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Clear out junk files and repair common Windows errorsFree Scan →Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →For local AI, sometimes—especially when fitting a large model into memory matters more than inference speed. For 3D work, it is not possible to make a general replacement claim from the available evidence. Ryzen AI Max+ 395 systems combine Radeon 8060S integrated graphics with a large shared memory pool, which can make workloads possible that exceed the dedicated VRAM of many graphics cards. But memory capacity is not the same as GPU performance, and AMD’s published examples do not establish how the 8060S compares with a desktop GPU in a particular 3D application.
What you get in a Ryzen AI Max+ 395 workstation
The Ryzen AI Max+ 395 is a 16-core, 32-thread processor with Radeon 8060S integrated graphics and 40 graphics cores. AMD lists support for up to 128GB of LPDDR5x-8000 memory, a 55W default TDP, and a configurable TDP range of 45W to 120W. These are processor specifications and limits; the finished computer’s memory configuration, power settings, and cooling depend on its maker. AMD’s Ryzen AI Max+ 395 specifications
The memory is shared by the CPU, GPU, and other system components. It is not 128GB of dedicated graphics memory automatically reserved for the Radeon 8060S. How much can be made available to graphics depends on the specific system and its firmware settings, and allocating more to the GPU leaves less for the operating system and applications.
AMD’s Ryzen AI Halo Developer Platform illustrates one compact configuration: 128GB of LPDDR5x-8000 memory, 256GB/s of memory bandwidth, and a listed 120W platform TDP. Those are Halo platform specifications, not guarantees for every Max+ 395 mini PC or workstation.
#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.
Can it replace a desktop GPU for local AI?
It can be a practical alternative when the key requirement is model or workflow capacity: the ability to fit a large working set in memory. That does not mean it will process the same workload as quickly as a desktop graphics card. The distinction matters: memory capacity determines what may fit; throughput determines how quickly it runs.
AMD has documented local AI workflows on the Max+ 395, including image generation on Windows and language-model inference on Ubuntu. The results below are AMD’s own measurements and examples, not independent benchmarks or guarantees for other computers, software versions, settings, or drivers.
| Documented workflow | Configuration and reported result | What the result establishes |
|---|---|---|
| Windows image generation | AMD’s guide uses a Max+ 395 system with 128GB unified memory and about 94GB GPU-accessible memory. Its stated software includes 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 reports SDXL at about 1.48 images per second and a 1024×1024 Flux.1-dev image in about 78 seconds; it says tested workflows had peak memory requirements of approximately 34–42GB. AMD’s Windows ROCm and ComfyUI guide | There is a documented, version-specific image-generation path and examples of workflows with substantial memory requirements. It does not predict results on a different system or establish desktop-GPU parity. |
| Ubuntu language-model inference | AMD’s guide covers ROCm 7.2.1 and Ollama 0.20.x on a 128GB Max+ 395 system. It describes configuring 64GB or more of GPU-accessible memory in BIOS. Its examples include Qwen 9B, 35B-A3B, and 122B-A10B; the 122B-class model is described as a 76GB load using CPU/GPU mixed loading, while smaller checkpoints can be fully GPU-offloaded. AMD’s Ubuntu inference guide | Large models can be run with this memory arrangement, but the largest example uses both CPU and GPU. Parameter count alone does not tell you how fast a model will run. |
These examples show why a Max+ system may be attractive for local AI: its shared memory can accommodate a larger model or image-generation working set than a card with a smaller VRAM pool. The trade-off is that a workload may be slower, especially if it spills into CPU memory or uses mixed CPU/GPU loading. Quantization, model architecture, context length, runtime, allocation, and memory bandwidth all affect the result.
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.
AMD also reports a 3.9× Stable Diffusion 3.5 image-generation advantage in a comparison with an Apple MacBook Pro 16-inch using an M4 Pro and 48GB of memory. The test system was an ASUS ROG Flow Z13 with a Max+ 395, Radeon 8060S, and 128GB of memory, running Windows 11 24H2. AMD further reports up to 2.6× faster token generation and 3.3× faster image generation in concurrent AI workloads, and says the Apple system relied on swap during that concurrent test. These are vendor-reported results from a comparison with that Apple laptop, not a comparison with a desktop graphics card. AMD’s Stable Diffusion 3.5 comparison
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1Scan for outdated or missing drivers - takes under a minute2Repair Windows errors before they cause bigger problems3Fix the driver behind crashes, sound loss and screen glitchesHow much graphics memory does it have?
