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Today — 12 May 2026Main stream

South Korea April 2026: Telsa and BYD break records

12 May 2026 at 08:12

The Tesla Model Y sells over 10,000 units in April.

The South Korean new light vehicle market edges up 0.8% year-on-year in April to 151,340 units, however this small gain has everything to do with foreign brands up 58.1% to 33,989 and 22.5% share whereas domestic brands fall -8.8% to 117,351. More precisely, the market is up thanks solely to Tesla up 811.5% to break its records for the third month in a row to 13,190 sales and 8.7% share. Meanwhile Kia (+7.9%) extends its now seemingly unassailable lead over sister brand Hyundai (-15.8%) to almost 8,000 units for the month and just above 16,500 units year-to-date. In 4th place below Tesla, Genesis (-40.3%) is in complete freefall and endures its lowest monthly volume in over 6 years: since March 2020. BYD (+272.6%) crosses the 2,000 monthly sales mark for the first time, reaching an all time high 9th place with 1.3% share.

In the domestic models ranking, the Kia Sorento (+37.3%) surges ahead to break its volume record for the 2nd month running at over 12,000 sales. The Hyundai Grandeur (+8.9%) is far below while the Hyundai Sonata (+22.4%) closes out the podium with a strong YoY gain. The Hyundai Avante (-22.9%), Kia Carnival (-34.2%) and Kia Sportage (-25.8%) follow and all sink. Meanwhile at #7 the Kia Ray (+14.4%) reaches an all time high ranking, also hit in August 2023 and February 2024. The Kia EV3 (+27.5%) also impresses and stays within the Top 10 at #10. The Kia EV5 (#15) is the best-selling recent launch ahead of the Kia PV5 (#21) and Renault Filante (#22).

Looking at foreign models, the Tesla Model Y (+1154.5%!) crosses the 10,000 monthly sales milestone and ranks #2 in the overall models charts including domestic vehicles. The Tesla Model 3 (+306.9%) also surges ahead and repeats at #2, followed by the BMW 5 Series (-7.5%) and Mercedes E Class (-22.2%) both in difficulty. The new BYD Dolphin advances to a record 5th place ahead of the BMW X3 (+53.1%), Polestar 4 (+277.1%) and Mercedes GLE (+23.3%), all sporting fantastic scores. The new BYD Sealion 7 lodges an 8th straight Top 10 finish at #9. 

Previous month: South Korea March 2026: BYD breaks records again, Renault Filante in Top 10

One year ago: South Korea April 2025: New gen pushes Hyundai Palisade to #4, Kia EV4 lands

Full April 2026 Top 30 All brands, Top 58 All domestic models and Top 50 foreign models below.

South Korea April 2026 – brands:

PosBrandApr-26%/25Mar2026%/25PosFY25
1Kia55,10836.4%+ 7.9%1196,77135.2%+ 6.0%12
2Hyundai47,18331.2%– 15.8%2180,19032.2%– 6.5%21
3Tesla13,1908.7%+ 811.5%334,1546.1%+ 445.2%36
4Genesis6,8684.5%– 40.3%432,9275.9%– 20.0%43
5BMW6,6584.4%– 0.8%526,0264.7%+ 2.8%54
6Mercedes4,7963.2%– 2.3%720,6583.7%+ 2.7%65
7Renault Korea4,0252.7%– 23.4%614,8942.7%– 21.0%77
8KGM3,3822.2%– 4.6%814,8522.7%+ 26.6%88
9BYD2,0231.3%+ 272.6%95,9911.1%+ 983.4%916
10Volvo1,1050.7%+ 3.5%104,7330.8%+ 3.5%119
11Lexus1,0790.7%– 20.3%124,8340.9%– 7.6%1010
12Audi9180.6%+ 12.4%114,0560.7%+ 42.5%1212
13Toyota8290.5%– 5.8%162,9820.5%+ 0.5%1414
14GM Korea7850.5%– 39.6%143,3250.6%– 38.1%1311
15Mini6960.5%+ 5.3%152,6510.5%+ 29.1%1615
16Porsche6790.4%– 37.0%132,7860.5%– 20.7%1513
17Polestar6750.4%+ 257.1%181,6290.3%+ 143.1%1820
18Volkswagen4580.3%+ 107.2%191,7510.3%+ 22.2%1718
19Land Rover2730.2%– 18.5%171,6100.3%– 1.2%1917
20Lincoln1200.1%– 4.8%281780.0%– 65.2%2623
21Jeep1020.1%– 28.2%204230.1%– 22.7%2021
22GMC730.0%+ 247.6%213580.1%+ 336.6%2130
23Cadillac670.0%+ 0.0%232150.0%+ 29.5%2425
24Honda660.0%– 59.3%222770.0%– 68.0%2222
25Ford550.0%– 90.4%252200.0%– 88.4%2319
26Bentley400.0%+ 300.0%261390.0%+ 131.7%2727
27Lamborghini290.0%+ 107.1%27800.0%– 37.0%2826
28Peugeot280.0%– 71.1%242120.0%– 15.5%2524
29Ferrari170.0%– 34.6%29750.0%– 42.3%2928
30Rolls-Royce130.0%– 51.9%30560.0%– 13.8%3031
 –Total local manufacturers117,35177.5%– 8.8% –442,95979.2%– 2.8% – –
 –Total foreign manufacturers33,98922.5%+ 58.1% –116,09420.8%+ 41.3% – –
 –Total market151,340100.0%+ 0.8% –559,053100.0%+ 3.9% – –

