

Bookship.org seemed to delay this anticipated partnership again, but tells TechCrunch that it has settled business terms and is working on integration.

techcrunchRead full article

July 5, 2026

Amazon will stop accepting new customers for Mechanical Turk

These may be the last days of Amazon’s Mechanical Turk.

techcrunchRead full article

July 3, 2026

This E Ink tablet replaced my iPad and Kindle - and it's 30% off on Amazon right now

If you're in the market for a tablet, look no further than the TCL Nxtpaper 11 Plus, especially at this price for the Fourth of July.

zdnetRead full article

July 3, 2026

The Tech Download: Amazon’s devices chief Panos Panay on tech giant's AI gadget push

CNBC's Arjun Kharpal sits down Amazon's Panay on the latest episode of The Tech Download podcast.

cnbc-technologyRead full article

July 2, 2026

A warning sign about AI’s real cost, courtesy of Google and Amazon

AI has made it a lot harder for tech companies like Amazon and Google to deliver on their net-zero pledges.

techcrunchRead full article

July 2, 2026

Amazon has deployed enough satellites to launch Leo service later this year

Leo will compete with SpaceX's Starlink, which had a four-year start over Amazon and has more than 10,000 satellites in its constellation.

cnbc-technologyRead full article

July 2, 2026

The 10 most popular products ZDNET readers bought last month (including during Prime Day)

From gadgets to streaming, these are the top tech gadgets and useful items our readers actually purchased in June.

zdnetRead full article

July 2, 2026

Amazon is designing its own AI chips for Echo, Fire TV and future devices, exec tells CNBC

Amazon hardware chief Panos Panay says the company is designing custom chips for key devices as it experiments with AI gadgets.

cnbc-technologyRead full article

July 1, 2026

Meta, like SpaceX, looks to turn excess AI compute into cash

Meta is developing plans for a cloud infrastructure business, selling access to AI compute power and models. The move would pit it against the big cloud providers like Amazon Web Services, Google Cloud, and Microsoft Azure.

techcrunchRead full article

June 30, 2026

Amazon blames piracy apps with malware for killing new Fire Stick sideloading

New Fire Stick OS helps Amazon block third-party homepage launchers, ad blockers.

arstechnicaRead full article

June 30, 2026

AWS puts $1 billion into new AI unit to embed engineers with customers, joining growing wave

AWS FDEs will look to leave behind self-sufficient teams with new AI solutions and capabilities in a matter of weeks, the company said.

cnbc-technologyRead full article

June 30, 2026

Amazon launches new $1 billion FDE org, following OpenAI and Anthropic

Engineers on the new team will embed within companies to deploy purpose-built agents, focusing on fast deployments and customer self-sufficiency.

techcrunchRead full article

June 30, 2026

Australia's competition regulator takes Amazon to court over alleged unfair Prime subscription contract terms

Australia's competition regulator is taking Amazon to court, alleging its Prime contracts required subscribers to pay AU$2.99 to avoid advertising, with no option for refunds

cnbc-technologyRead full article

June 29, 2026

Watch out, Amazon: The Kobo eReader now has a Goodreads rival

Kobo users can now automatically sync their reading progress to StoryGraph, making it easier to track books, reading stats, and challenges without relying on Amazon’s Goodreads.

techcrunchRead full article

June 29, 2026

Prime Day is over, but these 5 deals are still live (and you don't want to miss them)

Amazon Prime Day is over, but some of my favorite offers are still available, including deals on the Ninja Slushi, Garmin Fenix 8 Pro, Walmart Plus, and more.

zdnetRead full article

June 27, 2026

62 Last Minute Prime Day Weekend Deals: Up to 45% Off (2026)

Prime Day is officially over, but many of our favorite, hand-picked deals are still available through the weekend.

wired-businessRead full article

June 27, 2026

Best Buy's gaming deals are still live after Prime Day - Nintendo Switch, PS5, and more

Best Buy's competing Prime Day 2026 gaming deals will run through Sunday with massive savings on Alienware, Nintendo Switch, and Lenovo tech.

zdnetRead full article

June 27, 2026

Prime Day is over, but Walmart's big sale is still on: Up to 50% off laptops, TVs, & more

Walmart's massive rival Prime Day sale ends Sunday night, but great deals on 4K smart TVs, Apple tech, and laptops are still live.

zdnetRead full article

June 27, 2026

Prime Day is over, but these 60+ top deals are still live (for now): Apple, Garmin, LG, more

Amazon Prime Day 2026 deals have come and gone, but we're still seeing some of the same discounts live on editor-approved products like TVs, laptops, and more.

zdnetRead full article

June 27, 2026

This mesh system will make your at-home Wi-Fi lightning fast - and it's still 30% off for Prime Day

The TP-Link Deco 7 Pro is perfect for large houses with many devices, and each configuration is on sale right now.

zdnetRead full article

June 26, 2026

The most popular products during Amazon Prime Day 4: JBL and Bose speakers, Garmin watches, and more

We're tracking the items ZDNET readers have actually purchased during Prime Day sales so far today, and these deals are still here for a few more hours.

zdnetRead full article

June 26, 2026

The Apple Watch Series 11 is still under $280 on Amazon - but not for much longer

