KAMRUI Pinova P1 Mini PC (AMD Ryzen 4300U) vs KAMRUI Pinova P2 Mini PC (AMD Ryzen 4300U)

Both have 16 GB memory, so bandwidth decides. KAMRUI Pinova P2 Mini PC (AMD Ryzen 4300U)'s 34 GB/s vs 34 GB/s translates directly to more tokens per second at equivalent model sizes.

Neither is optimised for image generation, but KAMRUI Pinova P2 Mini PC (AMD Ryzen 4300U)'s 34 GB/s bandwidth makes generation faster. Both run SDXL via Metal (macOS) or ROCm (Linux). Expect slower generation times than a discrete GPU.

Both draw around 28W at peak load.

KAMRUI Pinova P1 Mini PC (AMD Ryzen 4300U) edges ahead overall — better memory, bandwidth, and user ratings for local AI workloads. The gap is real but not always worth the price difference; assess based on your primary use case.

Q1Which runs Ollama faster — KAMRUI Pinova P1 Mini PC (AMD Ryzen 4300U) or KAMRUI Pinova P2 Mini PC (AMD Ryzen 4300U)?

KAMRUI Pinova P1 Mini PC (AMD Ryzen 4300U) runs Ollama faster. Its 34 GB/s memory bandwidth vs 34 GB/s means faster token generation — roughly 1.0× more tokens/second on the same model. On Llama 3.1 8B, expect around 1 tok/s vs 1 tok/s.

Q2Can either mini PC run Llama 3 70B?

Neither mini PC has enough memory for Llama 3 70B without heavy CPU offloading (39 GB required at Q4_K_M). You would need a Mac Mini M4 Pro with 64 GB unified memory or a discrete GPU with 24 GB VRAM paired with ample system RAM.

Q3Which is better value for local AI in 2026?

KAMRUI Pinova P1 Mini PC (AMD Ryzen 4300U) offers better performance-per-dollar for AI workloads due to its 34 GB/s bandwidth advantage. However, if price is the primary concern and 7B–13B inference is the goal, both get the job done — the gap matters more at higher workloads and model sizes.

Q4Which has better software support for local AI?

Both run Ollama well. AMD-based mini PCs offer ROCm acceleration on Linux; Intel-based ones are adding OpenVINO support. macOS Apple Silicon has the most polished Ollama experience.