South Korea April 2026 – domestic models:

PosModelApr-26/25Mar2026/25PosFY25
1Kia Sorento12,078+ 37.3%139,029+ 10.0%11
2Hyundai Grandeur6,622+ 8.9%223,145– 1.4%25
3Hyundai Sonata5,754+ 22.4%421,119+ 20.7%311
4Hyundai Avante5,475– 22.9%619,826– 22.8%52
5Kia Carnival4,995– 34.2%719,392– 33.4%63
6Kia Sportage4,972– 25.8%520,327– 23.1%44
7Kia Ray4,877+ 14.4%1116,802– 1.2%812
8Hyundai Porter4,843– 9.8%318,752– 4.0%78
9Hyundai Santa Fe3,902– 38.6%1513,581– 37.8%127
10Kia EV33,898+ 27.5%1012,572+ 43.3%1422
11Hyundai Tucson3,858– 26.1%1415,014– 17.2%910
12Kia Seltos3,580– 29.8%813,691– 30.0%109
13Hyundai Palisade3,422– 48.6%2513,631– 22.7%116
14Kia Bongo3,335+ 1.0%2011,240– 9.5%1617
15Kia EV53,308new1610,192new1949
16Kia Morning3,186+ 209.9%307,842+ 103.4%2325
17Hyundai Staria3,039– 18.5%219,945– 23.1%2015
18Hyundai Kona2,559– 6.0%1212,702+ 27.5%1319
19Genesis G802,523– 41.9%1311,764– 21.3%1513
20Kia K52,366– 33.9%1810,360– 10.1%1716
21Kia PV52,262new1710,348new1845
22Renault Korea Filante2,139new97,099new26 –
23Genesis GV702,068– 33.1%199,841– 15.8%2118
24Genesis GV801,693– 42.2%228,306– 25.8%2220
25Hyundai Ioniq 51,674+ 14.8%237,625+ 84.8%2426
26Hyundai Bus/Truck1,562+ 24.6%295,941+ 18.5%2823
27Renault Korea Grand Koleos1,550– 64.6%325,958– 62.1%2714
28Kia K81,461– 43.1%247,232– 27.9%2521
29Kia EV41,432+ 72.3%275,511+ 563.2%2934
30Kia Niro1,289– 24.9%415,226+ 21.1%3227
31Hyundai Ioniq 91,225+ 21.4%334,439+ 124.9%3333
32Hyundai Casper1,142– 21.5%285,245– 8.0%3124
33KGM Musso1,135+ 99.5%265,505+ 549.2%3044
34Kia EV61,062+ 34.6%313,572+ 14.3%3430
35Hyundai Venue1,061+ 39.6%343,552+ 29.9%3528
36KGM Musso EV810+ 12.7%372,963+ 138.0%3737
37Chevrolet Trax Crossover613– 43.2%382,716– 36.1%3829
38KGM Actyon520+ 101.6%392,339+ 67.0%3935
39Hyundai Ioniq 6475– 22.1%363,153+ 106.6%3642
40Hyundai Nexo441+ 418.8%352,018+ 209.0%4139
41KGM Tivoli415– 3.0%431,774+ 15.1%4241
42Genesis G90409– 48.0%402,042– 19.2%4036
43Kia EV9393+ 162.0%46897+ 88.1%4653
44Renault Korea Arkana336– 22.4%441,479+ 10.4%4440
45KGM Torres327– 66.9%421,574– 50.4%4331
46Kia Tasman302– 75.8%451,406+ 4.6%4532
47Kia Bus/Special193+ 43.0%47678+ 41.3%4746
48Chevrolet Trailblazer168– 19.6%50592– 38.9%4848
49Hyundai ST1129+ 12.2%51502+ 16.2%5055
50Kia K9119– 19.0%52454– 31.2%5154
51Genesis GV6094– 36.1%53322+ 88.3%5558
52KGM Rexton New Arena90– 27.4%54335– 22.6%5457
53KGM Torres EVX85+ 14.9%49360– 54.4%5252
54Genesis G7062– 70.5%48505– 18.9%4950
55Genesis GV60 Magma19new5531new56 –
56Chevrolet Colorado4– 60.0%5616– 66.0%5763
57KGM Korando0– 100.0%572– 99.0%5860
58Renault Korea Scenic E-Tech0new58358new5359

