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Next week kicks off with Apple’s first big product announcements of 2026. Tim Cook has hinted at a big week ahead using the Apple Launch hashtag. Apple has media events planned in New York, Shanghai, and London on Wednesday, March. 

We are looking forward to the iPhone 17E, a brand new budget MacBook, and some smaller updates to the Mac and iPad lines.  

Low-Cost MacBook 

Viewers suggest the new MacBook will look similar to the MacBook Air. It is expected to have an aluminum body in several colors and a display that’s either 12.9 or 13 inches, depending on which report you believe.  

A low-cost MacBook might be thin and light, since it’s expected to use a low-power A-series chip that doesn’t require much cooling, though this hasn’t been confirmed yet. Apple once had a 12-inch MacBook with a slim design and a low-power Core M chip, so that this new model could be a modern version of that older machine.  

Thinner and lighter typically means more expensive, while Apple products, so a super slim design might not be what Apple is optimizing for. Making the low-cost MacBook thinner than the MacBook Air could confuse the MacBook lineup.  

With the low-cost iPad, Apple keeps the price down by using older display technology that’s not as thin as we see. We see the same strategy with the low-cost MacBook: a thicker chassis and a super-efficient chip mean a long battery life, which is ideal for a learning setting.  

The budget MacBook will likely have:  

• a dimmer screen  

• no True Tone  

• no backlit keyboard  

• slower SSD speeds  

• and no N1 chip  

Colors 

The MacBook will come in a selection of fun colors, and Apple has tested light yellow, light green, blue, pink, silver, and dark gray, according to Bloomberg. Not all of those colors are likely to ship, but it sounds like we’ll get at least four of them.  

Analyst Ming-Chi Kuo expects the MacBook to come in yellow, silver, blue, and pink, the same colors as the iPad. The Book is planned to use its own chip rather than an M-Series Mac chip. Apple is planning to use an A-Series chip. The low-cost MacBook is expected to use the A18 Pro chip, which Apple first debuted in the iPhone 16 Pro.  

The A18 Pro uses a second-generation 3nm process. It has a 6-core CPU with four performance cores and two efficiency cores, along with a 6-core GPU and a 16-core Neural Engine for AI-based tasks, as shown in Geekbench benchmarks. The A18 Pro has an average single-core score of 3451 and a multi-core score of 8572. For comparison, the M4 iPad Pro scores 3694 in single-core and 13732 in multi-core. (Apple’s next MacBook Air will use the M5 chip.  

The A18 Pro is faster than the M1, which Apple used in cheaper MacBook Air models for years. In single-core performance, the A18 MacBook would be close to the M4 chips in Macs and iPads, but multi-core performance would still lag. The A18 chip would be more than powerful enough for day-to-day use, such as web browsing, document creation, watching videos, and even light photo and video editing. It won’t be ideal for system-intensive games or tasks like 4K video editing and 3D rendering, but it will do almost anything an iPhone or iPad can do.  

Apple is designing a budget MacBook for students, aiming to offer an Apple version of the affordable Chromebooks many students use.  

RAM 

Max starts with 16 GB of RAM, but the iPhone 16 Pro has 8 GB. The minimum for Apple Intelligence: we can expect an A18 Pro MacBook to have at least 8 GB of RAM to support Apple Intelligence, but Apple may equip it with 16 GB, as all Macs do.  

Storage 

The MacBook Air starts at 256 GB of storage, but Apple might launch the budget MacBook with just 128 GB.  

Ports  

The A18 Pro chip in the iPhone 16 models does not support Thunderbolt, so the MacBook will only use USB-C at 10 GB and will not reach Thunderbolt speeds. This means display connectivity will be limited, and the A18 Pro MacBook will probably support just one external display.  

Price 

The MacBook Air starts at $999, but the new Low-Cost MacBook is expected to be priced significantly lower.  

Apple will likely not want to price the new MacBook much lower than its iPads. The low-cost iPad with the A16 chip starts at $349, and the iPad Air with the M2 chip starts at $599. Pricing the MacBook between $599 and $799 would keep it less expensive than the MacBook Air or iPad Pro but just above or around the iPad Air’s price, $599, which would match the price of some popular Chromebooks often used in schools. A $699 or $799 price would be in a similar range but a bit more premium. $599 is also the price of the iPhone 17e, Apple’s most affordable phone, which uses a slightly less powerful A18 chip.  

iPhone 17e 

The iPhone 16e, which launched in February 2025, is due for a refresh. The iPhone 17e is getting some useful upgrades over the iPhone 16e, making it even more worth the purchase price.  

Design 

The iPhone 17E will have a design similar to the iPhone 16E with a 6.1-inch display, a single rear camera, and black and white color options.  

Display 

The iPhone 17E is expected to use the same display as the iPhone 16E, so that it will have a 60 Hz refresh rate. Apple added 120 Hz Pro Motion to the standard iPhone 17 in 2025. This feature is not expected on the more affordable iPhone 17E.  

The iPhone 17e will remain the only new iPhone without 120 Hz support. These improve video playback and make scrolling smoother when viewing web pages.  

The iPhone 16e does not have an Always-On Display, and this is likely to change with the iPhone 17e. Always-On Displays require an OLED screen with a minimum brightness of 1 nit, which is only available on Apple’s more expensive devices. The Apple iPhone 17e will also lack HDR and have lower brightness compared to flagship models. It has eliminated it in its new flagship phones, but some rumors suggest that the iPhone 17e will feature a dynamic island instead of a notch, giving it a more modern look.  

The Dynamic Align is a peel-shaped cutout on the iPhone’s display that houses the TrueDepth and front-facing cameras. It uses less screen space than the notch and is better integrated into the iPhone’s design. More’s indicated that we could get a Dynamic Align. Other rumors suggest the iPhone 17e will retain the notch, so the Dynamic Align upgrade isn’t guaranteed.  

A19 Chip 

The iPhone 17e will use Apple’s A19 chip, the same one found in the iPhone 17. This chip is built on an improved M3P3DMX process and offers a 5-10% performance boost over the A18 chip.  

Apple could be planning to use a downclocked version of the A19 chip in the iPhone 17e, meaning its performance would not fully match that of the iPhone 17’s 5-core GPU. Instead of a 5-core GPU like the one in the iPhone 16, the iPhone 17e could get a similar downgrade.  

