What are the system requirements for KAONI-カメラで顔を取り戻せ- on PC?

Component Minimum: Recommended:
OS Windows 10+ x64 Windows 10+ x64
Processor Intel/AMD X64 architecture with SSE2 instruction set support Intel/AMD X64 architecture with SSE2 instruction set support
Memory 4 GB RAM 4 GB RAM
Graphics NVIDIA GTX 1060 6GB or AMD NVIDIA GTX 1060 6GB or AMD
DirectX Version 11 Version 11
Storage 550 MB available space 550 MB available space

What are the system requirements for KAONI-カメラで顔を取り戻せ- on PC?

To run KAONI-カメラで顔を取り戻せ- on your PC, you need at least a Intel/AMD X64 architecture with SSE2 instruction set support processor and a NVIDIA GTX 1060 6GB / AMD graphics card. For the best experience, a Intel/AMD X64 architecture with SSE2 instruction set support CPU and NVIDIA GTX 1060 6GB / AMD GPU are recommended. The game also requires a minimum of 4 GB RAM RAM, 550 MB available space of disk space, Windows 10+ x64 as your operating system, and DirectX 11. Check the full specification table above and compare it with your hardware to make sure KAONI-カメラで顔を取り戻せ- will run smoothly on your setup.

What GPU do I need for KAONI-カメラで顔を取り戻せ-?
The minimum GPU required for KAONI-カメラで顔を取り戻せ- is NVIDIA GTX 1060 6GB / AMD. For optimal performance, a NVIDIA GTX 1060 6GB / AMD or better is recommended.
How much RAM does KAONI-カメラで顔を取り戻せ- need?
KAONI-カメラで顔を取り戻せ- requires at least 4 GB RAM of RAM. The recommended amount is 4 GB RAM for the best experience.
How much disk space does KAONI-カメラで顔を取り戻せ- require?
You need at least 550 MB available space of available storage space to install KAONI-カメラで顔を取り戻せ-.
Can I run KAONI-カメラで顔を取り戻せ- on Mac or Linux?
The system requirements listed on this page are for the PC (Windows) version of KAONI-カメラで顔を取り戻せ-. Check the official store page for Mac or Linux compatibility.
What CPU is needed for KAONI-カメラで顔を取り戻せ-?
The minimum CPU for KAONI-カメラで顔を取り戻せ- is Intel/AMD X64 architecture with SSE2 instruction set support. For better performance, a Intel/AMD X64 architecture with SSE2 instruction set support processor is recommended.
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