South Korea April 2026 – foreign models:

PosModelApr-26/25Mar2026/25PosFY25
1Tesla Model Y10,086+ 1154.5%125,409+ 740.8%11
2Tesla Model 32,596+ 306.9%27,146+ 131.2%45
3BMW 5 Series1,887– 7.5%47,511– 1.3%33
4Mercedes E Class1,695– 22.2%38,530– 0.9%22
5BYD Dolphin800new91,527new17 –
6BMW X3692+ 53.1%112,665+ 22.9%78
7Polestar 4675+ 277.1%71,627+ 146.5%1426
8Mercedes GLE640+ 23.3%62,613+ 48.4%86
9BYD Sealion 7621new52,705new625
10Mercedes GLC597+ 92.6%82,910+ 23.7%54
11BMW X5564– 5.7%102,400+ 16.2%910
12BMW 3 Series553+ 11.7%132,236+ 28.1%109
13BMW 7 Series445+ 12.1%171,875+ 8.1%1113
14Tesla Model X427+ 42600.0%161,111+ 18416.7%23n/a
15BMW X7403– 8.4%181,581– 5.2%1514
16BYD Atto 3395– 27.3%n/a1,179+ 113.2%2022
17Audi Q4 e-Tron368+ 377.9%14986+ 14.5%2623
18Lexus NX363– 15.6%221,844+ 20.8%1218
19Volvo XC60359– 15.1%121,744+ 0.5%1311
20Lexus ES334– 41.3%211,555– 35.3%167
21BMW i5319+ 104.5%201,147+ 120.2%2136
22Mini Cooper Hatch314– 10.8%151,337+ 25.5%1915
23Mercedes CLE305+ 18.2%261,145– 1.5%2220
24Mercedes G Class304– 9.0%n/a716– 34.4%3421
25Mercedes S Class298– 4.2%251,343– 4.8%1812
26Audi Q5289n/a191,032n/a25n/a
27BMW X6261– 26.7%271,101– 18.6%2419
28Porsche Cayenne246– 54.1%42622– 53.6%3717
29Toyota Camry239+ 9.1%28833– 3.6%2931
30Lexus RX226+ 22.8%24826+ 30.7%3033
31BYD Seal207new38574new39n/a
32VW ID.4196+ 625.9%30793– 2.2%3143
33BMW X1188– 24.2%31727– 17.9%3328
34Volvo XC90184+ 73.6%36773+ 97.7%3238
35BMW X4179– 43.4%29846– 26.8%2816
36Toyota Alphard174+ 11.5%47544+ 21.4%4042
37VW Golf169+ 89.9%n/a492+ 452.8%41n/a
38BMW 4 Series164– 15.5%43596– 12.5%3832
39Porsche Taycan155+ 4.0%23874+ 37.4%2735
40Toyota Prius148+ 72.1%n/a410+ 74.5%46n/a
41Mini Countryman146+ 14.1%n/an/an/an/a40
42Volvo EX30145+ 25.0%35368– 44.1%5047
43Volvo S90144+ 58.2%39659+ 73.9%3639
44BMW iX1136+ 172.0%n/an/an/an/an/a
45Volvo XC40133– 40.4%34696– 21.8%3524
46Mercedes EQB133+ 1562.5%45449+ 1051.3%43n/a
47Toyota Crown132+ 207.0%n/a401+ 107.8%47n/a
48Porsche Macan EV122+ 100.0%50n/an/an/a41
49Mercedes EQE SUV119+ 65.3%n/an/an/an/an/a
50BMW iX112– 1.8%n/a434+ 127.2%45n/a

