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A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11For local AI workloads limited by memory capacity, a Ryzen AI Max+ 395 system can be a practical alternative to a desktop with a discrete GPU. For 3D work, the evidence does not establish that it replaces any particular desktop graphics card. Its unified memory can make large models or working sets fit, but capacity is not the same as GPU speed—and a system advertised with 128GB of memory does not give all 128GB to graphics.
Why unified memory matters—and what it does not mean
The processor and the finished system
AMD lists the Ryzen AI Max+ 395 with 16 Zen 5 CPU cores, 32 threads, boost clocks up to 5.1GHz, integrated Radeon 8060S graphics with 40 graphics cores, and support for up to 128GB of LPDDR5x-8000 memory. The processor’s listed default TDP is 55W, with a configurable range of 45W to 120W. These are processor-level specifications: a finished computer’s memory configuration, power limits, cooling and performance depend on its maker and design. See AMD’s Ryzen AI Max+ 395 specifications.
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AMD’s Ryzen AI Halo Developer Platform illustrates one compact-system configuration: 128GB LPDDR5x-8000, listed memory bandwidth of 256GB/s, Radeon 8060S with 40 RDNA 3.5 compute units, and a 120W platform TDP. Those are Halo specifications, not guaranteed specifications for every Max+ 395 computer. AMD lists Linux and Windows 11 support for the platform on its Ryzen AI Halo Developer Platform page.
System memory is not dedicated VRAM
A discrete desktop GPU normally has its own graphics memory; the Max+ 395 instead uses unified physical memory shared by the CPU, GPU and NPU. The computer maker and firmware determine how much is exposed to graphics, while the operating system and applications also need memory. AMD’s Windows guide documents one 128GB system with about 94GB accessible to the GPU; its Ubuntu guide describes configurations exposing 64GB or more. Those are examples of configured systems, not a promise that every model has the same allocation. The guides are AMD’s Windows image-generation setup and AMD’s Ubuntu inference setup.
#1 Best Overall
- Built for Local AI Development: AMD Ryzen AI Halo is designed for local AI development and inference, featuring 128GB unified memory and support for up to 200B parameter models to build and run intensive AI workloads locally.
- 128GB Unified Memory: Features 128GB LPDDR5x unified memory at 8000 MT/s with 256 GB/s memory bandwidth, providing a shared memory pool across the CPU, GPU, and NPU to support larger AI models.
- AMD Ryzen AI Max+ 395 Processor: Features 16 cores, 32 threads, and Zen 5 architecture, paired with AMD Radeon 8060S integrated graphics featuring 40 RDNA 3.5 compute units and an AMD XDNA 2 NPU with up to 50 TOPS.
- Linux AI Developer Platform: Purpose-built for Linux-based AI development with full AMD ROCm software support and preloaded tools, models, and workflows optimized for local AI development.
- Compact, Connected Design: Includes a 2TB M.2 SSD, 10GbE LAN, Wi-Fi 7, Bluetooth 5.4, USB-C connectivity, and HDMI 2.1b.
AMD’s January 2025 workstation whitepaper says up to 96GB of a 128GB configuration can be dedicated to graphics on Ryzen AI Max PRO systems. That is a PRO-series statement, not a universal allocation for consumer Max+ machines. The same paper describes PRO processors as designed for complex 3D projects and local LLMs; this is AMD’s intended-use positioning, not an independent performance result. See the January 2025 AMD workstation whitepaper.
What AMD documents for local AI
Image generation on Windows
AMD’s Windows ROCm guide documents a Ryzen AI Max+ 395 system with 128GB unified memory and about 94GB GPU-accessible memory, running Windows 11 Pro 24H2, Adrenalin 32.0.31019 or newer, ROCm 7.2.1, Python 3.12 and PyTorch 2.9.1+rocm7.2.1. AMD notes that the Windows ROCm wheels used in the guide are built for CPython 3.12, so this workflow depends on matching software versions.
