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  • AMD Ryzen AI Halo (PRO 495): Specs, Price, Release Date & Everything We Know

    AMD Ryzen AI Halo (PRO 495): Specs, Price, Release Date & Everything We Know

    AMD has unveiled the next version of its Ryzen AI Halo Developer Platform, a compact desktop built for running serious AI workloads locally. Powered by the new Ryzen AI Max+ PRO 495 processor and packing up to 192GB of unified memory, it is designed to run 300-billion-parameter language models entirely on your desk — no cloud required. Here is everything we know.

    What Is the Ryzen AI Halo Developer Platform?

    The Ryzen AI Halo is not a traditional desktop PC. It is a compact developer workstation — roughly the size of a small mini-PC — purpose-built for building, testing, and running AI models locally. The first version arrived earlier this year with the Ryzen AI Max+ 395 chip, 128GB of memory, and a $3,999 price tag, rated for models up to 200 billion parameters.

    The new version takes a big step up: the Ryzen AI Max+ PRO 495 chip, up to 192GB of LPDDR5x unified memory, and support for 300-billion-parameter models and larger at 4-bit quantization. It is aimed squarely at AI developers, researchers, and creators who want datacenter-class local AI without renting cloud GPUs.

    Ryzen AI Max+ PRO 495: Full Specifications

    The heart of the platform is the Ryzen AI Max+ PRO 495, which combines three processors on a single chip sharing one memory pool:

    • CPU: Up to 16 Zen 5 cores (32 threads), boosting up to 5.2GHz from a 3.1GHz base
    • GPU: 40 AMD RDNA 3.5 compute units (Radeon 8065S integrated graphics)
    • NPU: XDNA 2 neural processor rated up to 55 TOPS
    • Memory: Up to 192GB LPDDR5x unified memory (up to 160GB allocatable as VRAM)
    • Storage: 2TB SSD
    • Wireless: Wi-Fi 7, Bluetooth 5.4
    • FP16 AI compute: Up to 61 TFLOPS

    AMD notes that the 55 TOPS NPU figure is a peak rating under optimal conditions, and real-world throughput varies with system configuration, model, and software version.

    192GB of Unified Memory: Why It Matters for Local AI

    The headline feature is the memory. In a normal PC, system RAM and graphics memory are separate pools, and large AI models have to squeeze into whichever is smaller. The Ryzen AI Max+ PRO 495 puts the CPU, GPU, and NPU on a single high-bandwidth memory pool — up to 192GB of it, with as much as 160GB assignable to the GPU as VRAM.

    That changes what fits on a desk. AMD says the platform can hold 300-billion-parameter language models at 4-bit quantization entirely in memory, alongside datasets, applications, and working context. Developers can also run multiple large AI agents concurrently, each with its own KV cache — something that simply does not fit on systems with smaller GPU memory.

    Built for AI Agents, Not Just Chatbots

    AMD is positioning the platform around the shift from chatbots to AI agents — software that reads files, calls tools, coordinates parallel processes, and produces finished deliverables like decks, memos, and charts. In that setup, each part of the chip has a job: the CPU orchestrates the agent’s tools and processes, the GPU and NPU accelerate model inference and content generation, and the unified memory keeps models and working data loaded for all three.

    AMD argues that raw tokens-per-second still matters, but for agent workloads, orchestration, memory capacity, and end-to-end task completion matter just as much.

    Generative AI Performance: AMD’s Claims vs Intel and Apple

    AMD tested the PRO 495 on native x86 Windows with ROCm software across 18 image, video, music, and 3D generation workloads — including FLUX.2, Qwen Image, Ideogram V4, and Stable Music — and published comparisons against two rivals:

    • Vs Intel Core Ultra X9 388H: Higher relative throughput across all 18 workloads, with a top result of 32.2x.
    • Vs Apple M5 Pro: Higher throughput across the workloads, with a top result of 34.3x. AMD notes several workloads did not run on the Apple system at all.

    Two caveats worth knowing: these are AMD’s own tests from September 2026, not independent reviews, and the comparison systems carried 64GB of memory against the Halo’s 192GB — a gap that decides which workloads can even run on each machine.

    Software: Ryzen AI Developer Center and AI Playbooks

    Hardware is only half the story. AMD bundles a software layer meant to take developers from first boot to a running model with minimal setup:

    • Ryzen AI Developer Center: A single app for software, platform controls, features, and updates, with remote access and software sync.
    • Preloaded apps and models: Installed out of the box so testing can start immediately.
    • AI Playbooks: Guided paths through supported AI workflows.
    • Best-Known Configuration: AMD validates ROCm software, drivers, frameworks, applications, and models together as one set, restorable through the Developer Center.

    Windows-based versions will ship with Microsoft’s Windows Project Zenith, a ready-to-code Windows experience with VS Code, WSL, GitHub Copilot CLI, and PowerShell preinstalled.

    Price and Availability

    The Ryzen AI Halo Developer Platform with the Ryzen AI Max+ PRO 495 is available to order now from Micro Center in the US at $7,299.99 — $3,300 more than the first-generation 128GB model. Note that Micro Center lists it as in-store pickup only, with no shipping. Windows Project Zenith versions are coming soon. AMD has not announced pricing for other regions.

    Ryzen AI Halo vs NVIDIA RTX Spark: The Local AI PC Race

    The timing is no coincidence. NVIDIA just opened pre-orders for its RTX Spark AI PCs — laptops and compact desktops with up to 128GB of unified memory starting at $2,599. AMD’s answer is a more expensive, more memory-heavy developer box: 192GB vs 128GB, $7,299 vs $2,599.