There is no single answer for every Ryzen AI Max+ workstation. The processor supports systems with up to 128GB of LPDDR5x memory, but graphics-accessible memory is an allocation from shared system memory, not a fixed quantity of dedicated VRAM. The computer maker and BIOS settings determine the available allocation, and the OS and other applications still need memory.
AMD’s Windows image-generation guide reports about 94GB GPU-accessible on its particular 128GB test system. Its Ubuntu inference guide says GPU-accessible memory can be configured to 64GB or more. Those are configurations in separate AMD guides, not a universal setting or a promise that every system exposes the same amount.
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.
AMD’s January 2025 workstation whitepaper says that up to 96GB of a 128GB configuration can be dedicated to graphics on Ryzen AI Max PRO systems. That figure applies to the PRO-series positioning described in the whitepaper; it should not be treated as the default allocation in every consumer Ryzen AI Max+ machine. AMD describes unified memory as a physical pool shared by CPU, GPU, and NPU. AMD’s January 2025 workstation whitepaper
Can it run a 70B or 100B model locally?
AMD’s Ubuntu guide documents Qwen examples up to 122B-A10B on a 128GB Max+ 395 system, describing that largest model as a 76GB load using CPU/GPU mixed loading. This supports a qualified answer: a sufficiently configured system can run a model in that size class locally, but the example is not evidence that every 70B or 100B model will fit, run fully on the GPU, or deliver a particular response speed.
Whether a model fits depends on more than its parameter count. Quantization, the model’s architecture, context length, runtime overhead, GPU memory allocation, and memory retained for the operating system can change the working-set requirement. If a model is partly loaded on the CPU, it may run but behave differently from one fully offloaded to the GPU.
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 support ROCm?
AMD’s guides document ROCm 7.2.1 workflows for this class of system: ComfyUI with PyTorch on Windows and Ollama on Ubuntu. Treat those as tested software combinations, not a blanket promise that every ROCm application, release, plugin, or operating-system setup will work.
In AMD’s Windows guide, the listed setup uses Python 3.12 and PyTorch 2.9.1+rocm7.2.1; AMD notes that its Windows ROCm wheels are built for CPython 3.12. Changing Python, PyTorch, ROCm, the driver, or the application can affect compatibility. For another application, check its current support for the specific operating system, AMD driver, ROCm release, and GPU compute path before choosing the workstation.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Can it replace a desktop GPU for Blender, Unreal Engine, or CAD?
The available evidence does not settle that question for any particular 3D application or desktop graphics card. AMD positions Ryzen AI Max PRO processors for complex 3D projects and professional applications, but that is vendor positioning—not a neutral performance result for every Max+ system. The sources cited here do not provide matched Blender, Unreal Engine, CAD, or renderer benchmarks comparing a Max+ 395 computer with a named desktop GPU.
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.
So, do not infer that a large shared memory pool means equivalent render times or viewport responsiveness. A scene that fits in memory may still render more slowly, and an application may depend on a graphics or compute backend that has different support on the chosen AMD hardware.
What to compare before deciding
- Exact application and version: confirm compatibility with the operating system, AMD driver, and any required plugin or compute backend.
- Specific task: identify the renderer and path used—CPU, HIP, Vulkan, or another supported option—rather than comparing hardware by name alone.
- Project size: use a representative scene, model, or CAD assembly and check its memory use.
- Target performance: compare measured render time or interactive frame rate at the resolution and quality settings you actually use.
- Sustained operation: check the finished system’s power limits and cooling for long renders or extended inference sessions; processor TDP alone does not establish sustained performance.
- Whole-system trade-offs: account for the compact system’s memory and storage configuration, connectivity, upgrade options, and the value of being able to replace or upgrade a discrete desktop GPU independently.
Use a test project that reflects your real workload and compare complete systems under the same application version, settings, and output target. Without that matched result, a claim that the 8060S replaces a particular desktop card is speculation.
Which type of workload is the better fit?
Consider a Ryzen AI Max+ system when
- You want to run local AI workloads whose memory needs are the main obstacle, and a large shared-memory configuration is more useful to you than maximum GPU throughput.
- You value a compact workstation and can confirm that your chosen AI stack supports its specific OS, driver, ROCm, and application versions.
- You are willing to measure performance on your own models and settings rather than treating vendor results as a guarantee.
Consider a desktop with a discrete GPU when
- Your 3D application, renderer, or required plugin has specific discrete-GPU requirements or proven performance on a card you can identify.
- Your priority is a target render time or viewport frame rate that must be verified with benchmarks for your exact application and workload.
- You want the option to replace or upgrade the graphics card separately from the rest of the computer.
For either route, compare the cost of the complete system at the memory, storage, cooling, and performance level you need. Current retail pricing is not established by the specifications and tests cited here.
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