Beelink GTR9 Pro vs GMKtec EVO-X2 vs Mac Mini M4 Pro: Which Mini PC Wins for AI?

Beelink gtr9 pro, gmktec evo-x2, and mac mini m4 pro compared.

Three mini PCs, three ecosystems, one question—which runs your AI models best? AMD’s Strix Halo and Ryzen AI Max+ 395 brought 128 GB to the mini PC; Apple Silicon has unified memory and silence. We compare them head-to-head so you can pick the right device for your model size, budget, and OS. For the full picture, including more options, see our best mini PC for AI buyer’s guide; for the same hardware doing VMs and hypervisors, check our best NUC for virtualization pillar.

Meet the Contenders

Beelink GTR9 Pro

The Beelink GTR9 Pro is built around AMD’s Ryzen AI Max+ 395 (Strix Halo)—a 16-core Zen 5 CPU paired with a 40-CU RDNA 3.5 integrated GPU and a 50 TOPS XDNA NPU. It supports up to 128 GB of LPDDR5X memory at roughly 200 GB/s bandwidth, which is enough to run 70B-parameter models with Q4 quantization entirely in RAM. Storage comes via two M.2 NVMe slots, and connectivity includes dual 10 Gigabit Ethernet ports, USB4, and HDMI. The TDP ranges from 65 W to 150 W depending on workload. It ships with Windows 11 but is fully Linux-compatible, making it a natural fit for Proxmox or Docker-based homelabs. Pricing lands around $2,000–$2,500 for the 128 GB configuration—the highest of the three, justified by that dual 10GbE networking and the maximum memory ceiling.

Beelink Mini PC, GTR9 Pro AMD Ryzen AI Max+ 395 CPU (126 Tops), 128GB RAM 2TB Crucial SSD, Mini Computer 10GbE Dual LAN/WiFi 7+BT5.4/8K Quad Display/USB4.0 * 2/SD Card Slot/DeepSeek 70B

• 【Powerful AMD Ryzen AI Max+ 395 CPU and AMD Radeon 8060S GPU Bring the Future to Your Fingertips】 — 16 Zen 5 CPU cores, combined with the advanced Radeon 8060S iGPU, next-gen XDNA 2 NPU, and 126 AI TOPS, deliver cutting-edge architecture that significantly boosts the GTR9 Pro's performance, ideal for editing, rendering, designing, live streaming and AAA gaming
• 【140W Ultra-Quiet Cooling: Dual-Turbine Fans + Unified Vapor Chamber】 — Engineered with dual turbine fans and a full-coverage vapor chamber, Beekink Mini PC achieves 140W TDP at just 32dB—massive performance, near silence
• 【Unmatched Memory & Storage】 — Beelink GTR9 Pro comes with 128GB LPDDR5X RAM and 2TB Cucial SSD (dual M.2 2280 PCIe 4.0 slots. supporting up to 8TB, speeds up to 7000MB/s). The GTR9 Pro delivers blazing speed for AI, gaming, and creative tasks
• 【AI Server Clustering】 — Equipped with dual 10GbE LAN ports and dual USB4 (40Gbps), the Ryzen AI Max+ 395 Mini PC can serve as an AI computing hub, supporting local deployment of massive models like DeepSeek 70B for secure, private AI applications
• 【Quad 8K Display Support】 — Beelink PC features HDMI 2.1, DisplayPort 2.1, and dual USB4 ports (40Gbps/8K@60Hz), supports up to four 8K displays, perfect for expansive workspaces and high-precision tasks

$3,399.00

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GMKtec EVO-X2

The GMKtec EVO-X2 shares the same AMD Ryzen AI Max+ 395 CPU and 40-CU RDNA 3.5 GPU as the Beelink, along with up to 128 GB LPDDR5X and 200 GB/s bandwidth. Where it diverges is price and expandability: the EVO-X2 typically runs $1,700–$2,000 for comparable configs, roughly $200–$500 less than the GTR9 Pro. It also includes an OCuLink port alongside its two M.2 NVMe slots and USB4. That OCuLink connection is a genuine differentiator—it lets you attach an external GPU enclosure with an NVIDIA RTX card for CUDA acceleration, a future-proofing option neither competitor offers in this form factor. The TDP sits at a typical 65 W, though sustained AI loads push higher. Full specs are on the GMKtec EVO-X2 product page.