Rank #2
- Built for Local AI and Advanced Workflows – The BOSGAME M5 AI Mini PC is powered by AMD Ryzen AI Max+ 395 with 16 cores, 32 threads, up to 5.1GHz, 50 TOPS NPU performance and up to 126 TOPS total AI performance. It is designed for local AI inference, private AI assistants, coding, data analysis, virtualization, content creation and demanding multitasking while keeping sensitive data on the device.
- 128GB Unified Memory for Large Models and Creative Projects – M5 includes 128GB LPDDR5X-8000 unified memory, giving the CPU and Radeon 8060S graphics access to a large shared memory pool. This helps support memory-intensive AI workloads, large project files, multiple virtual machines, 3D work, video editing and complex professional applications without the capacity limits of typical 32GB or 64GB mini computers.
- Radeon 8060S Graphics for Creation, Rendering and Gaming – Integrated Radeon 8060S graphics with 40 RDNA 3.5 compute units delivers high-end visual performance without a separate graphics card. Use the M5 creator workstation for 4K video editing, 3D rendering, CAD, AI image workflows, high-resolution media and modern gaming, while maintaining a compact desktop footprint.
- 2TB PCIe 4.0 SSD and Flexible Expansion – A pre-installed 2TB NVMe PCIe 4.0 SSD provides fast access to models, datasets, media libraries and project files. A second M.2 2280 PCIe 4.0 slot allows additional storage expansion, while the SD 4.0 card reader supports efficient photo and video workflows for creators and production teams.
- Professional Connectivity and Four-Display Support – Dual USB4 ports, HDMI 2.1 and DisplayPort 1.4 support up to four displays and resolutions up to 8K@60Hz. WiFi 7, Bluetooth 5.4 and 2.5GbE deliver fast networking for cloud collaboration, NAS access and business deployment. Windows 11 Pro, performance-mode switching, Wake-on-LAN and auto power-on support flexible workstation use.
In that stated setup, AMD reports SDXL generation at about 1.48 images per second and a 1024×1024 Flux.1-dev image in about 78 seconds. The guide also describes workflows with peak memory requirements of approximately 34–42GB. These are AMD-reported results for the documented setup; they are not guaranteed for another manufacturer’s system, driver, settings or software release.
LLM inference on Ubuntu
AMD’s Ubuntu guide documents ROCm 7.2.1 with Ollama 0.20.x on a 128GB Max+ 395 system. It gives examples using Qwen 9B, 35B-A3B and 122B-A10B models. AMD describes the 122B-class example as a 76GB load using CPU/GPU mixed loading, while smaller checkpoints can be fully offloaded to the GPU. The guide says GPU-accessible memory can be set to 64GB or more in BIOS, leaving the rest for the operating system and applications.
Rank #3
- Unlock next-generation AI computing with AMD Ryzen AI Max+ 395 processor featuring 16 cores, 32 threads, up to 5.1GHz boost clock, and integrated Ryzen AI engine delivering up to 126 TOPS AI performance. EVO-X3 is designed for local AI models, content creation, development, and professional workloads.
- OCuLink External GPU Expansion – Upgrade Beyond a Mini PC: Take your graphics performance further with a dedicated OCuLink (PCIe 4.0 x4) interface. Connect an external GPU dock to add desktop-class graphics power for AAA gaming, AI acceleration, 3D rendering, video production, and advanced creative applications. EVO-X3 gives you the flexibility of a compact PC with workstation-level expansion capability.
- AI NPU with XDNA 2 ARCHITECTURE - Powered by 16 “Zen 5” CPU cores, 50+ peak AI TOPS XDNA 2 NPU and a truly massive integrated GPU driven by 40 AMD RDNA 3.5 CUs, the Ryzen AI MAX+ 395 is a transformative upgrade and delivers a significant performance boost over the competition. The Ryzen AI Max+ 395 excels in consumer AI workloads like the llama.cpp-powered application: LM Studio. Shaping up to be the must-have app for client LLM workloads, LM Studio allows users to locally run the latest language model without any technical knowledge required and unleash their creativity and productivity.