Source: KAIDA, Manufacturers

Yesterday — 11 May 2026Main stream

Intel Resurrects On-Package Memory With Razor Lake-AX, Loading Up LPDDR6 to Hunt Down AMD’s Medusa Halo by 2028

11 May 2026 at 21:51

Intel Resurrects On-Package Memory With Razor Lake-AX, Loading Up LPDDR6 to Hunt Down AMD's Medusa Halo by 2028

Intel's next-generation Razor Lake-AX chips will compete directly against AMD's Medusa Halo while featuring on-package memory. Intel Is Bringing Back On-Package Memory With Its Next-Gen Razor Lake-AX Chips That Fight Against AMD's Medusa Halo On-Package Memory was last used by Intel for its Lunar Lake SoCs. These SoCs were aimed at low-power mobile platforms, and while the chips themselves offered solid performance in a 30W budget, Intel's next on-package memory solution will be a big one. As per Haze2K1 on X, Intel Razor Lake-AX SoCs will feature on-package memory. This is a big deal as moving the DRAM closer to […]

Read full article at https://wccftech.com/intel-resurrects-on-package-memory-with-razor-lake-ax-to-hunt-down-amd-medusa-halo/

Google may be about to widen the SEO playing field

11 May 2026 at 19:00

SEO has always been a fight for the first page of Google. Every toolchain, audit, and content brief assumes that Google’s ranking systems evaluate a relatively fixed set of roughly 20 to 30 candidate pages before final rankings are determined.

Google has kept that set small because evaluating more pages is computationally expensive.

Google’s VP of Search acknowledged the constraint in federal court. The company’s CEO later confirmed the hardware bottleneck behind it. Google’s research division has now published a technique designed to reduce those costs.

If the candidate set widens, the rules of the last decade stop working.

Why the ranking window is 20 to 30 results wide

Here’s the exchange that matters from Day 24 of United States v. Google in October 2023. DOJ counsel Kenneth Dintzer cross-examining Pandu Nayak, Google vice president of Search, from transcript page 6431:

Q: RankBrain looks at the top 20 or 30 documents and may adjust their initial score. Is that right?
A: That is correct.

Q: And RankBrain is an expensive process to run?
A: It’s certainly more expensive than some of our other ranking components.

Q: So that’s, in part, one of the reasons why you just wait until you’re down to the final 20 or 30 before you run RankBrain?
A: That is correct.

Q: RankBrain is too expensive to run on hundreds or thousands of results?
A: That is correct.

Four consecutive confirmations. The deep-learning component of Google ranking that SEOs have built a decade of theory around is deliberately withheld from the bulk of the index because Google can’t afford to apply it more broadly.

The architecture feeding that reranking window is equally revealing. Earlier in the same testimony, at transcript page 6406, Nayak described classical postings-list retrieval to Judge Mehta: 

  • “[T]he core of the retrieval mechanism is looking at the words in the query, walking down the list, it’s called the postings list… [Y]ou can’t walk the lists all the way to the end because it will be too long.” 

The corpus gets culled to “tens of thousands” of pages before ranking begins, and from that pool only the top 20 to 30 results reach the deep-learning layer.

That runs against how most SEO commentary describes Google. The industry treats RankBrain, BERT, and other deep learning components as the definition of how Google ranks. Under oath, Nayak described them as expensive optional layers applied to a narrow window that classical retrieval has already culled.

Every practice in this industry that treats the top 20 to 30 as the competitive surface assumes it’ll stay that size. The testimony makes clear that the assumption is contingent, not foundational. The number could have been 50 or 500. It landed at 20 to 30 because that’s what Google’s hardware budget would support, and the constraint has held.

The constraint that held the number there is now in public view, and Google has published what comes next.

The wall and the algorithm that climbs it

On April 7, Sundar Pichai sat down with John Collison and Elad Gil on the Cheeky Pint podcast and described a set of hard supply constraints that no amount of CapEx will solve in the short term. The operative line: 

  • “To be very clear, we are supply-constrained. We are seeing the demand across all the surface areas.”

Pichai named five specific bottlenecks: wafer starts at the foundries, memory, power and energy, permitting for data centers, and skilled labor. Of the five, he pressed hardest on memory: 

  • “There is no way that the leading memory companies are going to dramatically improve their capacity.” 