GMKtec EVO-X2 AI Mini PC Ryzen Al Max+ 395 (up to 5.1GHz) Mini Gaming Computers, 128GB LPDDR5X 8000MHz (16GB*8) 2TB PCIe 4.0 SSD, Quad Screen 8K Display, WiFi 7 & USB4, SD Card Reader 4.0

• EVOLUTION RYZEN AI MAX+ 395 MINI PC - GMKtec EVO-X2 is the next evolution in AI mini PC Ryzen Strix Halo series. Thanks to AMD Simultaneous Multithreading (SMT) the core-count is effectively doubled, to 32 threads. Ryzen AI Max+ 395 has 64 MB of L3 cache and can boost up to 5.1 GHz, depending on the workload. The Ryzen AI Max+ 395 is currently rated as the "most powerful x86 APU" on the market for AI computing.
• 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.
• QUAD SCREEN 8K DISPLAY SUPPORT - EVO-X2 AI Mini PC support 4-screen 4K/8K output via HDMI 2.1 (8K@60Hz), DisplayPort 1.4 (4K@60Hz), and dual USB 4 40Gbps Transfer speed (supporting PD3.0/DP1.4/DATA). Ideal for gaming, video editing, and multitasking, it provides expansive and crisp multi-display support.

$3,299.99

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Mac mini M4 Pro

Apple’s Mac mini M4 Pro takes a fundamentally different approach. The M4 Pro packs a 12-core CPU and 14-core GPU with Metal acceleration into a package that sips 25–30 W under full AI load and idles at 5–15 W. Unified memory tops out at 64 GB with 273 GB/s bandwidth—higher per-GB throughput than either AMD machine. The trade-off is that 64 GB ceiling: you can comfortably run 32B-parameter models, but 70B requires a Mac Studio with 96+ GB. Thunderbolt 4 (x3), HDMI, and Gigabit Ethernet handle connectivity, with internal SSD options from 512 GB to 2 TB. Pricing ranges from $1,999 for the 48 GB model to $2,499 for 64 GB. The Mac mini is effectively silent under sustained AI workloads—a quality-of-life factor that’s hard to quantify until you’ve lived with a fan-cooled alternative on your desk. Configurations are on Apple’s Mac mini page; our Mac mini for AI guide goes deeper.

Apple 2024 Mac mini Desktop Computer with M4 chip with 10‑core CPU and 10‑core GPU: Built for Apple Intelligence, 16GB Unified Memory, 256GB SSD Storage, Gigabit Ethernet. Works with iPhone/iPad

• SIZE DOWN. POWER UP — The far mightier, way tinier Mac mini desktop computer is five by five inches of pure power. Built for Apple Intelligence.* Redesigned around Apple silicon to unleash the full speed and capabilities of the spectacular M4 chip. With ports at your convenience, on the front and back.
• LOOKS SMALL. LIVES LARGE — At just five by five inches, Mac mini is designed to fit perfectly next to a monitor and is easy to place just about anywhere.
• CONVENIENT CONNECTIONS — Get connected with Thunderbolt, HDMI, and Gigabit Ethernet ports on the back and, for the first time, front-facing USB-C ports and a headphone jack.
• SUPERCHARGED BY M4 — The powerful M4 chip delivers spectacular performance so everything feels snappy and fluid.
• BUILT FOR APPLE INTELLIGENCE — Apple Intelligence is the personal intelligence system that helps you write, express yourself, and get things done effortlessly. With groundbreaking privacy protections, it gives you peace of mind that no one else can access your data — not even Apple.*

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Spec-Sheet Comparison

The spec sheet reveals two fault lines. First, memory: the AMD machines double the Mac mini’s ceiling at 128 GB, which is the dividing line between running 70B models or not. Second, power and noise: the Mac mini draws a fraction of the wattage and runs silent, while both AMD machines produce audible fan noise under sustained AI inference. Everything else—CPU cores, GPU compute, storage speed—is close enough that the decision comes down to those two factors plus OS preference.

AI Inference Benchmarks

Methodology

All benchmarks use Ollama with Q4_K_M quantization, measuring generation tokens per second (tok/s) on a single prompt. The AMD machines run Linux; the Mac mini runs macOS with Metal acceleration. We focus on Q4_K_M because it offers the best balance of quality and speed for local inference—small enough to fit large models in RAM, accurate enough for productive use.

Results

Analysis

At 8B and 14B, the AMD machines pull ahead on raw tok/s thanks to their 40-CU RDNA 3.5 GPU doing much of the matrix math. At 32B, the gap narrows considerably—Apple’s 273 GB/s unified memory bandwidth compensates for the lower core count, and the Mac mini lands in the same 10–15 tok/s range as both AMD devices. The real separation happens at 70B: only the 128 GB AMD configs (Beelink or GMKtec) can load the model at all, delivering 5–8 tok/s that’s usable for single-turn queries and batch processing. The Mac mini simply can’t participate at that tier without upgrading to a Mac Studio. XDA’s hands-on with an overpowered mini PC running local LLMs confirms these patterns with independent tok/s numbers. Between the two AMD machines, performance is essentially identical—they share the same silicon and memory controller.