- AMD RADEON 8090S iGPU GAMING PC - The AMD Radeon RX 8060S offers all 40 CUs with up to 2.9 GHz graphics clock and uses the new RDNA 3.5 architecture. The powerful iGPU is positioned between an RTX 4060 and 4070 laptop GPU and therefore enables gaming in FHD at maximum details in most demanding games. The 8060S can also utilize the full 128GB pool, which is perfect for running LLMs such as Deepseek 70B Q8, which runs comfortably on this machine.
- EIGHT CHANNEL LPDDR5X - LPDDR5X is a new ground breaking memory small form factor installed on-board. With blazing speeds up to to 8000MT/s, it runs 1.5x faster than the DDR5 SODIMMs; 90% better performance over DDR5 SODIMMs in video conferencing and photo editing; 30% better performance in productivity apps; 12% better performance in digital content workloads.
This establishes that the documented system can load a very large model through a mixed CPU/GPU path; it does not establish a particular tokens-per-second rate or show that every model of a given parameter count will fit or run well. Quantization, architecture, context length, runtime, memory allocation and bandwidth all affect memory use and speed. The guide does not establish an equivalent result for every 70B or 100B model, so use the exact model, quantization and context you intend to run when estimating fit.
Keep vendor comparisons in context
AMD separately reported a 3.9× Stable Diffusion 3.5 image-generation advantage in its test of an ASUS ROG Flow Z13 with Max+ 395, Radeon 8060S and 128GB, compared with an Apple MacBook Pro 16-inch with M4 Pro and 48GB. For concurrent AI workloads, AMD reported up to 2.6× faster token generation and 3.3× faster image generation, noting that the Apple system used swap in that test. These are vendor-reported comparisons involving different systems and software optimizations—not independent results and not comparisons with a desktop graphics card. Details are in AMD’s 2025 technical article.
Rank #4
- 【High-Performance APU】The MS-S1 MAX features an AMD Ryzen AI Max+ 395 APU, integrating a Zen 5 architecture CPU (up to 5.1GHz, 16C/32T, 64M L3 Cache), an RDNA 3.5 GPU, and an NPU (50 TOPS). The total system output is 126 TOPS. It provides powerful parallel computing capabilities for demanding AI workflows. It is ideal for running local LLMs, multimodal models, and computationally intensive tasks
- 【128GB UMA Memory】Equipped with up to 128GB of LPDDR5x-8000MT/s unified memory, it enables the CPU and GPU to access a shared, high-bandwidth memory pool with extremely low latency. Ideal for large-scale AI inference, 3D workloads, and complex timelines in video editing. It eliminates traditional VRAM bottlenecks, ensuring smoother data transfer during high-intensity computations. The UMA design maximizes performance stability under high loads
- 【Flexible Expansion】The MS-S1 MAX features USB4 V2 (up to 80Gbps), dual 10GbE LAN, HDMI 2.1 (up to 8K60), a full-length PCIe x16 expansion slot, and dual M.2 slots supporting up to 16TB RAID 0/1. Wi-Fi 7 provides stronger signal coverage and a more stable wireless experience. The slide-out design facilitates upgrades and maintenance. It easily adapts to personal, studio, or rack-mount enterprise environments
- 【High-Efficiency Cooling System】Utilizing an aerospace-grade aluminum alloy chassis, copper base plate, six heat pipes, dual turbine fans, and advanced PCM thermal conductive material, it maintains stable cooling performance even under continuous load. This system supports 130W continuous power and 160W peak power operation, with a built-in 320W power supply. It boasts multiple global certifications including CCC, FCC, UL, CE, and UKCA, ensuring stable and reliable operation in various environments
- 【Cluster Design】Two MS-S1 MAX units can be configured as a dual-unit cluster to run a large 235B Q4 model locally, achieving an output speed of 10.87 tok/s. Supporting 2U rack deployment, multiple MS-S1 MAX units can be cascaded into a distributed cluster to create a high-efficiency AI computing center. A cluster of four MS-S1 MAX units successfully ran a DeepSeek-R1 671B Q4 large model. A reserved cluster power-on interface allows for unified start-up and shutdown
Does Radeon 8060S replace a desktop GPU for 3D?
