- GMKTec EVO-X2 achieves faster build speeds than DGX Spark in large models
- First Token Latency Improvements Highlight AMD Ryzen AI Engine Efficiency
- Mini PC form factor delivers workstation-level AI performance
GMKtec's EVO-X2 has emerged as a powerful alternative to the Nvidia DGX Spark, offering high-performance AI computing at around half the price.
The company says its compact mini PC delivered faster build speeds for medium and large models like the GPT-OSS 20B and Llama 3.3 70B in recent benchmark tests.
First token latency was also lower across multiple tests, highlighting the efficiency of AMD's Ryzen AI engine and its optimized memory bandwidth.
GMKTec EVO-X2 stands out for now
The EVO-X2 supports a wide range of open source models and frameworks, including Llama, Qwen, Mistral, Ollama, LM Studio and vLLM, allowing developers to run AI workloads locally without relying on cloud resources, offering flexibility and data privacy.
The device's compact design also makes it suitable for high-performance mobile workstations where space and energy efficiency are important.
In terms of raw performance, the EVO-X2's dedicated AI acceleration offers low-latency, multi-threaded inference that directly competes with the DGX Spark.
The device handles real-world AI workloads effectively, enabling local deployment of large language models without the need for expensive enterprise infrastructure.
Its performance-to-power ratio is especially strong, providing workstation-level capability in a smaller, more energy-efficient package.
GMKtec's EVO-X2 is the world's first mini PC to launch with AMD's flagship Ryzen AI Max+ 395 APU.
The device is priced at €1,499 (approximately $1,735), less than half the $3,999 cost of the Nvidia DGX Spark.
This large price difference is hard to ignore, especially for organizations and individuals weighing budget against performance.
Despite this difference, Nvidia DGX Spark is still a premium enterprise-focused system, offering benefits in areas such as long-term reliability, multi-GPU scalability, and enterprise support.
Users with sustained or large-scale workloads may still prefer Nvidia's established system.
However, for developers, researchers, and professionals looking for a capable workstation or flexible business laptop, the EVO-X2 presents a practical, lower-cost alternative.
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