For the 2026 to 2027 horizon, Google can’t buy its way past the memory bottleneck. Higher prices won’t create more capacity.

That matters because nearest-neighbor vector search, the mechanism behind modern semantic retrieval, is memory-bound. The wider the set of candidate pages a system can consider, the more memory it needs. The tight coupling between memory supply and retrieval breadth is what sets the cost boundary Nayak testified about.

On March 24, two weeks before the Cheeky Pint episode, Google Research published a blog post describing a technique called TurboQuant. The corresponding arXiv paper, “TurboQuant: Online Vector Quantization with Near-optimal Distortion Rate,” was authored by researchers at Google Research, Google DeepMind, and NYU.

The headline claims:

  • 4x to 4.5x compression of vector representations with performance “comparable to unquantized models” on the LongBench benchmark.
  • Nearest-neighbor search indexing time reduced to “virtually zero.”
  • Outperforms existing product quantization techniques on recall.

The paper covers two applications: KV-cache compression inside Gemini, and nearest-neighbor search in vector databases. Most coverage has focused on the Gemini application. The search-stack application is the nearest-neighbor-search half, and it’s the one relevant to the cost boundary Nayak described. 

If indexing is virtually free and memory per vector drops by 4x, the economics that held RankBrain at 20 to 30 candidates no longer apply. A system running on the same hardware could plausibly evaluate a candidate set several times larger.

TurboQuant hasn’t been confirmed as deployed in Google Search. TechCrunch reported at the time of announcement that it remained a lab breakthrough, and the March 2026 core update carried no public commentary from Google linking it to retrieval efficiency or vector quantization. Google has published the algorithm but hasn’t yet deployed it.

Google has been running quantized vector search in production for years through ScaNN. TurboQuant extends that approach rather than introducing it.

The question has shifted from whether the cost boundary can be moved to what SEOs do before it moves.

What to do before the boundary moves

Waiting for SERPs to confirm that retrieval has widened before adjusting is the losing strategy. The competitive surface is shifting. By the time it’s visible in rank-tracking tools, the positioning work of the next cycle is already done.

Three practical shifts are worth making now.

1. Measure whether your pages enter candidate sets

Rank tracking tools measure position within the set. They say nothing about whether a page was eligible for the set in the first place. In classical Search the distinction matters less because the set is narrow. In AI-mediated retrieval, and in a wider RankBrain-style window once it arrives, the distinction is the entire game.

The fastest check is server log analysis. Two classes of retrieval user agents matter. 

  • Search index crawlers build the corpus AI systems pull from. Some examples include:
    • OAI-SearchBot (ChatGPT search).
    • Claude-SearchBot (Claude search).
    • PerplexityBot.
    • Applebot (which also feeds Apple Intelligence). 
  • User-driven agents fetch pages on demand when someone asks an AI model about a topic your page covers: ChatGPT-User, Claude-User, and Perplexity-User.
    • These don’t execute JavaScript, so they’re invisible to GA4 and any analytics tool that depends on client-side tags. If the pages you care about aren’t appearing against either list, they aren’t in the candidate sets those systems construct, and ranking work can’t put them there.

Get the newsletter search marketers rely on.


2. Audit pages for retrieval-friendliness separately from ranking-friendliness

Ranking and retrieval reward different properties. The ranking signals you already know include topical authority, link equity, and query-intent match. Retrieval systems look for something else: a clear, self-contained, citable claim that can be extracted and evaluated without reading the whole document. 

A page written for ranking often buries its main claim under context-setting, caveats, and SEO-driven preamble. In a retrieval-ready page, the claim sits in the first 100 words, attached to an entity or statistic a retrieval system can verify, and surrounded by evidence worth citing. Most sites we audit fail this test even when they rank well.

3. Stop treating the top 20 to 30 pages as a fixed target

The window is a hardware constraint that has held for years because no one at Google could afford to widen it. Briefing content against “what ranks in positions 1 to 10 for this query” is briefing against a snapshot of a window that’s narrower than it needs to be because of hardware economics. 

When the economics change, the window will widen. Content built to compete inside a narrow set will face broader competition once it expands. The margin goes to content that was strong enough to enter a wider candidate set from the start.

None of the three requires predicting when TurboQuant or its descendants ship to production. They require acknowledging that retrieval economics is moving and positioning for what lies on the other side of the move, rather than for the current snapshot.