Capacity may help; performance depends on the job
A large shared memory pool can help when a scene, project or collection of applications would otherwise exceed a discrete GPU’s dedicated memory. It does not establish comparable rendering throughput, viewport responsiveness or compatibility. Radeon 8060S is integrated graphics, not a removable desktop card, and the amount of system memory available to it varies by machine and configuration.
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The cited material does not provide an apples-to-apples test of a named Blender scene, Unreal Engine project, CAD model or GPU renderer against a specified desktop GPU. It therefore cannot support a claim that the 8060S matches or replaces a particular card across 3D work. A meaningful comparison needs the application and version, renderer or compute path, project size, resolution, memory use, target frame rate or render time, and the systems’ power and cooling conditions. Confirm that the application, driver and any required renderer, extensions or plugins support the AMD GPU path you plan to use.
Best Value
- 🚨[Industry Supply Alert: Strix Halo Scarcity] Driven by the global surge in AI development, the ultra-high-performance AMD Ryzen AI Max+ 395 (Strix Halo) silicon is in extremely limited supply. Secure your A9 Mega now to lock in this unprecedented 126 TOPS AI configuration before inventory shifts or pricing adjustments based on raw material costs.
- [3-Year Limited Warranty & Brand-Direct Support] GEEKOM A9 Mega combines an aluminum-alloy chassis, rigorous reliability testing and CE, FCC, CB and RoHS compliance for professional use. Backed by a 3-year limited warranty, it provides long-term coverage for home offices, creative studios and business workspaces.
- [Local AI Super PC: Run Up to 128B Models Offline] GEEKOM A9 Mega supports select 4-bit quantized models with up to 128 billion parameters using compatible drivers and inference software. Build private knowledge bases, generate images with local Stable Diffusion, and automate tasks on-device. After setup and model downloads, supported workflows can run offline without cloud API fees, reducing the need to upload sensitive data.
- [128GB Unified Memory & 2TB PCIe Gen4 SSD] 128GB LPDDR5X memory at 8000 MT/s provides room for large AI models, datasets and multitasking. With supported settings, up to 96GB of this shared memory can be allocated to the Radeon 8060S GPU. The 2TB PCIe Gen4 NVMe SSD stores models, creative projects and high-resolution media, while dual M.2 slots support up to 8TB total storage (4TB per slot).
- [IceBlast 5.0: Keep Your AI Work Moving] From overnight AI tasks to deadline-driven renders, GEEKOM A9 Mega is built for demanding creative sessions. Its IceBlast 5.0 cooling combines a full-coverage vapor chamber and dual turbo fans to support up to 120W sustained power, with specified maximum power dissipation of 140W. Smart fan control balances cooling and noise, helping you stay focused on your next model, next frame and next deadline.
How to decide between a Max+ system and a desktop GPU
Compare the complete systems against the work you actually do. Keep these questions separate rather than treating a larger memory number as proof of faster performance:
- Will the workload fit? Check total memory, the firmware’s graphics allocation, memory left for the OS and other applications, and whether the AI runtime fully offloads the model or shares work with the CPU.
- How fast does it run? Look for measured tokens per second, images per second, render time or viewport frame rate in your exact workload. Do not infer speed from memory capacity or core counts alone.
- Does your software path work? Verify the operating system, driver and ROCm versions, application release, renderer backend and plugin support for the specific configuration.
- Can it sustain the load? Check the finished system’s power limits, cooling and noise, and whether performance holds during long inference sessions or renders.
- Does the form factor suit you? Consider compactness, storage and connectivity alongside upgradeability: a desktop discrete GPU can be replaced independently, whereas integrated 8060S graphics are part of the processor.
- What is the full-system cost? Compare the actual memory and storage configuration and account for any desktop GPU, power supply and cooling costs. No current retail prices are established here.
If possible, test the exact AI model or 3D project on the specific system before relying on it for production. For AI, record whether the workload fits, whether it spills to CPU and its sustained generation rate. For 3D, use the renderer and settings you expect to ship with, and measure both render time and interactive viewport performance.
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