Aside from the improved CPU and GPU, the A19 features an upgraded display engine, an image signal processor, and a neural engine for enhanced AI performance. Every GPU core features a neural accelerator to boost the performance of local AI models. The iPhone 17e is expected to have 8GB of RAM, just like the iPhone 16e. Other Apple models come with 12GB.  

MagSafe Compatibility 

The iPhone 16 does not have a MagSafe charging ring, but it is expected to add this feature. iPhones have used MagSafe since the iPhone12, so there is a wide array of MagSafe cases and accessories. The iPhone 16e is not compatible with these accessories, which is a major limitation.   

Without MagSafe, the iPhone 16E can only charge wirelessly at 7.5 W. With MagSafe, charging would increase to at least 15 W. The current iPhone 17 models can charge at 25 W with MagSafe, while the iPhone Air is limited to 20 W.  

Camera 

The iPhone 17e is expected to feature a single 48-megapixel wide-angle camera on the back, with no upgrades rumored. The iPhone 16e lacks a camera control button, and there is no indication that Apple will add one to the iPhone 17e.  

The iPhone 17 model features an upgraded 18-megapixel center-stage front-facing camera, but rumors suggest the iPhone 17e will continue to use the same 12-megapixel front camera as the iPhone 16e.  

C1X model and N1 chip 

The iPhone 17e will adopt Apple’s C1X model. The chip for Apple’s first iPhone, the C1X model, is faster and more efficient than the C1 model used in the iPhone 16e.  

Apple says the C1X modem is up to 2x faster than the C1 and far more energy-efficient than Qualcomm modems.  

Apple could also update the iPhone 17 models with Apple’s Wi-Fi and Bluetooth N1 networking chip, which brings speed and efficiency enhancements and thread support. Leaked Apple code suggests the chip will not only be included in the iPhone 17E to keep costs down, but that Apple also plans to add it to other models.  

Pricing 

The iPhone 16e is priced at $599, and no price changes are expected for the iPhone 17e.  

MacRumors Coverage 

Apple isn’t holding an event for the new announcements, so there won’t be a video. Pre-advert new products to be unveiled via press release on Monday, Tuesday, and Wednesday. Stay tuned to MacRumors for details on everything Apple unveils.  

Apple is adding a special experience for members of the media on March 4, 2026, during which we expect Apple to showcase new products. MacRumors will attend and share a hands-on look at what Apple has to offer.  

The special experience will take place at 9 am Eastern Time.

Source: What to Expect From Apple’s Big Week: iPhone 17e, Low-Cost MacBook, New iPads, and More 

AMD Ryzen AI Max+ 395, also known as Strix Halo, is currently the most powerful x86 APU available and offers a big performance boost over other options. It features 16 Gen5 CPU cores, over 50 peak AI TOPS with XDNA2 NPU, and a large integrated GPU with 40 AMD RDNA 3.5 Compute Units. This makes it a major upgrade for high-end thin-and-light devices. You can get the Ryzen AI Max Plus 395 with system memory options ranging from 32 GB to 128 GB of unified memory, with up to 96 GB of that available as VRAM with AMD Variable Graphics Memory.  

The Ryzen AI Max+ 395 performs especially well with consumer AI tasks such as using LM Studio, which LAMA CPP powers. LM Studio is becoming a popular choice for running language models on your own device, even if you have no technical background. It makes it easy to use new AI text and vision models right away.  

The new AMD Ryzen AI Max series, the Strix Halo platform, continues to lead in LM Studio performance.  

As a primal, the model size is dictated by the number of parameters and the precision used. Generally speaking, doubling the number of parameters (on the same architecture) or the precision will also double the model size. Most of our competitors’ current-generation offerings in this space max out at 32 GB of one-package memory. This is enough shared graphics memory to run large language models (up to 16 GB).  

Benchmarking Text and Vision Language Models in LM Studio 

For this comparison, we used the Asus ROG Flow Z13 with 64 GB of unified memory. We limited the language model size to 16 GB so it would work on a competitor’s 32 GB laptop. We measured latency by looking at the time to first token (how long it takes the model to start responding) and tokens per second.  

The results show that the Asus ROG Flow Z13, which uses the integrated Radeon 8060S and 256GB of bandwidth, easily achieves 2.2 times the token throughput of the Intel Arc 140V.  

The performance uplift is very consistent among different model types (whether you are running Chain of Thought, Deep Seek R1, Deep Tales, or Standard models like Microsoft Phi 4) and different parameter sizes.  

In Time-to-First-Token Benchmarks, the AMD Ryzen AI Max+ 3950X processor is up to 4x faster than the competition on smaller models like LAMA 3.2 3B Instruct.  

For larger models with 7 or 8 billion parameters, like Deep Sea R1 Distal Queen 7B and Deep Sea R1 Distal Llama 8B, the Ryzen AI Max+ 395 is up to 9.1 times faster. With 14 billion parameter models, which is about the largest that fits on a standard 32GB laptop, the Asus ROG Flow Z13 is up to 12.2 times faster than a laptop with an Intel Core Ultra 258V. This is more than 10 times faster than the competition.  

The larger the LLM, the faster the AMD Ryzen AI Max+ 395 processor responds to your queries. Whether you are chatting with the model or giving it large summarization tasks with thousands of tokens, the AMD system will respond much more quickly. This advantage grows as the prompt gets longer, so the more demanding the task, the greater the speed difference. The IBM Grand Light Vision is one example, and the recently launched Google Gemma 3 family of models is another, with both providing highly capable vision capabilities to next-generation AMD AI PCs. Both these models run performantly on an AMD Ryzen AI Max+ 395 processor.  

An interesting point to note here: when running vision models, the time to first token also measures how long the model takes to analyze your image. Vision 3.2 3b is up to 4.6x faster in Google JAMA 3 4b and up to 6x faster in Google JAMA 3 12b. The Asus ROG Flow Z13 came with a 64 GB memory option, so it can also effortlessly run the Google JAMA 3 27b vision model, which is currently considered SOTA (state-of-the-art) in vision.  

Another example is running the Deep Seek R1 distal quan32b in 6-bit precision, while 4 bits are the industry standard for most users. Coding often requires higher precision for accuracy. With this setup, you can code a gaming classic in about 5 minutes.

Source: AMD Ryzen™ AI MAX+ 395 Processor: Breakthrough AI Performance in Thin and Light 

Introduce Vision OS 26 today, a major update with new spatial experiences and features for Apple Vision Pro. Every day use feels increasingly immersive and personal, thanks to:  

• Widgets that fit into your space  

• AI-powered spatial scenes that add life-like depth to photos  

• Improve personas and look more natural.  