2026 is a year of change for SEO

The test is simple. Pull your server logs for the last 30 days. Count the retrieval user agents that have hit the pages you care about. If the answer is zero, or close to it, no amount of ranking work will move that number.

The competitive surface is shifting under you. The rest follows.

NVIDIA Squashes Vera Rubin Rumors, First Shipments Rolling Out In July To Major AI Customers With Mass Production In 2H 26

11 May 2026 at 05:25

NVIDIA Squashes Vera Rubin Rumors, First Shipments Rolling Out In July To Major AI Customers With Mass Production In 2H 26

NVIDIA has accelerated the rollout of its next-gen AI powerhouse, Vera Rubin, with first shipments commencing as early as July this year. Despite Rumors of Design Issues, NVIDIA is pushing ahead with a spectacular Vera Rubin Launch, The Center of Next-Gen AI A few days ago, we reported a few rumors that were going around regarding NVIDIA's Vera Rubin related to its design and specs changes. While the rumors sounded similar to what we heard about Blackwell GPU servers before their launch, NVIDIA has the ability to quickly address these pre-shipment drawbacks with the help of its supply chain partners, […]

Read full article at https://wccftech.com/nvidia-squashes-vera-rubin-rumors-first-shipments-rolling-out-in-july-to-ai-customers/

OPPO Find X9 Ultra vs Google Pixel 10 Pro XL: Camera, Performance, Pricing Compared

10 May 2026 at 17:06
Oppo vs Google

OPPO Find X9 Ultra and Google Pixel 10 Pro XL represent two very different flagship philosophies in 2026. OPPO focuses on cutting-edge hardware with a massive battery, ultra-fast charging, and an aggressive camera setup, while Google leans heavily on AI-powered software, refined photography, and long-term Android support. Both phones sit firmly in the ultra-premium segment, but the real question is whether raw flagship power matters more than a polished smart experience.

Major Features:

FeatureOPPO Find X9 UltraGoogle Pixel 10 Pro XLWinner
Display6.82-inch LTPO AMOLED, 144Hz, 3600 nits peak6.8-inch LTPO OLED, 120Hz, 3300 nits peakOPPO Find X9 Ultra – Higher refresh rate and brighter panel
Resolution1440 x 3168 pixels1344 x 2992 pixelsOPPO Find X9 Ultra – Sharper display
ProtectionGorilla Glass Victus 2Gorilla Glass Victus 2Tie – Same protection
ChipsetSnapdragon 8 Elite Gen 5Google Tensor G5OPPO Find X9 Ultra – More powerful flagship chipset
GPUAdreno 840PowerVR DXT-48-1536OPPO Find X9 Ultra – Stronger GPU performance expected
RAM & StorageUp to 16GB RAM, 1TB, UFS 4.1Up to 16GB RAM, 1TB, UFS 4.0OPPO Find X9 Ultra – Faster storage standard
Software SupportAndroid 16, 5 upgradesAndroid 16, 7 upgradesGoogle Pixel 10 Pro XL – Longer software support
Main Camera200MP + 200MP + 50MP + 50MP50MP + 48MP + 48MPOPPO Find X9 Ultra – More advanced camera hardware
Zoom Camera3x + 10x periscope zoom5x periscope zoomOPPO Find X9 Ultra – More versatile zoom setup
Video Recording8K30, 4K120, Dolby Vision, O-Log28K30 (cloud upscaled), 4K60, 10-bit HDROPPO Find X9 Ultra – More professional video tools
Selfie Camera50MP42MP ultrawideOPPO Find X9 Ultra – Higher resolution front camera
Battery7050mAh5200mAhOPPO Find X9 Ultra – Significantly larger battery
Wired Charging100W45WOPPO Find X9 Ultra – Much faster charging
Wireless Charging50W25W Qi2 magneticOPPO Find X9 Ultra – Faster wireless charging
Water ResistanceIP68/IP69IP68OPPO Find X9 Ultra – Better durability rating
Extra FeaturesInfrared portSatellite SOS, UWB, skin thermometerGoogle Pixel 10 Pro XL – More smart ecosystem features
Approx Price$1150 / ₹110000$1200 / ₹125000OPPO Find X9 Ultra – Better hardware value for lower price
Disclaimer: Specs are based on available data. Actual performance may vary. Verify details from official sources before buying.

