What are the system requirements for PAYDAY 2: Gunslinger Weapon Pack on PC?

Component Minimum: Recommended:
OS Windows 10
Processor 2 GHz Intel Dual Core Processor 2.3 GHz Intel Quad Core Processor
Memory 4 GB RAM 8 GB RAM
Graphics Nvidia & AMD (512MB VRAM) Nvidia & AMD (1GB VRAM)
DirectX Version 9.0c Version 9.0c
Storage 83 GB available space 83 GB available space

What are the system requirements for PAYDAY 2: Gunslinger Weapon Pack on PC?

To run PAYDAY 2: Gunslinger Weapon Pack on your PC, you need at least a 2 GHz Intel Dual Core Processor processor and a Nvidia & AMD (512MB VRAM) graphics card. For the best experience, a 2.3 GHz Intel Quad Core Processor CPU and Nvidia & AMD (1GB VRAM) GPU are recommended. The game also requires a minimum of 4 GB RAM RAM, 83 GB available space of disk space, — as your operating system, and DirectX 9.0c. Check the full specification table above and compare it with your hardware to make sure PAYDAY 2: Gunslinger Weapon Pack will run smoothly on your setup.

What GPU do I need for PAYDAY 2: Gunslinger Weapon Pack?
The minimum GPU required for PAYDAY 2: Gunslinger Weapon Pack is Nvidia & AMD (512MB VRAM). For optimal performance, a Nvidia & AMD (1GB VRAM) or better is recommended.
How much RAM does PAYDAY 2: Gunslinger Weapon Pack need?
PAYDAY 2: Gunslinger Weapon Pack requires at least 4 GB RAM of RAM. The recommended amount is 8 GB RAM for the best experience.
How much disk space does PAYDAY 2: Gunslinger Weapon Pack require?
You need at least 83 GB available space of available storage space to install PAYDAY 2: Gunslinger Weapon Pack.
Can I run PAYDAY 2: Gunslinger Weapon Pack on Mac or Linux?
The system requirements listed on this page are for the PC (Windows) version of PAYDAY 2: Gunslinger Weapon Pack. Check the official store page for Mac or Linux compatibility.
What CPU is needed for PAYDAY 2: Gunslinger Weapon Pack?
The minimum CPU for PAYDAY 2: Gunslinger Weapon Pack is 2 GHz Intel Dual Core Processor. For better performance, a 2.3 GHz Intel Quad Core Processor processor is recommended.
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