• Mutual experiences for Vision Pro users in the same room  

Vision OS 26 also adds support for 180-degree, 360-degree, and wide-field-of-view content from Insta360, GoPro, and Canon. While new enterprise APIs enable organizations to create unique experiences on Vision OS, with support for PlayStation VR 2 Sense controllers, players can enjoy a new class of games on Apple Vision Pro 1.  

Apple Vision Pro has set the standard for spatial computing, and with Vision OS 26, we are taking it even further, said Mike Rockwell, Apple’s Vice President of Vision Products Group. We are thrilled for users to try new ways to connect, explore, work together, and enjoy, including customizable apps and widgets, new spatial scenes for photos, and improved personas on Apple Vision Pro.  

Widgets Become Spatial 

Widgets on Apple devices give users personalized information at a glance. With Vision OS 26, widgets become spatial, fitting right into your space and showing up each time you use Apple Vision Pro. You can customize widgets with different frame widths, colors, and depths. New widgets, such as clock, weather, music, and photos, offer unique ways to interact.  

Users can decorate their spaces with favorite widgets, including:  

• stunning panoramas and special photos of their beloved memories  

• clocks with distinctive face designs and quick access to their go-to playlists and songs on Apple Music  

The widgets app helps users find widgets, including those from compatible iOS and iPadOS apps. Developers can also create their own widgets using WidgetKit.  

Enhanced Shared Spiritual Experiences 

Users love how Vision OS lets them connect with family, friends, and colleagues remotely. With Vision OS 26, they can share spatial experiences with fellow Apple Vision Pro users in the same room. They can come together to watch the latest 3D blockbuster, play a spatial game, or collaborate with coworkers. Users can also add remote participants from across the world via FaceTime, enabling connection with people near and far.  

Dassault Systèmes, a leading provider of engineering and 3D design software, is exploiting this capability with its 3D Live app, enabling the visualization of 3D designs both in person and with remote colleagues.  

With Vision OS 26, personas feel more natural and familiar thanks to industry-leading volumetric rendering and machine learning. The all-new personas are now striking in their expressiveness and sharpness, offering a full-size profile view and remarkably accurate hair, lashes, and complexion. Personas are still created on the device in a matter of seconds, and new improvements to the setup process allow users to adjust and preview how their persona looks spatially and even pick glasses from over 1,000 variations.  

Introducing Spatial Scenes 

Noise makes photos look more realistic by using a new generative AI algorithm and computational depth. This creates spatial change with multiple perspectives, so users feel like they can lean in and look around.  

Users can view spatial scenes in photos, the spatial gallery, and Safari apps. Developers can use the Spatial Scene API to make their apps increasingly immersive. Zillow uses this API in their Zillow Immersive App, letting users view homes and apartments with added depth and dimension.  

New Ways To Browse, Play, And Watch 

With spatial browsing in Safari, users can transform articles, remove distractions, and see spatial scenes that come to life as they scroll. Web developers can embed 3D models in web pages so users can shop, browse, and interact with 3D objects directly in Safari.  

Ryzen OS 26 supports native playback of 180-degree, 360-degree, and wide-field-of-view content from Insta360, GoPro, and Canon. Users may enjoy their exciting 2D action footage the way it was meant to be seen. Developers can incorporate this new playback capability into their apps and websites.  

Vision OS 26 now supports the PlayStation VR 2 Sense controller. Developers can create highly engaging games for Apple Vision Pro using features such as advanced motion tracking, finger touch detection, and vibration feedback.  

Enterprise APIs and Tools 

Businesses worldwide are using Spatial Computing on the Apple Vision Pro to improve their processes across design, training, sales, and education. With new team device sharing, organizations can easily set up and manage shared devices. Users can save their eye and hand data, vision description, and access settings to their phone with iPhone iOS 26, then use them on another Vision Pro. This makes sharing devices much simpler.  

The OS 26 now supports Logitech Muse, a spatial accessory made for Apple Vision Pro. It allows for more accurate input and new ways to use collaboration apps like Spatial Analogue.  

Enterprise APIs, such as the new Protected Content API, ensure that only authorized users can view confidential materials, including medical records and business forecasts. These tools also block copying screenshots and screen sharing.

Source: visionOS 26 introduces powerful new spatial experiences for Apple Vision Pro 

OpenAI released the O3 Mini in early 2025. This smaller reasoning model is built for STEM tasks and offers better intelligence and lower latency than the O1 Mini. Users can choose low, medium, or high reasoning effort. It can also be used to create high-value, cost-effective, real-time use.  

STEM Raising Performance 

O3 Mini performs very well at a medium effort level. It equals the larger O1 model’s functions but responds faster and more accurately.  

• In the 2024 AIME Math Test, O3 Mini with high reasoning effort did better than both O1 Mini and the full O1 model.  

• Reputation coding (Codeforces): O3 Mini achieves an ELO rating of 27/27, significantly higher than O1 Mini’s 1891. It outperforms the O1 Mini high in programming tasks.  

• On the GPQA Diamond Science Test, O3 Mini scored 87.7% on PhD-level questions, which is 10% better than O1 Mini.  

• In software engineering tests (SWE Bench Verified), O3 Mini is the top performer in its series. With significant effort, it solves complex tasks and often beats the O1 Mini by more than 20% in software benchmarks.  

• Experts found that O3 Mini made 39% fewer major errors than O1 Mini.  

Latency and Speed Metrics 

• Training effort customization: users can select low, medium, or high effort to trade off speed and accuracy. Models are 63% cheaper than the O1 Mini.  

• Advanced features:  

• Supports function calling  

• Structured outputs and developer messages  

• One limitation is that O3 Mini does not support vision features like the O1 model.  

Comparison with other models. 

• Compared to the O1 Mini, the O3 Mini is faster, cheaper, and more accurate. It also does better in coding and math competitions.  

• Versus DeepSeek R1: While DeepSeek R1 is frequently more cost-effective per token, O3 Mini is generally faster for live coding and STEM tasks, and it shows superior safety with a lower rate of unsafe responses (1.19% versus 11.98%).  

Today we’re launching OpenAI O3 Mini, our latest and most affordable reasoning model, now available in ChatGPT and through the API. First reviewed in December 2024, this fast and capable model pushes the limits of small models, offering strong STEM skills, especially in science, math, and coding. It also keeps the low cost and fast response times of OpenAI O1 Mini.  

