GMKtec / Enthusiast tier
GMKtec EVO-X2 (128GB)
Enthusiast-tier mini workstation: AMD Ryzen AI Max+ 395 with 128 GB of unified memory. Runs Llama 3.3 70B and Mistral Small 3.1 at roughly 15-25 tokens/s — 70B-class models without a discrete GPU, in a small-form-factor chassis.

- Sku
- CS-GEVOX2
- Chip
- AMD Ryzen AI Max+ 395
- Hdmi
- HDMI 2.1 ×1, up to 8K@60Hz
- Name
- GMKtec EVO-X2 AMD Ryzen AI Max+ 395 128GB RAM + 2TB SSD Windows 11 Pro Mini PC 2 years warranty (CS-GEVOX2)
The decision
Where it wins
- 128GB massive memory pool
- Ultra-compact form factor
- Dual NVMe storage slots
Where it doesn't
- APU graphics bottleneck token generation speed
- Audible fan noise under sustained load
Specifications
Structured product data, grouped by system.
Core hardware03
| Chip | AMD Ryzen AI Max+ 395 |
|---|---|
| Processor | AMD Ryzen™ AI Max+ 395, 16 cores / 32 threads, up to 5.1GHz |
| Runs | Llama 3.3 70B, Mistral Small 3.1 |
Memory & compute05
| Memory | 128GB LPDDR5X 8000MHz |
|---|---|
| Memory Form | Onboard LPDDR5X, typically not user-upgradeable |
| Memory Speed | 8000MHz |
| Memory Capacity | 128GB LPDDR5X |
| Unified memory | 128 GB |
AI & acceleration02
| Ai Npu | Based on AMD XDNA 2 architecture; AI TOPS performance varies by application, model, and settings |
|---|---|
| Throughput | 15-25 tok/s |
Display & media03
| Hdmi | HDMI 2.1 ×1, up to 8K@60Hz |
|---|---|
| Displayport | DisplayPort 1.4 ×1, up to 8K@60Hz |
| Display Output | HDMI 2.1 ×1, DisplayPort 1.4 ×1, USB4 ×2, supports up to 8K@60Hz display output, actual output depends on display, cables, and settings |
Physical & connectivity02
| Usb A | USB 3.2 ×3, USB 2.0 ×2 |
|---|---|
| Dimensions | Approximately 186 × 77 × 192 mm |
Other specifications12
| Sku | CS-GEVOX2 |
|---|---|
| Name | GMKtec EVO-X2 AMD Ryzen AI Max+ 395 128GB RAM + 2TB SSD Windows 11 Pro Mini PC 2 years warranty (CS-GEVOX2) |
| Audio | 3.5mm headphone / audio jack ×1 |
| Storage | 2TB M.2 2280 SSD; up to 2 M.2 2280 slots for expansion, actual capacity depends on SKU and hardware support |
| Warranty | 2 years |
| Bluetooth | Bluetooth 5.4 |
| Wired Network | 2.5G LAN ×1 |
| Sd Card Reader | Some official / retail data indicates SD Card Reader, actual shipping version varies |
| Operating System | Windows 11 Pro |
| Wireless Network | Wi-Fi 7 |
| Preloaded Storage | 2TB M.2 2280 SSD |
| Storage Expansion | Up to 2 M.2 2280 slots; expansion limit depends on actual unit and manufacturer data |
Read the record
- Source on record
- gmktec.com.hk
Packing 128GB of RAM into a mini-PC chassis enables running massive models that simply will not fit in standard consumer VRAM. While inference speed via CPU/APU is slower than discrete GPUs, the sheer memory capacity unlocks use cases previously restricted to cloud servers.
The EVO-X2 packs an AMD Ryzen AI Max+ 395 with 128GB of unified memory into a mini-PC chassis — enough to run Llama 3.3 70B and Mistral Small 3.1 at roughly 15–25 tokens/second without a discrete GPU.
What the memory unlocks
Models in the 70B class simply do not fit in standard consumer VRAM. 128GB addressable by the APU makes them loadable on a machine you can hold in one hand, drawing a fraction of the power a multi-GPU rig would. Dual NVMe slots handle the model library.
The trade-off is speed, as always with this architecture
The APU graphics bottleneck token generation — 15–25 tok/s is usable for interactive chat and retrieval, not for high-throughput serving or batch work. And the fan is audible under sustained load.
Who should buy
High-capacity context-retrieval workloads, CPU/APU-based LLM inference, and anyone who needs 70B-class capability in a small, quiet-ish box. If your target models fit in 16–24GB of VRAM, a discrete GPU runs them several times faster for less money.
Frequently Asked Questions
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Alternatives to consider
See all alternatives →Memory on record
- Another option Mac Mini M4 Pro (64GB)
64GB unified memory accessible by GPU
64 GBDesign score 9.5/10 - Another option Ryzen 5 + RTX 4060 Ti Build
16GB VRAM at entry-level pricing
16 GBDesign score 7.5/10 - Another option Nvidia GeForce RTX 3090 (Used)
24GB of GDDR6X memory for handling large datasets and complex scenes
Explore its evidenceDesign score 8.5/10
Where to buy
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Further reading
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