Design and Display

Build and Feel

The OPPO Find X9 Ultra and Google Pixel 10 Pro XL both target premium flagship buyers, but they deliver very different personalities. OPPO goes for a more aggressive ultra-premium approach with IP68/IP69 protection, optional eco-leather finish, and a bold camera-focused design that immediately feels like a photography flagship. The Pixel 10 Pro XL looks cleaner and more refined with Google’s familiar horizontal camera bar and polished aluminum frame. It feels understated and professional rather than flashy.

OPPO also adds practical extras like an infrared blaster and stronger water resistance credentials, which may matter for long-term durability. The Pixel, meanwhile, keeps things minimalist and polished with tighter software integration and exclusive ecosystem features.

Display Quality

The Find X9 Ultra pushes ahead on paper with a sharper LTPO AMOLED panel, 144Hz refresh rate, Dolby Vision support, and an extremely bright 3600-nit peak brightness. The display feels more cinematic and slightly more immersive for gaming and HDR streaming.

Google’s 120Hz LTPO OLED panel still looks excellent with strong color calibration and excellent HDR tuning. However, OPPO clearly delivers the more hardware-focused display experience.

Verdict

The Pixel 10 Pro XL feels cleaner and more refined, but the OPPO Find X9 Ultra offers the more ambitious flagship hardware package. Its brighter 144Hz display and rugged premium build give it a noticeable edge for multimedia-heavy users.

Specifications Including Battery

Performance

The OPPO Find X9 Ultra is powered by the Snapdragon 8 Elite Gen 5, paired with UFS 4.1 storage and up to 16GB RAM. It is built for raw flagship performance and should comfortably handle high-end gaming, multitasking, and demanding AI workloads. The combination of Qualcomm’s latest chipset and ColorOS optimization makes the phone feel fast and responsive under almost every scenario.

The Pixel 10 Pro XL uses Google’s Tensor G5 chip, which focuses more on AI features, camera intelligence, and software smoothness than outright benchmark dominance. Day-to-day performance should remain excellent, but heavy gamers may still prefer Qualcomm’s stronger GPU advantage.

Battery and Charging

Battery life is one of OPPO’s biggest strengths here. The massive 7050mAh silicon-carbon battery combined with 100W wired and 50W wireless charging gives the Find X9 Ultra a major advantage. It is the kind of setup that feels built for power users.

Google’s 5200mAh battery is respectable, and Qi2 magnetic wireless charging adds convenience, but the slower 45W charging cannot match OPPO’s speed.

Verdict

The Pixel 10 Pro XL focuses more on smart software efficiency, while the Find X9 Ultra prioritizes raw flagship power. OPPO clearly wins for performance enthusiasts and heavy battery users.

Camera

Main and Secondary Lenses

The OPPO Find X9 Ultra delivers one of the most ambitious camera systems in the flagship market. Its dual 200MP setup, including a large periscope sensor, is paired with an additional 10x periscope zoom lens and Hasselblad color tuning. The phone is clearly designed for users who enjoy versatile photography and long-range zoom performance. Video capabilities also feel more professional with Dolby Vision HDR, O-Log2, and cinematic LUT support.

The Pixel 10 Pro XL takes a different approach. Google focuses heavily on computational photography with features like Best Take, Zoom Enhance, and Pixel Shift processing. Its camera tuning tends to produce more natural-looking shots with reliable dynamic range and skin tones. While the hardware is less extreme than OPPO’s, Google’s image processing still remains among the best in smartphones.

Selfie Camera

OPPO offers a sharper 50MP front camera with strong detail retention, while Google’s 42MP ultrawide selfie camera feels more practical for group shots and social content.

Verdict

The Pixel 10 Pro XL is likely the safer point-and-shoot camera for most users, but the Find X9 Ultra feels far more exciting for photography enthusiasts who want maximum zoom flexibility and advanced video tools.

Pricing

The OPPO Find X9 Ultra is expected to cost around $1150 (roughly ₹1,10,000), while the Google Pixel 10 Pro XL sits slightly higher at around $1200 (roughly ₹1,25,000). Despite the smaller gap in global pricing, the difference becomes more noticeable in India, where the Pixel carries a heavier premium.

At its price, the Find X9 Ultra offers stronger hardware value. Buyers get a larger battery, faster charging, a more aggressive camera setup, a higher refresh rate display, and flagship Qualcomm performance. It feels like a specification-heavy flagship designed to outperform competitors on paper.