OpenAI O3 Mini is our first small reasoning model to support popular developer features like function calling, structured outputs, and developer messages, making it ready for production use right away. Like OpenAI O1 Mini and O1 Preview, O3 Mini also supports streaming. Developers can choose from three reasoning effort options: low, medium, or high, to fit their needs best. This means O3 Mini can focus more on tough problems or work faster when speed matters. O3 Mini does not handle vision tasks, so developers should use OpenAI for those starting today. O3 Mini is available in the Chat Completions API, Assistance API, and Batch API for select developers in API user tiers 3-5.  

Starting today, ChatGPT Plus, Team, and Pro users can use OpenAI O3 Mini, and Enterprise users will get access in February. O3 Mini will replace O1 Mini in the model picker, offering higher rate limits and faster responses. This makes it a great choice for coding, STEM, and logic tasks. Plus and Team users will now have their daily message limit increased from 50 to 150 with O3 Mini. O3 Mini also now supports search, helping users find current answers with links to web sources. The search feature is an early prototype while we work to add it to more models.  

Free plan users can now try O3 OpenAI O3 Mini by choosing a region in the message composer or by regenerating a response. This is the first time a reasoning model has been available to two free ChatGPT users.  

OpenAI O1 remains our main model for general knowledge, while OpenAI O3 Mini is designed for technical fields that require accuracy and speed. In ChatGPT, O3 Mini uses a medium level of understanding effort to balance speed and accuracy. Paid users can also choose O3 Mini High in the model picker for a smarter version that takes a bit longer to reply. Pro users get unlimited access to both O3 Mini and O3 Mini High.  

Fast, Powerful, And Built For STEM Reasoning 

Tech: OpenAI O1 and O3 Mini are tuned for STEM reasoning. With medium reasoning effort, O3 Mini matches O1’s performance in math, coding, and science, but responds faster. Expert testers found that O3 Mini provides more accurate, clearer answers with better reasoning than O1 Mini. They preferred O3 Mini’s answers 56% of the time and saw 39% fewer major errors on tough real-world questions. With moderate effort, O3 Mini matches O1’s results on challenging tasks, such as AIME and GPQA.  

What’s Next? 

The launch of OpenAI O3 Mini is another step forward in our effort to make cost-effective intelligence possible. We have improved the rationale for STEM fields and kept costs low so people can access high-quality AI. Since GPT-4, we have reduced per-token pricing by 95% while still offering strong reasoning abilities. As more people use AI, we are committed to leading the way by building models that are smart, efficient, and safe at scale.

Source: OpenAI o3‑mini 

Decompression helps reduce storage costs and speed up data transfers across databases, data centers, high-performance computing, deep learning, and other areas. However, decompressing this data can slow things down by adding latency and using valuable computing power.  

To address these challenges, NVIDIA introduced the hardware decompression engine DE in the NVIDIA Blackwell architecture and created it for the nvCOMP library. Together they offload decompression from general-purpose compute, accelerate widely used formats like Snappy, and make adoption seamless.  

In this blog, we will explain how DE and nvCOMP work, share usage tips, and highlight the performance benefits they deliver for data-intensive tasks.  

How The Decompression Engine Works 

The new DE in the Blackwell architecture is a dedicated hardware block that speeds up decompression for snappy LZ4 and D-flat-based streams. By handling decompression in hardware, the DE lets streaming multiprocessor (SM) resources focus on computation rather than data movement.  

The DEE is built into the copy engine. You no longer need to do host-to-device copies and then run software decompression. Now, compressed data can move directly over PCIe or C2C and be decompressed as it travels, helping remove a major I/O bottleneck.  

The DE does more than boost throughput. It allows data movement and computation to occur simultaneously. With multi-stream workloads, decompression can run in parallel with SM kernels, so the GPU stays busy. This helps with data-intensive tasks like training LLMs, evaluating large geonomics datasets, and/or running HPC simulations, keeping up with the high bandwidth of Blackwell GPUs without being slowed down by I/O.  

The Benefits of NvComp’s GPU-Accelerated Decompression 

The NVIDIA nvCOMP library offers GPU-accelerated routines for both compression and decompression. It works with many standard formats, as well as formats that NVIDIA has tuned for top GPU performance.  

Standard formats, CPUs, and fixed-function hardware often have an edge over GPUs because GPUs have less parallelism for these tasks. The decompress engine solves this issue for many workloads. Next, we will explain how to use nvCOMP with the DE.  

How to use DE and nvCOMP 

Developers should use DE through the nvCOMP API’s. Right now, DE is only on certain GPUs (B200, B300, GB200, and GB300), so using nvCOMP lets you write code that works among different GPUs as support grows. If DE is available, nvCOMP uses it automatically. If not, it switches to its fast SM-based methods without needing changes to your code.  

To ensure this works on DE-enabled GPUs, follow these steps. nvCOMP usually accepts any input and output buffers that the device can access, but the DE has stricter rules. If your buffers don’t meet these rules, nvCOMP will use the SM or decompression instead.  

You can use cudaMalloc as usual for device-to-device decompression. For host-to-device or host-to-host decompression, use cudaMallocFromPoolsync or active cuMemCreate, but make sure to set up the allocators correctly.  

How SM Performance Compares to DE 

DE offers faster decompression and lets the SM handle other tasks. The DE has dozens of execution units, while SMs have thousands of volts. Each DE unit is much faster at decompression, but in some cases, a fully loaded SM can come close to DE speed. Both SM and DE can use cost-pinned data as input, enabling zero-copy decompression.  

The next figure shows how SM and DE perform on the Silesia benchmark for LZ4, D-flat, and Snappy algorithms. Snappy has been newly optimized in nvCOMP 5.0, and there are more chances to improve D-flat and LZ4 as well.  

Performance was measured using 64KiB and 512KiB chunk sizes on both small and large data sets. The large data set is the full Silesia dataset, and the small data set is the first 50 MB of Silesia.tar.  

Get started 

The Decompressor engine in Blackwell helps solve one of the biggest problems in data-heavy workloads: getting first efficient decompression. By moving this job to a dedicated hardware application, it runs faster and frees up GPU resources. For other tasks, operators can take advantage of these improvements without changing their code, leading to better pipelines and better performance.

Source: Speeding Up Data Decompression with nvCOMP and the NVIDIA Blackwell Decompression Engine 

Samsung Electronics has announced the One UI 8.5 Beta program, which brings simpler ways to create, connect, and stay secure. With this update, CUV users can get more done with less effort, thanks to easier actions, easier device management, and better security.  