    The two target different buyers. RTX Spark is a consumer-and-creator platform that also plays AAA games; the Ryzen AI Halo is a developer-first machine for people whose models genuinely need 160GB of VRAM. But together they mark the same turning point: 2026 is the year serious AI moved from the cloud to the desk.

    Should You Buy It?

    The Ryzen AI Halo makes sense for a narrow audience: AI developers and researchers running very large local models or multi-agent workflows who would otherwise pay for cloud GPU time. For everyone else — including most creators — the $7,299 price and developer focus make it a tough sell against cheaper local-AI options.

    Still, as a statement of where the industry is going, it matters. Unified memory architectures are rapidly becoming the default for local AI, and AMD just raised the bar for how much of it you can get in a box that sits quietly on a desk.

  • NVIDIA RTX Spark AI PCs: Specs, Price, Release Date & Everything We Know

    NVIDIA RTX Spark AI PCs: Specs, Price, Release Date & Everything We Know

    NVIDIA and Microsoft have officially kicked off a new era of AI computing. Their joint platform, NVIDIA RTX Spark, puts datacenter-class AI power into laptops and compact desktops — and the first machines hit store shelves on October 16, 2026. Preorders opened October 7, with six PC makers shipping RTX Spark hardware at launch, a scale no AI-focused chip launch has reached before.

    But what exactly is RTX Spark, and should you care? Here’s everything we know so far.

    What Is NVIDIA RTX Spark?

    RTX Spark is a new chip platform co-developed by NVIDIA and Microsoft, built around one idea: running powerful AI models locally on your PC instead of sending every request to a cloud datacenter.

    NVIDIA calls it a two-part platform. RTX Spark itself is the hardware half — a CPU-plus-GPU “superchip.” Microsoft provides the software half, called Microsoft Execution Containers (MXC), which is baked into Windows 11 and manages how AI workloads run on the machine.

    The pitch is simple: chatbots, coding assistants, image generators, and autonomous AI agents running entirely on your laptop — no subscription, no latency, no data leaving your device.

    RTX Spark Specs: What’s Inside the Superchip

    The numbers NVIDIA has shared are serious:

    • GPU: Blackwell-generation RTX graphics with up to 6,144 CUDA cores
    • CPU: 20-core NVIDIA Grace processor based on the Arm architecture (a mix of Cortex-X925 and Cortex-A725 cores)
    • Interconnect: NVLink-C2C chip-to-chip link instead of a conventional PCIe connection
    • Memory: up to 128GB of unified memory shared between the CPU and GPU
    • AI acceleration: fifth-generation Tensor Cores with FP4 precision support
    • Claimed performance: up to 1 petaflop of AI compute

    The standout spec is the unified memory. In a normal PC, the CPU and GPU have separate memory pools, and large AI models get split awkwardly between them. RTX Spark’s shared 128GB pool means a big language model can sit in one place, accessible to both processors at full speed.

    Microsoft’s Half: Execution Containers

    Hardware is only half the story. Microsoft Execution Containers (MXC) is the software layer in Windows 11 that schedules and sandboxes AI workloads on RTX Spark machines.

    Think of it as the traffic controller: it decides which parts of an AI task run on the GPU’s Tensor Cores, which run on the CPU, and how memory gets allocated — all without the user thinking about it. For developers, it means AI apps can target one consistent platform instead of wrestling with drivers and frameworks per machine.

    Which RTX Spark PCs Can You Buy?

    Six PC makers are shipping RTX Spark systems at launch. The two with the most detail so far:

    Dell XPS 16 Creator Edition — Dell’s flagship creator laptop, rebuilt around a 20-core NVIDIA N1X processor (the top of the RTX Spark stack). It pairs the chip with a 3.2K OLED display running at 120Hz and a 99Wh battery. Preorders are open now at a starting price of $3,799.99, with shipments beginning October 16, 2026. Notably, this is the first Dell XPS ever built on NVIDIA silicon instead of Intel or AMD.

    HP RTX Spark AI PCs — HP unveiled its RTX Spark lineup alongside the ZGX Fury GB300 workstation, with Perplexity AI integration built in. Pricing and exact configurations are still rolling out.

    Expect the remaining makers to announce their models through the launch window.

    Battery Life: The Big Claim

    NVIDIA makes one more bold promise: RTX Spark laptops are designed to hold full AI and graphics performance while unplugged, with all-day battery life.

    If true, that fixes one of the oldest complaints about powerful laptops — that they throttle hard the moment you leave the charger. But it’s worth noting this claim has not yet been independently benchmarked by reviewers. Take it as a target, not a guarantee, until third-party tests land.

    Who Is RTX Spark Actually For?

    Let’s be honest: most people don’t need a petaflop on their lap. RTX Spark makes the most sense for:

    • Developers building and testing AI agents and apps locally
    • Creators running image and video generation models without cloud fees
    • Researchers and students working with large open models
    • Privacy-conscious users who want AI that never phones home

    If your heaviest workload is a browser with forty tabs, a conventional ultrabook remains the smarter buy — and far cheaper.

    RTX Spark Price and Release Date

    • Preorders opened: October 7, 2026
    • Retail availability: October 16, 2026
    • Dell XPS 16 Creator Edition: from $3,799.99
    • HP models: pricing to be confirmed
    • Form factors: laptops and compact desktops, all running Windows 11

    Should You Wait for RTX Spark?

    If you run AI workloads daily and you’re shopping for a new machine this fall, RTX Spark is worth a serious look — it’s the first platform genuinely designed around local AI rather than bolting an NPU onto a standard laptop. If you don’t, there’s no reason to pay the early-adopter premium; prices will only come down as more makers join in.

    Either way, October 16 is the date to watch. That’s when the first independent benchmarks should start appearing — and benchmarks, not launch slides, will tell us whether RTX Spark delivers on its petaflop promise.