Power Consumption and Noise

Annual costs assume 24/7 operation at the US average of $0.12/kWh. The Mac mini’s efficiency advantage is striking: it costs roughly a quarter of what the Beelink draws annually and a third of the GMKtec. Over a three-year ownership period, that electricity delta adds up to $100–$225 in savings—not enough to change a buying decision on its own, but meaningful for always-on AI servers.

The GMKtec runs slightly cooler than the Beelink under sustained AI workloads thanks to its lower typical TDP, but both produce noticeable fan noise in the 30–40 dBA range during long inference runs. If your mini PC sits in a living room, home office, or bedroom, the Mac mini’s silence is a major quality-of-life advantage. The AMD machines are acceptable in a dedicated office or server closet, but you’ll hear them during sustained AI workloads.

OS and Software Compatibility

Windows/Linux (Beelink, GMKtec): Both AMD machines ship with Windows 11 and run Linux flawlessly—Ubuntu, Fedora, and Proxmox all work out of the box. This opens the full ecosystem: Docker with GPU passthrough, ROCm for AMD GPU acceleration, vLLM for production-grade model serving, and Proxmox for running VMs alongside AI workloads. macOS (Mac mini): Ollama, LM Studio, and MLX run natively with Metal acceleration. Setup is simpler—install Ollama and go—but there’s no Docker GPU passthrough, no ROCm or CUDA, and no hypervisor like Proxmox. For a step-by-step Ollama setup on a mini PC, we have a dedicated guide. For RAM and VRAM requirements across all platforms, see our memory guide.

Framework Compatibility

If you need Docker with GPU passthrough, vLLM for production serving, or Proxmox for running virtualization alongside AI, the AMD machines are the clear choice. If you want the simplest setup path with the best power efficiency—install Ollama, load a model, and start prompting—macOS wins handily.

Upgrade Path and Longevity

Beelink GTR9 Pro: RAM is soldered, so buy the 128 GB configuration upfront if you want 70B model capability—there’s no upgrading later. The two M.2 NVMe slots make storage expansion straightforward, and dual 10GbE ports make the GTR9 Pro excellent as a high-speed network node or NAS companion. There’s no official eGPU path, so what you get from the integrated RDNA 3.5 GPU is what you keep.

GMKtec EVO-X2: RAM is also soldered, and you get the same dual M.2 NVMe storage slots. The differentiator is the OCuLink port: connect an external GPU enclosure with an NVIDIA RTX card and you get CUDA acceleration for 70B+ models without replacing the entire machine. This is the biggest future-proofing advantage in the lineup. An RTX 4090 in an external enclosure gives you 24 GB of dedicated VRAM for CUDA-accelerated inference, dramatically speeding up models that fit in GPU memory while the system RAM handles overflow.

Mac mini M4 Pro: Everything is soldered—CPU, RAM, and storage. There’s no RAM upgrade, no internal storage expansion, and no eGPU path for ML acceleration (macOS dropped eGPU support and Ollama doesn’t use external GPUs). Thunderbolt external drives work for additional storage, but they won’t help with inference speed. Buy the 64 GB configuration and accept the ceiling, or step up to a Mac Studio if you need 96–192 GB. DevToys’ Beelink SER9 vs GEEKOM comparison and Hostbor’s ASUS NUC 14 Pro AI vs Beelink SER9 review cover build quality and expandability in adjacent models worth considering.

Price-to-Performance Verdict

At the 32B parameter level where all three compete head-to-head, they’re remarkably close on raw tok/s. The GMKtec wins on price-to-performance at roughly 6.7 tok/s per $1,000 spent, making it the best value per dollar. The Mac mini dominates on power efficiency at just 2.5 W per tok/s—less than a third of the Beelink’s draw—which compounds into real savings over years of 24/7 operation. The Beelink justifies its price premium with dual 10GbE networking and the highest RAM ceiling in the group, making it the strongest choice for homelab users who need high-speed network throughput alongside their AI workloads.

Which Should You Buy?

Best for 70B+ Models

Only the 128 GB AMD machines can load a 70B-parameter model with Q4 quantization—the Mac mini’s 64 GB ceiling puts it out of contention entirely. Between the two, pick the Beelink GTR9 Pro if you need dual 10GbE networking for serving models across your homelab or pushing large datasets between machines. Pick the GMKtec EVO-X2 if you want the lower entry price and the OCuLink option for adding a dedicated GPU later. Both deliver 5–8 tok/s on Llama 3.1 70B, which is usable for single-turn queries and batch processing.

Best for Silence and Power Efficiency

The Mac mini M4 Pro wins by a wide margin. At 25–30 W under full AI load and effectively zero audible noise, it’s the only device in this comparison you can run 24/7 in a bedroom or living room without noticing it. Annual electricity cost is $15–25, compared to $50–100 for the AMD machines. If your use case stays at or below 32B parameters, the Mac mini gives you competitive tok/s with none of the thermal or acoustic compromises.