One UI 8.5: What’s New for Content Creation 

One UI 8.5 makes it easier to create and share content. With the updated photo assist, users can keep making new images without stopping. They can edit photos as much as they want, without saving each step along the way, when they are done. It is easy to review the edit history and choose their favorite versions.  

Sharing is now easier with improvements to Quick Share, which can recognize people in photos and suggest sending the images directly to those contacts.  

How does One UI 8.5 improve device connectivity? 

New cross-device feature: make it simpler to manage devices, share files, or connect with nearby devices. Audio broadcast lets users easily communicate with nearby LE audio-supported devices via AuraCast. Now users can also broadcast their voices through their Galaxy phones’ microphones, which is useful for group activities such as tours and events.  

Storage Share connects the Galaxy ecosystem by letting users view files from other Galaxy devices, such as tablets or PCs, right in the My Files app. It also lets users access their phone’s files from other Samsung devices, including their TV.  

How Is My Galaxy Device Staying Protected 

One UI 8.5 enhances device security and makes security settings easier to manage. Thief protection helps keep phones and data safe. If a device is lost or stolen, the failed authentication lock will lock the screen after too many failed attempts to unlock it with a fingerprint, PIN, or password. The identity check now protects more settings, adding extra security.  

Availability 

The One UI 8.5 beta program will first be available for Galaxy S25 series users in select markets, including Germany, India, Korea, Poland, the UK, and the US. Starting December 8, Galaxy users can sign up for the beta through the Samsung Members app.  

• Use the Generative Edit feature in Photo Assist. You need a network connection and a Samsung account. When you edit with Generative Edit, your photo may be resized. A visible watermark will appear on the saved image to indicate that the AI created it. The screen image shown is for illustration only. The actual user experience and interface may be different.  

• This feature is available on devices running One UI 2.1 or later with Android Q or newer. Quick Share needs both Bluetooth Low Energy and Wi-Fi to work. The actual speed can change based on your device, network, and environment. The screen image is for illustration only. The real user experience and interface may look different.  

• This feature is only available on Galaxy S25 series devices, which include the Galaxy S25, S25 Plus, and S25 Ultra.   

• Each device must be signed in to the same Samsung account and must have both WiFi and Bluetooth turned on. Requires updated Galaxy phones and tablets with One UI 7 or higher, kernel version 5.15 or higher, and Galaxy Book 2 or later (Intel and Galaxy Book 4 or later) (Arm) and Samson Smart TV models, including U8000 and above, released after 2025. Feature availability may vary by region and device model. Screen image simulated for illustrative purposes; actual UX/UI may vary. 

Source: Samsung Launches One UI 8.5 Beta for Next-Level Ease of Use 

We are pleased to share that our Surface Co-Pilot Plus PC lineup for business is growing. The new 13.8-inch Surface Laptop 5G with Intel Core Ultra (Series 2) processors will start shipping on August 26th. You can get the new 13-inch Surface Laptop and 12-inch Surface Pro starting today.  

AI gives organizations a real advantage, but only if it’s available when needed. The Surface Laptop 5G delivers this with a neural processing unit (NPU) that handles over 40 trillion operations per second, enabling everyday tasks to run faster and easier. Whether you need to stay focused in meetings, find information quickly, or cut down on routine work, AI helps you get more done. With built-in 5G, you can stay connected to Microsoft 365, Co-Pilot, and other cloud tools for better insights and real-time teamwork.  

Many business customers have asked for 5G in the Surface Laptop. This request concerned more than just adding a modem. It showed a real need for instant, secure, and reliable connections, without worrying about signal strength or finding a hotspot.  

This need inspired the design of the Surface Laptop 5G. Our goal was to create the best 5G-connected laptop, where being connected is effortless. Whether you are a consultant or a team’s call on a train, a field engineer, uploading site data, or a sales leader finishing a proposal in a hotel lobby, Surface Laptop 5G helps you keep working wherever you are.  

Surface Laptop shows how Microsoft brings together hardware, software, and cloud services to create smart, secure, and connected tools for today’s mobile workforce. The Surface for Business line-up has solutions for every need, from flexible tablets to powerful laptops, all backed by Microsoft’s management tools and top security.  

Engineered For Seamless 5G Performance 

Adding 5G to the Surface Laptop took more than just adding a modem. We redesigned every part of the Surface Laptop 5G to ensure it’s seamless, reliable, and secure while maintaining the design, performance, and portability you expect.  

Dynamic Antenna System 

At the heart of Surface Laptop 5G is a dynamic antenna system that constantly adapts to its environment. With six strategically placed antennas, the device automatically adjusts signal paths and power based on how it’s being held or used, ensuring strong, reliable connectivity exactly when and where it’s needed. As users move between environments, the device smoothly transitions between 5G and Wi-Fi networks, maintaining a steady, secure connection to cloud-based apps, updates, and corporate resources. This novel antenna design also enables Surface Laptop 5G to act as a mobile hotspot, securely sharing its 5G connection with other devices when Wi-Fi isn’t available.  

Carefully Designed Hardware 

Most laptops put the antenna near the base, where signals can be blocked by objects on your legs. The Surface Laptop 5G is different. Its antennas are placed higher up to reduce interference and keep your connection strong and steady.  

To make this design work, we needed a new material that lets radio signals pass through while remaining durable, high-quality, and light. We created a custom, multi-layered laminate that delivers all this, so you get reliable 5G connectivity without sacrificing portability or style.  

Surface Laptop 5G also includes both Nano SIM and eSIM options integrated to preserve its slim profile while enabling worldwide connectivity. Weighing under 3 lb, it is light and easy to carry across campuses, through airports, or from meeting to meeting.  

Tested For The Real World 

In Surface, we don’t just emulate real-world use; we build for it. The Surface Laptop 5G was tested in homes, apartments, and active work environments to replicate typical scenarios, including:  

• moving between rooms  

• switching networks  

• multitasking  

• working from laptops  

These helped us fine-tune antenna placement, thermal performance, and connectivity behavior to reflect how people actually work.  

To ensure it works everywhere, we tested the 5G hardware with over 100 mobile operators across more than 50 countries. This means you get reliable 5G connectivity wherever your team goes.  

Secure and Connected for Smarter Management 

With built-in 5G, Surface laptop devices are persistently connected, so IT can send security updates and force policies, and get instant insights from almost anywhere. This is possible because Surface works closely with Windows and InTune, bringing together hardware, software, and cloud management into a single Microsoft solution. Surface devices paired with Windows AutoPilot enable a true zero-touch deployment experience where devices arrive carefully configured, secured, and ready to use.  