The Pixel 10 Pro XL justifies its higher price differently. Google’s seven years of Android upgrades, AI-driven features, exclusive Pixel software tools, and cleaner Android experience still hold strong appeal. The phone feels more polished in software execution, even if the hardware specifications are less aggressive.

Verdict

The Pixel 10 Pro XL is priced for users who value Google’s software ecosystem, while the Find X9 Ultra delivers stronger hardware value for the money. OPPO feels like the better deal overall.

Disclaimer:
Prices are approximate and may vary based on country, region, launch timing, and applicable taxes. Always check whether the listed price is for a China unit or a global/international variant when purchasing.

Conclusion

The OPPO Find X9 Ultra stands out with its massive silicon-carbon battery, extremely fast charging speeds, dual 200MP camera system, and advanced zoom hardware. It feels like a flagship designed to push hardware boundaries in almost every category. Users focused on gaming, multimedia, battery endurance, and versatile photography will likely appreciate OPPO’s more aggressive approach.

The Google Pixel 10 Pro XL counters with cleaner Android software, deeper AI integration, long-term software support, and Google-exclusive camera intelligence features. Its experience feels smoother and more refined in daily use rather than purely specification-focused. Features like Satellite SOS, Qi2 wireless charging, and advanced AI editing tools help the Pixel maintain its premium identity.

Verdict

Both phones are elite Android flagships, but they target different priorities. The Pixel 10 Pro XL feels smarter and more polished, while the OPPO Find X9 Ultra feels more powerful and feature-packed. For users chasing cutting-edge hardware and better overall value, the Find X9 Ultra emerges as the stronger flagship package.

Disclaimer: This comparison is based on the specifications provided and is intended for general informational purposes. Actual performance, camera results, battery life, and overall experience may vary depending on real-world usage, software updates, and individual preferences.

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The post OPPO Find X9 Ultra vs Google Pixel 10 Pro XL: Camera, Performance, Pricing Compared appeared first on Gizmochina.

Before yesterdayMain stream

NVIDIA’s AI Chips Reached China’s Alibaba Through Thailand, As US Indicts Supermicro Execs In $2.5 Billion Smuggling Ring

9 May 2026 at 19:35

NVIDIA's AI Chips Reached China's Alibaba Through Thailand, As US Indicts Supermicro Execs In $2.5 Billion Smuggling Ring

NVIDIA's AI chips have once again bypassed barriers and landed at Alibaba in China, as the US suspects Supermicro's role in smuggling through Thailand. NVIDIA's AI Chips Still Carry Immense Interest In China As Alibaba Lands Restricted Supermico Servers That Were Smuggled Via Thailand Despite China dropping the hammer on NVIDIA's chips to increase dependency on in-house AI chips, the leading Chinese firms, such as Alibaba, are still procuring the latest hardware from NVIDIA through illegal channels. As per Bloomberg, several Supermicro employees, including high-level executives, are involved in a $2.5 billion smuggling case. The case revolves around shipping several […]

Read full article at https://wccftech.com/nvidia-ai-chips-reached-china-alibaba-through-thailand-smuggling-ring/

Google AdSense removes browser back button trigger for vignette ads

7 May 2026 at 19:39

Google is dropping the back button trigger for AdSense vignette ads on June 15, 2026 due to the new Google search penalty for back button hijacking. Google wrote, “Starting June 15, 2026, the browser back button will no longer trigger a vignette ad.”

What is changing. Google explained that the back button trigger will no longer work after June 15th. The “change will apply automatically for all publishers who have opted in to “Allow additional triggers for vignette ads” and will take effect across all supported browsers (including Chrome, Edge, and Opera).” Google added.

A Google spokesperson told me these same updates will apply to Ad Manager as well.

Why the change. Google explained that the Google Search team “recently introduced a new policy against “back button hijacking” — a practice where websites or scripts interfere with a user’s ability to navigate back to their previous page. To ensure our publishers remain compliant with these latest user experience and search quality guidelines, we are removing the trigger that shows a vignette ad when the user navigates backward from the suite of vignette ad triggers.”

This comes after the search community called this out to Google and Google is making the right change here. Of course, some publishers will not be happy because that trigger may have earned them a lot of money.

Why we care. If you currently have the allow additional triggers for vignette ads setting on with AdSense, keep in mind, one of the triggers, the back button trigger, will be disabled on June 15th. It may impact your earnings, but it will ensure that your site does not get penalized by the back button hijacking penalty.

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