The Apple Watch Series 11 arrived last year with a full suite of health-tracking features and an extended battery life, and it's on sale for 30% off for a few more hours.

zdnetRead full article

June 26, 2026

My favorite Prime Day streaming stick deal will be gone soon - here's why you need it

Amazon Prime Day ends tonight, and this $25 Fire TV Stick 4K Plus is one deal you won't want to miss.

zdnetRead full article

June 26, 2026

I bring this Bose speaker to every outdoor gathering - get it for 33% off before Prime Day ends

Bose's SoundLink Plus is a great midsize speaker for indoor and outdoor use. It's on sale for Prime Day, but Amazon's sale ends tonight.

zdnetRead full article

June 26, 2026

The Best Prime Day Laptop Deals on My Personal Favorites

From MacBooks to gaming laptops, these are the very best deals on some of my very favorite laptops for Amazon Prime Day.

wired-businessRead full article

June 26, 2026

Best Ninja Prime Day Deals (2026) Slushi, Creami, Crispi, Cafe Luxe

Ninja Creami Swirl, Crispi, Slushi, and Cafe Luxe Pro are all on Prime Day deals that will soon go away.

wired-businessRead full article

June 26, 2026

Samsung’s Excellent OLED Monitors Are Up to 38 Percent Off for Prime Day

Samsung makes some of the very best OLED gaming monitors, and they’ve never been this affordable.

wired-businessRead full article

June 26, 2026

This Garmin smartwatch is half off while Prime Day lasts

The Garmin Epix Pro Gen 2 smartwatch is half off during Prime Day. Grab it before the sale ends.

zdnetRead full article

June 26, 2026

I can't live without these 7 kitchen and home gadgets - and they're still on sale for Prime Day

Amazon Prime Day ends tonight. These are the best home and kitchen deals I would grab before the sale is over.

zdnetRead full article

June 26, 2026

10 Best Prime Day Streaming Deals, Including Half Off Apple TV (2026)

Prime Day isn’t just about cheap TVs. It’s also about cheap stuff to watch on your cheap TV.

wired-businessRead full article

June 26, 2026

The business headphones I recommend most are 15% off in Amazon Prime Day's final hours

Jabra's Evolve3 75 boomless headphones is one of the most comfortable business headsets I've ever worn.

zdnetRead full article

June 26, 2026

I'm Adding These Bose Headphones to My Prime Day Cart (2026)

Bose headphones are already one of our favorites for comfort, sound, and noise canceling. Now they’re cheaper.

wired-businessRead full article

June 26, 2026

This GE Opal nugget ice maker makes 'the good ice,' and it's $160 off for Prime Day

Whether you call it the good ice, Sonic ice, or soft ice, you can now have it from the comfort of your kitchen - and I'd recommend this deal.

zdnetRead full article

June 26, 2026

This is the one smart home product everyone should have, and it's on sale

Smart light bulbs easily add ambiance to any home, and the GE Cync color-changing smart bulbs are discounted for Amazon's Prime Day, which ends tonight.

zdnetRead full article

June 26, 2026

27 Best Prime Day Beauty Deals of 2026 (We Sifted Through Hundreds to Pick Them)

It wouldn't be Amazon Prime Day without some beauty deals. Here's a roundup of all our favorites.

wired-businessRead full article

June 26, 2026

I Found the Best Prime Day Pixel Buds Deals: 2a, Pro (2026)

Google Pixel Buds are steeply on sale, presumably only through the end of the day.

wired-businessRead full article

June 26, 2026

Prime Day’s Best Handheld Fan Deals, Up to 20% Off, Are About to Disappear (2026)

These are the best last-minute Prime Day discounts on handheld fans, from $10 budget buys to Shark’s high-tech ChillPill.

wired-businessRead full article

June 26, 2026

Prime Day ends today: We hand-picked the 100+ best deals still live, before they disappear

LIVE: Amazon Prime Day 2026 deals are here, but not for long. Follow our live blog for real-time tracking on editor-approved products like TVs, MacBooks, Samsung devices, SSDs, and more before the sale ends tonight.

zdnetRead full article

June 26, 2026

Final hours for the best Amazon Prime Day SSD and storage deals - Samsung, Kingston, and more

I track SSD deals, and found huge markdowns from top brands like WD, Samsung, and more for Amazon Prime Day.

zdnetRead full article

June 26, 2026

The best last minute Prime Day smartwatch and fitness tracker deals I recommend right now

I'm a health and wearables editor, and these are some of the top smartwatch, smart ring, and wellness deals I've found for the last day of Prime Day.

zdnetRead full article

June 26, 2026

The 35+ best Sam's Club deals competing with Prime Day 2026 (including a $15 membership)

Beat Amazon Prime Day 2026 with Sam's Club Instant Savings. Get deals on premium TVs, home & kitchen tech, speakers, laptops, and more without a Prime fee.

zdnetRead full article

June 26, 2026

The 30+ best Prime Day robot vacuum deals I'd buy (after testing dozens of them)

Skip the fake sales: Check out our expert-vetted list of the absolute best Prime Day 2026 robot vacuum and mop deals worth your money today.

zdnetRead full article