The Surface Management Portal within the Intune Admin Center provides IT with a clear view of device health, compliance, and usage across all Surface devices, with Security Co-Pilot now included. IT can use AI tools to spot issues, assess risks, and respond more confidently. An actor helps safeguard on-screen information and can reduce the risk of screen exposure when working in public spaces.  

Surface brings together Microsoft’s hardware, software, and cloud to give you a solution that’s easy to manage, secure to deploy, and ready for AI from the start.  

A Linked Future, Built for Business 

Surface protects your data and privacy while helping your employees get more done.  

Surface Laptop 5G is now part of our expanding Co-Pilot + PC lineup, built for the changing needs of today’s workforce. With the 12-inch Surface Pro for business and 13-inch Surface Laptop for business now available and Surface Laptop 5G coming on August 26, organizations will have more options than ever to operate with powerful, secure, and AI-ready devices.  

When paired with Verizon’s secure, reliable 5G network, Surface devices unlock even greater productivity. The combination of Surface Co-Pilot, plus PCs, Microsoft 365 Co-Pilot, and high-speed mobile connectivity enables an effortless experience that helps businesses to work more easily and efficiently in the office or out in the field. In the U.S., Surface for Business devices are available through a broad network of partners, including Verizon Business, with selected Verizon stores rolling out in the coming months.  

Support for Windows 10 PCs ends on October 14, 2025. Now is the time for a modern Windows experience built for the air, secure by design, and ready for mobile work. Surface.com/business to find an authorized dealer or visit the Microsoft Store. When you shop at microsoft.com, you’ll get free shipping and an extended 60-day price protection and return menu. For a deeper technical dive, see the Surface Pro blog.

Source: Introducing Surface Laptop 5G: Seamless connectivity, built for business 

As of early 2026, Google Vio 3 (including 3.1) and OpenAI Sora 2 are leading the way in AI video generation. Both combine high-quality audio with video visuals. Vio 3 stands out for its sharp resolution and professional results, while Sora 2 is known for smooth, longer, story-focused clips.  

To summarize, VO3 is best for 4K professional cinematic and high-resolution marketing videos. Sora 2 works better for longer story-driven and consistent social content.  

Official Benchmarks: Google Vio 3 vs OpenAI Sora 2 

Feature	Google Vio 3/3.1 (2025/2026)	OpenAI Sora 2 (2025/2026)
Max Native Resolution	4K Open (2160p) at 60 fps via H.265/HEVC	2080p (native)
Max Duration	~8 to 10 seconds (native)	25+ seconds (up to 60s in testing)
Native Audio	Yes: dialog + SFX + music	Yes: synchronized dialog plus SFX
Frame rate	24-60 FPS	24 to 30 FPS
Aspect Ratios	16:9, 9:16, 1:1.	16:9, 9:16, 1:1
Strengths	4K Quality Color SCI Fast Mode	Longer clips, consistency, physics
Availability	Gemini app Vertex AI Flow	IOS app (invite) Sora.com API

Official Resolution and Visual Benchmarks 

• Google V03 offers native (4K capability): Veo 3 offers native (3840×2160) output, which is ideal for broadcast and high-end advertising.  

• OpenAI Sora 2 is designed to produce consistent photo-realistic video at 1080p (Full HD) with better character steadiness across shots.  

• Emirates V03 supports up to 60 fps (H265/AV1), permitting smoother motion than typical 21/30 fps models.  

Native Audio Benchmarks 

Models include synchronized multi-modal audio.  

• VO3 (Audio Accuracy): VO3 Sonidos, Effectos Sonoros y Sonidos De fondo. It excels at lip syncing for dialogue-heavy scenes.  

• Sora 2 (Audio physics): integrates sound that fits the scene’s physical dynamics, such as footsteps, and provides dialogue.  

Key Differences in Performance 

• Video length: Sora 2 creates clips often 20-25+ seconds long, whereas VR 3 is optimized for 8-second high-fidelity shots.  

• Creative Control and Editing: Sora 2 includes an editing suite for altering scenes, while Veo 3 via Google Flow focuses on video ingredients and high-quality generation.  

• Cameos vs Flow: Sora 2 introduces Cameos, which allow users to insert their likeness and voice into scenes. Vio 3 integrates with Google’s ecosystem: (YouTube Shorts/Gemini API).  

OpenAI just announced its latest AI video generation model, Sora 2. The model competes with Google’s updated Vio 3, which also promises realistic AI-generated videos. OpenAI describes Sora 2 as a major step, calling it the ChatGPT-5 movement. Google, in turn, calls Vio 3 its most advanced video language model.  

The competition in Generative Video Technology has advanced past silent clips and simple animations. OpenAI’s Sora 2 and Google’s Vio 3 each take a different approach, modulating how creators/developers and platforms apply Video AI. Both models combine video control features and serve both professionals and creators, but they vary in their strengths, focus, and availability.  

Core Focus and Positioning 

Sora 2 is built as a general-purpose video and audio model focusing on realism, accurate physics, and smooth storytelling. OpenAI presents it as a creative partner for making longer, storyboarded videos with features like multi-shot control and persistent scenes. One highlight is cameos, which let users add their own likeness and voice to scenes. Veo 3, on the other hand, is more platform-focused. Google features built-in audio and video creation, fast production, and easy sharing via YouTube shots and the Gemini API. Make it great for creators who need quick results.  

Audio Integration 

Models move beyond silent video, but they focus on different things.  

• Sora 2 adds synchronized dialog sound effects and full audio environments that match the action in each scene.  

• Veo 3 includes audio as a core part of its design, generating speech, music, and effects together.  

With Veo 3, fast creators can make shots with audio in a single step. Sora 2’s main audio strength is its strong correspondence with the visuals.  

Visual Detail and Control 

Visually, Sora 2 focuses on realism and believable motion, such as gymnastic moves and buoyancy effects that demonstrate its physics handling. Its multi-shot editing and control features help creators build smooth stories. Veo 3, in contrast, emphasizes cinematic quality, efficient workflows, and options for both 1080p and some 4K video. Veo 3 Fast is built for speed, while the main Veo 3 tier supports longer, higher-quality videos.  

Ecosystem and Integration 

Sora 2 is launching slowly through an invite-only iOS app in North America, with access on Sora.com and an API coming soon. OpenAI has mentioned a Sora 2 Pro tier for ChatGPT Pro users, which could serve both creative users and developers. Veo 3 is already part of Google’s ecosystem, offering developers access to the Gemini API and direct YouTube integration for creators. This makes Veo 3 easier to use widely, especially for social media production.  