Best Value for 30B Models

The GMKtec EVO-X2 in a 64 GB configuration ($1,200–$1,400) is the cheapest path to comfortable 30B inference. The Mac mini M4 Pro 64 GB ($1,999) costs more but adds silence, power efficiency, and the polished macOS Ollama experience. Both handle Qwen 2.5 32B at 10–15 tok/s. If budget is the deciding factor, GMKtec wins; if you value the daily experience of a silent, low-power machine, the Mac mini is worth the premium.

Best for Multi-Purpose (AI + VMs + Docker)

Beelink GTR9 Pro or GMKtec EVO-X2 running Linux. Install Proxmox, spin up VMs for development or testing, run Docker containers with GPU passthrough, and host Ollama on the same box. The Mac mini can’t run Proxmox, can’t do Docker GPU passthrough, and can’t serve as a hypervisor host. If your mini PC needs to wear multiple hats—AI inference plus virtualization plus containerized services—the AMD machines are the only realistic option.

FAQ

Can any of these run 235B models?

Only the AMD machines with 128 GB, using heavy quantization (Q2 or Q3), and at extremely slow speeds—roughly 1–2 tok/s. That’s not practical for interactive chat or any real-time use. For 235B models, you’re looking at multi-GPU desktop rigs or cloud instances.

Which is quietest?

The Mac mini M4 Pro, by a wide margin. It’s effectively inaudible under sustained AI load—under 20 dBA. Both AMD machines ramp their fans to 30–40 dBA during extended inference runs, which is noticeable in a quiet room.

Can I dual-boot Linux on the Mac mini?

Asahi Linux runs on Apple Silicon, but Ollama’s Metal acceleration only works on macOS. If you boot into Linux on a Mac mini, you lose the GPU acceleration that makes Apple Silicon competitive for inference. You’d be better off buying an AMD machine if Linux is a requirement.

Do these mini PCs support eGPU?

The GMKtec EVO-X2 has an OCuLink port that supports external GPU enclosures—connect an NVIDIA RTX card for CUDA acceleration. The Mac mini has Thunderbolt 4, but macOS no longer supports eGPU for ML workloads and Ollama won’t use an external GPU. The Beelink GTR9 Pro lacks a dedicated eGPU port, though USB4 can technically drive an enclosure at reduced bandwidth.

Is the price premium for 128 GB worth it?

Yes, if you plan to run 70B+ parameter models—there’s no other way to fit them in memory on a mini PC. No, if your largest model stays at 32B or below; a 64 GB configuration handles that comfortably and saves you $400–$800.

Can I use the same mini PC for virtualization and AI?

Yes. The AMD machines run Proxmox or other hypervisors natively—you can host VMs, run Docker containers, and serve Ollama on the same box. Our best NUC for virtualization pillar (linked in the intro) covers the virtualization angle in depth.

Which has the best warranty and support?

Apple offers a standard 1-year warranty with optional AppleCare+ (up to 3 years). Beelink and GMKtec provide 1–2 year limited warranties. Apple’s support infrastructure—Genius Bar, phone support, mail-in service—is generally more accessible and consistent than what either AMD brand offers.

Can I cluster two mini PCs for more AI power?

It’s technically possible using tools like exo or Ollama’s experimental mesh networking, which distribute model layers across multiple machines. In practice, the inter-node latency over Ethernet is significant enough that buying one larger machine (or upgrading to 128 GB) is simpler and delivers better tok/s than two clustered 64 GB nodes.

AMD ROCm vs Apple Metal — which has better LLM support?

Apple Metal is more polished for LLM inference—Ollama and llama.cpp “just work” with Metal acceleration on macOS. ROCm has broader framework support (PyTorch, vLLM, Docker GPU passthrough) but comes with more setup friction, driver compatibility issues, and occasional version mismatches. If you want plug-and-play inference, Metal wins; if you need the wider ML ecosystem, ROCm is more capable.

How often do these brands release new models?

Both AMD and Apple follow roughly annual silicon refresh cycles. AMD’s Strix Halo (Ryzen AI Max+ 395) and Apple’s M4 Pro are the latest as of early 2026; expect successors within 12 months. Beelink and GMKtec typically launch updated chassis within a few months of new AMD silicon availability.

Conclusion

There’s no single “best”—it depends on model size, OS, and budget. The AMD machines own the 70B tier and the multi-purpose server role; the Mac mini owns silence, efficiency, and ease of setup. Once you’ve chosen, set up Ollama on your mini PC with our Ollama setup tutorial. For more options across every price tier, see our best mini PC for AI guide.

Quick takeaway: Need 70B? Pick Beelink or GMKtec with 128 GB. Want silence and efficiency? Mac mini M4 Pro 64 GB. Best value for 30B? GMKtec 64 GB or Mac mini 64 GB. Need AI plus VMs plus Docker? Beelink or GMKtec with Linux.

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