VENOEN/Topton P09/F9
VENOEN/Topton

P09/F9

CPU i5 8305G
GPU Vega M GL
Max RAM 32GB
Drives 3
From $380
Seller Aliexpress

The VENOEN/Topton P09/F9 is a mini PC powered by the Intel i5 8305G (8th gen). It features 4 performance cores and 8 threads and a soldered CPU. Graphics are handled by the discrete AMD Vega M GL. Supports up to 32GB of RAM across 2 slots. Storage capacity of up to 3 drives including 1 NVMe. Networking features 2 Ethernet ports (up to 1G). Dimensions: 228 × 148 × 52mm (1.75L).

CPU & Performance

CPUi5 8305G
Generation8th
P-Cores4
Threads8
Socket0

GPU

GPUVega M GL
Discrete GPUYes
Integrated GPUYes
eGPU supportNo

RAM

Max RAM32GB
RAM slots2
ECC supportNo

Storage

Max drives3
NVMe slots1
Gen3 x41
SD cardYes

Ports & Connectivity

Max displays4

Network

Max Ethernet2G
1G ports2

Physical

Dimensions228 × 148 × 52 mm
Volume1.75L
Fan size80mm

Power

Additional

Recommended for gaming, GPU-accelerated creative work, 3D or graphics-heavy tasks, and local storage expansion. Consider VENOEN/Topton P09/F9 if you want a small-form-factor mini PC built around its listed Intel i5 8305G processor and AMD Vega M GL discrete GPU plus integrated graphics. It is a stronger fit when the listed CPU, GPU, connectivity, and expansion features match your workload requirements.

VENOEN/Topton P09/F9 features Intel i5 8305G with AMD Vega M GL discrete GPU plus integrated graphics, offering 2× 1G Ethernet and expanded internal storage. CPU details include 8th CPU generation, 4 performance cores, and 8 threads. Memory support includes up to 32GB RAM across 2 slots. Storage support includes up to 3 storage drives including 1 NVMe SSD slot, 1× PCIe Gen3 x4 NVMe, and 1× M.2 SATA slot and SD card reader. Display support includes support for up to 4 displays. Networking includes 2× 1G Ethernet. Physical design includes a 228 × 148 × 52 mm chassis (1.75L). Cooling information lists 80 mm main fan.

The overall score is not populated for VENOEN/Topton P09/F9, so this model should be evaluated by the listed hardware specifications rather than by a ranked dataset position.

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