Both companies focus on safety and on tracking the origin of content.  

• Sora 2 has a system card to address risks such as misuse of personal likeness and adds controls for tracking content in its app.  

• Veo 3 uses SynthID watermarking and YouTube’s detection tools to stop unauthorized AI content.  

Which Is The Right One For You 

If you want the realistic physics, multi-short storytelling, and cameo features, Sora 2 is the better option, though it is still hard to access. If you need speed, built-in audio, and easy sharing, especially on YouTube and through the Gemini API, Veo 3 is the most sensible choice right now.

Source: OpenAI Sora 2 vs Google Veo 3: It is more about realism and storytelling versus speed and audio integration 

Intel Panther Lake (Core Ultra Series 3) delivers a big jump in AI performance over Lunar Lake (Series 2), reaching up to 180 total platform TOPS vs 120 TOPS. It includes a 5th-generation NPU (50+ TOPS) with improved FP8 support and XE3 graphics, enabling faster, more local, and more energy-efficient generative AI tasks.  

Key AI and Platform Comparison 

• Total platform TOPS: Panther Lake offers up to 180, while Lunar Lake provides 120  

• NPU performance: Panther Lake’s NPU 5 delivers 50 TOPS, about 4% more than Lunar Lake’s NPU 4 (48 TOPS). It also achieves over 40% higher TOPS per unit area and better efficiency.  

• Data type support: Panther Lake NPU now supports FP8 natively, enabling larger, more efficient AI models.  

• Graphics AI GPU: Panther Lake uses the Xe3 (Celestial) architecture, which provides a significant boost to AI inference via XMX cores and delivers 77% faster gaming and graphics performance than Lunar Lake.  

• Model Size: Panther Lake can run large language models with 30-70 billion parameters on a device, while Lunar Lake is aimed at models with 7-8 billion parameters.  

• Architecture Panther Lake uses Intel’s 18A process technology, while Lunar Lake is built on TSMC nodes.  

Panther Lake’s fifth-generation MPU is built for higher performance in a smaller chip area. This means better AI-powered multitasking and more advanced private on-device AI features.  

With the arrival of Intel Core Ultra Series 3 processors codenamed Panther Lake, Intel has signaled a decisive step forward from the previous Series 2 generation codenamed Lunar Lake. This new platform isn’t just faster; it’s fundamentally more intelligent, built to support high-performance Co-Pilot plus PCs with on-device AI.  

Paired with Asus’ latest premium designs and software, the Panther Lake generation of Intel’s processors showcases how next-generation silicon can unlock lightweight laptops that are more capable, more efficient, and more adaptive for real-world use.  

Lunar Lake vs Panther Lake: Clearing up the Generations 

To avoid confusion, it is worth stating this clearly upfront:  

• Intel Core Intel Series 2 processors are known as Lunar Lake or Arrow Lake.  

• Intel Core Ultra Series 3 processors are known as the Panther Lake series.  

Lunar Lake (Series 2 processors) marked Intel’s first major push into AI-native laptop computing. Panther Lake (Series 3 processors) builds on that foundation, scaling AI performance, graphics capability, and platform intelligence to better meet the demands of modern AI workflows.  

From AI Ready to AI First Computing 

One of the most meaningful generational shifts between Lunar Lake and Panther Lake lies in AI computing throughput. While past generations introduced the idea of distributing AI workloads across the CPU, GPU, and NPU, Panther Lake dramatically expands the scale of what’s possible on-device.  

Delivering up to 180 platform TOPS, Panther Lake processors offer a substantial increase in power over Lunar Lake’s 120 TPOS. This jump enables faster local inference, smoother AI-assisted multitasking, and more responsive real-time features, all without relying on the cloud. For users, this means AI-powered photo enhancements, background effects, transcription, and generative tools feel instantaneous and private in seconds, even on a lightweight laptop.  

Smarter Cores, Better Efficiency for Mobile Work 

Panther Lake refines Intel’s Hybrid Architecture with updated Performance Cores (P-Cores), Efficient Cores (E-Cores), and low-power efficient cores (LP-E cores), all working together more intelligently than before, compared to Lunar Lake’s more limited core configurations. Intel Core Ultra Series 3 processors scale up to 16 total cores, allowing demanding applications and AI workloads to co-exist without compromising battery life.  

The result is a system that feels consistently fast throughout the day. Heavy creative tasks can surge when needed, while AI processes quietly run on low-power cores in the background. For professionals who expect desktop-class responsiveness from a thin-and-light laptop, this balance is crucial.  

NPU 5: Where AI Becomes Practical 

The center of Panther Lake’s AI leap is the new NPI/NPU5 architecture. This dedicated neural processing unit is designed specifically for sustained low-power AI workloads, something Lunar Lake introduced, but Panther Lake takes to a new level.  

Instead of pushing AI tasks directly onto the CPU or GPU, it will select which are better suited for the NPU and let the NPU handle them efficiently and continuously. This is what enables always-on AI features in Co-Pilot Plus PCs, from real-time collaboration enhancements to intelligent system optimization, without draining the battery or increasing fan noise. It’s a subtle change that dramatically improves day-to-day usability.  

Graphics Performance for Modern Creatives 

Panther Lake’s Xe 3 GPU architecture brings a clear boost in graphics performance. Lunar Lake set a high bar for integrated graphics, but Xe 3 goes even further with more Xe cores, better ray tracing, and improved AI upscaling.  

If you edit high-resolution video or use several external displays, Panther Lake offers smoother visuals and faster video processing. What’s impressive is that these improvements don’t come at the cost of the slim, portable designs Intel laptops are known for.  

Platform Intelligence Beyond Raw Performance 

Panther Lake processors update the whole laptop experience with faster connectivity, smarter memory support, and next-generation I/O. This helps your system keep up with changing workflows.  

With Intel Wi-Fi 7, Dual Bluetooth Core 6.0, and Thunderbolt 5, you get faster data transfers, lower device latency, and more flexible workstation setups. Panther Lake laptops feel more responsive and ready for the future than Lunar Lake systems.  

Asus AI PCs Powered By Panther Lake 

Asus uses Panther Lake processors to build laptops designed for the way people work and create today. The 2026 Asus Zen Duo is made for power users and creators. Its dual-screen design takes advantage of Panther Lake processors, which offer more cores, better graphics, and faster AI features. This makes multitasking, content creation, and AI tasks smoother than before.  

The Asus ZenBook S14 is all about easy mobility. This premium, lightweight Intel laptop delivers Panther Lake performance, an OLED screen, and a sleek design. It’s made for professionals who want built-in AI features, long battery life, and greater portability.  

Learn More. 

With Panther Lake processors, the 2026 Asus ZenBook Duo and ZenBook S14 offer faster workflows, smarter AI features, and top performance in compact designs. To find out more about these new laptops, click the button below.

Source: Intel® Panther Lake vs Lunar Lake: How Intel® Core™ Ultra Series 3 Processor Redefines the AI PC Era 

The Apple Vision Pro (M5) builds on the M2 model by boosting processing power, raising the refresh rate to 120 Hz, and improving efficiency. Instead of a new design, the M5 focuses on performance, offering up to 36% faster CPU and GPU speeds and better AI features. This leads to better visuals and a battery that lasts a bit longer.  

Hardware and Processing Changes: M5 vs M2 

• Chipset & Performance: The M5 chip has an 8-core CPU, while the M2 has 8 cores. This means the M5 is about 35% faster for single-core tasks and 36% faster for multi-core tasks in Geekbench 6 text tests. It also has more memory bandwidth (153 GB vs 100 GB) and a faster neural engine, which helps with AI tasks like quicker persona generation.  

• Visuals & Display: The OLED panels are unchanged, but the M5 now supports a 120 Hz refresh rate instead of 100 Hz. It can also show 10 more pixels in the center of your view, making visuals sharper. The M5 adds hardware-accelerated ray tracing and mesh shading, which improve graphics in games.  

• Battery & Power: The M5 comes with a 40W battery adapter, up from 30W on the M2. It also offers a bit more battery life, up to 3 hours of video playback, compared to 2.5 hours on the M2.  

• Design & Comfort, Cologne: Both headsets look the same, but the M5 usually includes a new, more comfortable dual neck band that helps spread the weight more evenly.  

• Software & ecosystem: Both devices use the same Vision OS, so the main user interface and app library are the same.  

Summary Table 

Feature	Vision Pro M2	Vision Pro M5
Processor	M2 (8-core CPU)	M5 (10-core CPU)
Refresh rate	Up to 100 Hz.	Up to 120 Hz.
Memory Bandwidth	100 GBs	153 GBs
Battery Life	~2.5 hours	~ 3 hours.
Power Adapter	30 W	40 W

Conclusion 

The M5 is focused on better performance and is a good choice for power users or developers; however, the M2 is still a solid option for most people. Some users say that changes like clearer text and faster app loading are noticeable but not dramatic.  

Apple is fully embracing its new M5 chip, adding it to all its main products, as well as updated MacBooks and iPads. Apple also revealed a new version of the Vision Pro. This is the first update to the Apple Mixed Reality Headset, which it calls a Spatial Computer.  

Since the first M2-powered Vision Pro launched last year, the main change has been the switch from the M2 chip to the more powerful M5. The headset’s design and features are mostly the same; however, Apple has made a few other improvements, so we will break down what has changed and what hasn’t.  

Processor: A Faster Chip 

This is the most significant upgrade. The new Vision Pro moves from the first M2 chip (found in the 2022 MacBook Air and iPad Pro) to the M5 chip (now in the latest MacBook Pro and iPad Pro). We haven’t tested the M5 yet, but we can now look at how performance improved between the M2 and M4 chips in the 2024 iPad Pro and 2025 MacBook Air.  

On Geekbench 6, the iPad Pro with the M2 chip scores 2,545 for single-core and 9,505 for multi-core. The M4 iPad Pro scored 3,679 for single-core and 14,647 for multi-core. That’s a big jump, and the M5 should be even faster. Of course, mixed reality headsets work differently than tablets and laptops, so it’s hard to know exactly how much faster the new Vision Pro will be. Still, the rawpower should be a noticeable upgrade.  

Both the M2 and M5 are paired with Apple’s R1 chip for spatial processing, so the actual motion-tracking and environment-scanning functions will likely remain unchanged. Individual apps should benefit from the faster CPU, and this may offer a better experience when using multiple steps, multiple apps simultaneously (especially those that primarily use 2D windows rather than spatial computing). For reference, Apple says third-party apps will run twice as fast on the new Vision Pro compared to the original model.  

Both headsets appear to be physically identical, at least in terms of the main hardware. They have smooth aluminum bodies and curved glass fronts, similar to those of the Apple Watch. Vision Pro came with a dual-loop band that supports the device across the top and back of the head, using narrow, stiff straps. A solo-knit band features a nice-of-healing wider fabric strap that runs only along the back of the head. Neither is ideal, and both make the headset feel very front-heavy. The dual-knit band is the best of both worlds, potentially better distributing the headset’s load and resolving one of the Vision Pro’s biggest design complaints.  

Display: A Faster Refresh Rate 

Won’t get a sharper or more colorful display on the new Vision Pro, as it uses the same 23 million-pixel 92% DCI-P3 macro OLED display as the original. You might move more smoothly, though, as Apple says the upgraded headset supports up to 120 Hz, up from the previous version’s 100 Hz. This seems entirely due to the M5’s power, not the display itself. More fluid and consistent movement can reduce the risk of motion sickness, which is beneficial.  

Battery: A Half Hour More 

The new Vision Pro can last even longer than the original, providing up to 2.5 hours of general use or 3 hours of video playback. It’s still not great, but that’s a good 30 minutes more than the first Vision Pro.  

What Remains the Same 

Both devices run Vision OS 26 and feature the same easy-to-use eye and hand-tracking controls. They offer the most advanced mixed reality interface so far. Storage choices are still 256 GB, 512 GB, or 1 TB. Each version comes with 18 GB RAM. It comes with 4x F/2.0 stereophonic 3D main cameras, 6 world-facing tracking cameras, and 4 eye-tracking cameras. Connectivity hasn’t changed either, with Wi-Fi 6 and Bluetooth 5.2. The price is still a steep US$3,499.  

I haven’t tried the new Vision Pro yet, but if you already own one, the upgrade will not be worth spending another $3,500 just a year after buying the first. Still, Vision Pro is the top mixed reality headset right now, and the 2025 model’s better chip is a nice improvement. I am excited to test it soon, so check back for my full review and clear buying advice.

Source: Apple M5 Vision Pro vs. M2 Vision Pro: Same Vision, More Power